This PDF file contains the front matter associated with SPIE Proceedings Volume 6808, including the Title Page, Copyright information, Table of Contents, and the Conference Committee listing.

In September 2000, INCITS W1 (the U.S. representative of ISO/IEC JTC1/SC28, the standardization committee for office equipment) was chartered to develop an appearance-based image quality standard.^(1),(2) The resulting W1.1 project is based on a proposal⁽³⁾ that perceived image quality can be described by a small set of broad-based attributes. There are currently six ad hoc teams, each working towards the development of standards for evaluation of perceptual image quality of color printers for one or more of these image quality attributes. This paper summarizes the work in progress of the teams addressing the attributes of Macro-Uniformity, Colour Rendition, Gloss & Gloss Uniformity, Text & Line Quality and Effective Resolution.

A flatbed reflection scanner is a tempting device to use as a surrogate for a microdensitometer in the evaluation of print image quality. Since reflection scanners were never designed with this purpose in mind, many concerns exist regarding their usefulness as a microdensitometer surrogate. This paper addresses the concerns regarding scan uniformity that must be addressed in order to qualify a reflection scanner for use in print image quality evaluation.

Edition 2 of ISO 12233, Resolution and Spatial Frequency Response (SFR) for Electronic Still Picture Imaging, is likely to offer a choice of techniques for determining spatial resolution for digital cameras different from the initial standard. These choices include 1) the existing slanted-edge gradient SFR protocols but with low contrast features, 2) polar coordinate sine wave SFR technique using a Siemens star element, and 3) visual resolution threshold criteria using a continuous linear spatial frequency bar pattern features. A comparison of these methods will be provided. To establish the level of consistency between the results of these methods, theoretical and laboratory experiments were performed by members of ISO TC42/WG18 committee. Test captures were performed on several consumer and SLR digital cameras using the on-board image processing pipelines. All captures were done in a single session using the same lighting conditions and camera operator. Generally, there was good conformance between methods albeit with some notable differences. Speculation on the reason for these differences and how this can be diagnostic in digital camera evaluation will be offered.

One of the first ISO digital camera standards to address image microstructure was ISO 12233, which introduced the SFR, spatial frequency response, based on the analysis of edge features in digital images. The SFR, whether derived from edges or periodic signals, describes the capture of image detail as a function of spatial frequency. Often during camera testing, however, there is an interest in distilling SFR results down to a single value that can be compared with acceptable tolerances. As a measure of limiting resolution, it has been suggested that the frequency at which the SFR falls to, e.g., 10%, can be used. We use this limiting resolution to introduce a sampling efficiency measure, being considered under the current ISO 12233 standard revision effort. The measure is the ratio of limiting resolution frequency to that implied by the image (sensor) sampling alone. The rationale and details of this measure are described, as are example measurements. One-dimensional sampling efficiency calculations for multiple directions are included in a two-dimensional analysis.

We explore two recent methods for measuring the Modeling Transfer Function of a printing system¹². We investigate the dependency on the amplitude when using the sinusoidal patches of the method proposed in¹ and show that for too small amplitudes the measurement of the MTF is not trustworthy. For the method proposed in² we discuss the underlying theory and in particular the use of a significance test for a statistical analysis. Finally we compare both methods with respect our application - the processing and printing of photographic images.

Printer resolution is an important attribute for determining print quality, and it has been frequently referred to hardware optical resolution. However, the spatial addressability of hardcopy is not directly related to optical resolution because it is affected by printing mechanism, media, or software data processing such as resolution enhancement techniques (RET). The international organization ISO/IEC SC28 addresses this issue, and makes efforts to develop a new metric to measure this effective resolution. As the development process, this paper proposes a candidate metric for measuring printer resolution. Slanted edge method has been used to evaluate image sharpness for scanners and digital still cameras. In this paper, it is applied to monochrome laser printers. A test chart is modified to reduce the effect of halftone patterns. Using a flatbed scanner, the spatial frequency response (SFR) is measured and modeled with a spline function. The frequency corresponding to 0.1 SFR is used in the metric for printer resolution. The stability of the metric is investigated in five separate experiments: (1) page to page variations, (2) different ROI locations, (3) different ROI sizes, (4) variations of toner density, and (5) correlation with visual quality. The 0.1 SFR frequencies of ten printers are analyzed. Experimental results show the strong correlation between a proposed metric and perceptual quality.

Mottle is a common defect in printing. Mottle evaluation is crucial in image quality assessment and system diagnosis. In this paper, we present a new automatic mottle estimation method which improves the existing technologies in two aspects. First, a modified mottle noise frequency range is proposed, which further separates the banding and streak spectra from mottle spectrum. Second, a robust estimation algorithm is introduced. It is less sensitive to the outliers that may appear in the measurement. These outliers include other defects within the mottle frequency range, such as spots, or defects outside of mottle frequency range, but are strong enough that can not be completely eliminated by normal spatial filtering.

In this paper, we propose new techniques for detecting and quantifying print defects. In our previous work, we introduced a scanner-based print quality system to characterize directional print defects, such as banding, jitter, and streaking. We extend our previous print quality work two ways. First, we introduce techniques for detecting 2-D isotropic, mottled print defects such as grain and mottle. Wavelet pre-filtering is used to limit the defect's size or frequency range. Then we analyze the L* variation in the wavelet-processed images. The methods used to quantify grain and mottle are similar to ISO/IEC 13660 techniques. The second part of this paper provides techniques for detecting and quantifying low frequency directional defects, which we call left-to-right and top-to-bottom L* variation. Since these defects extend less than two cycles across the page, and probably less than a complete cycle, we fit a 4th-degree polynomial to the defect profile. To measure the strength of the defect, we use variational analysis of the fitted polynomial. Experimental results on 10 printers and 100 print samples showed an average correlation for isotropic defects of 0.85 between the proposed measures and experts' visual evaluation, and 0.97 for low frequency defects.

Fine-pitch banding is one of the most unwanted artifacts in laser electrophotographic (EP) printers. It is perceived as a quasiperiodic fluctuation in the process direction. Therefore, it is essential for printer vendors to know how banding is perceived by humans in order to improve print quality. Monochrome banding has been analyzed and assessed by many researchers; but there is no literature that deals with the banding of color laser printers as measured from actual prints. The study of color banding is complicated by the fact that the color banding signal is physically defined in a three-dimensional color space, while banding perception is described in a one-dimensional sense such as more banding or less banding. In addition, the color banding signal arises from the independent contributions of the four primary colorant banding signals. It is not known how these four distinct signals combine to give rise to the perception of color banding. In this paper, we develop a methodology to assess the banding visibility of the primary colorant cyan based on human visual perception. This is our first step toward studying the more general problem of color banding in combinations of two or more colorants. According to our method, we print and scan the cyan test patch, and extract the banding profile as a one dimensional signal so that we can freely adjust the intensity of banding. Thereafter, by exploiting the pulse width modulation capability of the laser printer, the extracted banding profile is used to modulate a pattern consisting of periodic lines oriented in the process direction, to generate extrinsic banding. This avoids the effect of the halftoning algorithm on the banding. Furthermore, to conduct various banding assessments more efficiently, we also develop a softcopy environment that emulates a hardcopy image on a calibrated monitor, which requires highly accurate device calibration throughout the whole system. To achieve the same color appearance as the hardcopy, we perform haploscopic matching experiments that allow each eye to independently adapt to different viewing conditions; and we find an appearance mapping function in the adapted XYZ space. Finally, to validate the accuracy of the softcopy environment, we conduct a banding matching experiment at three different banding levels by the memory matching method, and confirm that our softcopy environment produces the same banding perception as the hardcopy. In addition, we perform two more separate psychophysical experiments to measure the differential threshold of the intrinsic banding in both the hardcopy and softcopy environments, and confirm that the two thresholds are statistically identical. The results show that with our target printer, human subjects can see a just noticeable difference with a 9% reduction in the banding magnitude for the cyan colorant.

Print mottle is one of the most significant defects in modern offset printing influencing overall print quality. Mottling can be defined as undesired unevenness in perceived print density. Previous research in the field considered designing and improving perception models for evaluating print mottle. Mottle has traditionally been evaluated by estimating the reflectance variation in the print. In our work, we present an approach of estimating mottling effect prior to printing. Our experiments included imaging non printed media under various lighting conditions, printing the samples with sheet fed offset printing and imaging afterwards. For the preprint examinations we used a set of preprint images and for the outcome testing we used high resolution scans. For the set of papers used in experiment only uncoated mechanical speciality paper showed a good chance of print mottle prediction. Other tested paper types had a low correlation between non-printed and printed images. The achieved results allow predicting the amount of mottling on the final print using preprint area images for a certain paper type. Current experiment settings suited well for uncoated paper, but for the coated samples other settings need to be tested. The results show that the estimation can be made on the coarse scale and for better results extra parameters will be required, i.e., paper type, coating, printing process in question.

In recent years, several methods for evaluation or quantification of video image quality have been studied, such as MPRT (Moving Picture Response Time) for quantification of motion blur occurred on hold-type displays. It is required to improve the methods or criteria to consider human visual characteristics, especially anisotropy and spatio-temporal dependency of contrast sensitivity. In this study, we quantify motion blur of the display by comparing it with static blur edge. We examine the influence of conditions for edge presentation, such as moving speed and moving direction of the edges, on perceived blurriness. According to the results of the assessment, we found that the anisotropy of the display had a significant influence on perception of motion blurs. This result suggests that multidirectional measurement is required to improve criteria of motion blur.

It is important to estimate the noise of digital image quantitatively and efficiently for many applications such as noise removal, compression, feature extraction, pattern recognition, and also image quality assessment. For these applications, it is necessary to estimate the noise accurately from a single image. Ce et al proposed a method to use a Bayesian MAP for the estimation of noise. In this method, the noise level function (NLF) which is standard deviation of intensity of image was estimated from the input image itself. Many NLFs were generated by using computer simulation to construct a priori information for Bayesian MAP. This a priori information was effective for the accurate noise estimation but not enough for practical applications since the a priori information didn't reflect the variable characteristics of the individual camera depending on the exposure and shutter speed. In this paper, therefore, we propose a new method to construct a priori information for specific camera in order to improve accuracy of noise estimation. To construct a priori information of noise, the NLFs were measured and calculated from the images captured under various conditions. We compared the accuracy of noise estimation between proposed method and Ce's model. The results showed that our model improved the accuracy of noise estimation.

Can images from professional digital SLR cameras be made equivalent in color using simple colorimetric characterization? Two cameras were characterized, these characterizations were implemented on a variety of images, and the results were evaluated both colorimetrically and psychophysically. A Nikon D2x and a Canon 5D were used. The colorimetric analyses indicated that accurate reproductions were obtained. The median CIELAB color differences between the measured ColorChecker SG and the reproduced image were 4.0 and 6.1 for the Canon (chart and spectral respectively) and 5.9 and 6.9 for the Nikon. The median differences between cameras were 2.8 and 3.4 for the chart and spectral characterizations, near the expected threshold for reliable image difference perception. Eight scenes were evaluated psychophysically in three forced-choice experiments in which a reference image from one of the cameras was shown to observers in comparison with a pair of images, one from each camera. The three experiments were (1) a comparison of the two cameras with the chart-based characterizations, (2) a comparison with the spectral characterizations, and (3) a comparison of chart vs. spectral characterization within and across cameras. The results for the three experiments are 64%, 64%, and 55% correct respectively. Careful and simple colorimetric characterization of digital SLR cameras can result in visually equivalent color reproduction.

The paper is focused on the implementation of a modular color image difference model, as described in [1], with aim to predict visual magnitudes between pairs of uncompressed images and images compressed using lossy JPEG and JPEG 2000. The work involved programming each pre-processing step, processing each image file and deriving the error map, which was further reduced to a single metric. Three contrast sensitivity function implementations were tested; a Laplacian filter was implemented for spatial localization and the contrast masked-based local contrast enhancement method, suggested by Moroney, was used for local contrast detection. The error map was derived using the CIEDE2000 color difference formula on a pixel-by-pixel basis. A final single value was obtained by calculating the median value of the error map. This metric was finally tested against relative quality differences between original and compressed images, derived from psychophysical investigations on the same dataset. The outcomes revealed a grouping of images which was attributed to correlations between the busyness of the test scenes (defined as image property indicating the presence or absence of high frequencies) and different clustered results. In conclusion, a method for accounting for the amount of detail in test is required for a more accurate prediction of image quality.

The mobile imaging market is a rapidly developing market, and has outgrown the traditional imaging market. This market is dominated by CMOS sensors, with pixels getting small and smaller. As pixel size is reduced, the sensitivity is lowered and must be compensated by longer exposure times. However, in the mobile market, this amount to increased motion blur. We characterize the hand motion with a typical shooting scenario. This data can be used to create an evaluation procedure for image stabilization solutions, and we indeed present one such procedure.

Quality assessment methods are classified into three types depending on the availability of the reference image or video: full-reference (FR), reduced-reference (RR), or no-reference (NR). This paper proposes efficient RR visual quality metrics, called motion vector histogram based quality metrics (MVHQMs). In assessing the visual quality of a video, the overall impression of a video tends to be regarded as the visual quality of the video. To compare two motion vectors (MVs) extracted from reference and distorted videos, we define the one-dimensional (horizontal and vertical) MV histograms as features, which are computed by counting the number of occurrences of MVs over all frames of a video. For testing the similarity between MV histograms, two different MVHQMs using the histogram intersection and histogram difference are proposed. We evaluate the effectiveness of the two proposed MVHQMs by comparing their results with differential mean opinion score (DMOS) data for 46 video clips of common intermediate format (CIF)/quarter CIF (QCIF) that are coded under varying bit rates/frame rates with H.263. We compare the performance of the proposed metrics and conventional quality measures. Experimental results with various test video sequences show that the proposed MVHQMs give better performance than the conventional methods in various aspects such as the performance, stability, and data size.

The study of the Human Visual System (HVS) is very interesting to quantify the quality of a picture, to predict which information will be perceived on it, to apply adapted tools ... The Contrast Sensitivity Function (CSF) is one of the major ways to integrate the HVS properties into an imaging system. It characterizes the sensitivity of the visual system to spatial and temporal frequencies and predicts the behavior for the three channels. Common constructions of the CSF have been performed by estimating the detection threshold beyond which it is possible to perceive a stimulus. In this work, we developed a novel approach for spatio-chromatic construction based on matching experiments to estimate the perception threshold. It consists in matching the contrast of a test stimulus with that of a reference one. The obtained results are quite different in comparison with the standard approaches as the chromatic CSFs have band-pass behavior and not low pass. The obtained model has been integrated in a perceptual color difference metric inspired by the s-CIELAB. The metric is then evaluated with both objective and subjective procedures.

The method of paired comparisons is often used in image quality evaluations. Psychometric scale values for quality judgments are modeled using Thurstone's Law of Comparative Judgment in which distance in a psychometric scale space is a function of the probability of preference. The transformation from psychometric space to probability is a cumulative probability distribution. The major drawback of a complete paired comparison experiment is that every treatment is compared to every other, thus the number of comparisons grows quadratically. We ameliorate this difficulty by performing paired comparisons in two stages, by precisely estimating anchors in the psychometric scale space which are spaced apart to cover the range of scale values and comparing treatments against those anchors. In this model, we employ a generalized linear model where the regression equation has a constant offset vector determined by the anchors. The result of this formulation is a straightforward statistical model easily analyzed using any modern statistics package. This enables model fitting and diagnostics. This method was applied to overall preference evaluations of color pictorial hardcopy images. The results were found to be compatible with complete paired comparison experiments, but with significantly less effort.

In this paper we discuss the application of online surveys to the field of image quality. We examine an online survey technique that measures the subject's response time, in particular the time it takes for the subject to identify which of two otherwise identical images contains an image defect. The efficiency and accuracy of the results will be discussed for a case where subjects are asked to identify defects known as graininess and mottle in photographs with a varying amount of "quiet regions".

Due to the rise in performance of digital printing, image-based applications are gaining popularity. This creates needs for specifying the quality potential of printers and materials in more detail than before. Both production and end-use standpoints are relevant. This paper gives an overview of an on-going study which has the goal of determining a framework model for the visual quality potential of paper in color image printing. The approach is top-down and it is founded on the concept of a layered network model. The model and its subjective, objective and instrumental measurement layers are discussed. Some preliminary findings are presented. These are based on data from samples obtained by printing natural image contents and simple test fields on a wide range of paper grades by ink-jet in a color managed process. Color profiles were paper specific. Visual mean opinion score data by human observers could be accounted for by two or three dimensions. In the first place these are related to brightness and color brightness. Image content has a marked effect on the dimensions. This underlines the challenges in designing the test images.

This study presents a methodology of forming contextually valid scales for subjective video quality measurement. Any single value of quality e.g. Mean Opinion Score (MOS) can have multiple underlying causes. Hence this kind of a quality measure is not enough for example, in describing the performance of a video capturing device. By applying Interpretation Based Quality (IBQ) method as a qualitative/quantitative approach we have collected attributes familiar to the end user and that are extracted directly from the material offered by the observers' comments. Based on these findings we formed contextually valid assessment scales from the typically used quality attributes. A large set of data was collected from 138 observers to generate the video quality vocabulary. Video material was shot by three types of video cameras: Digital video cameras (4), digital still cameras (9) and mobile phone cameras (9). From the quality vocabulary, we formed 8 unipolar 11-point scales to get better insight of video quality. Viewing conditions were adjusted to meet the ITU-T Rec. P.910 requirements. It is suggested that the applied qualitative/quantitative approach is especially efficient for finding image quality differences in video material where the quality variations are multidimensional in nature and especially when image quality is rather high.

The subjective quality of an image is a non-linear product of several, simultaneously contributing subjective factors such as the experienced naturalness, colorfulness, lightness, and clarity. We have studied subjective image quality by using a hybrid qualitative/quantitative method in order to disclose relevant attributes to experienced image quality. We describe our approach in mapping the image quality attribute space in three cases: still studio image, video clips of a talking head and moving objects, and in the use of image processing pipes for 15 still image contents. Naive observers participated in three image quality research contexts in which they were asked to freely and spontaneously describe the quality of the presented test images. Standard viewing conditions were used. The data shows which attributes are most relevant for each test context, and how they differentiate between the selected image contents and processing systems. The role of non-HVS based image quality analysis is discussed.

In psychological research, it is common to perform investigations on the World Wide Web in the form of questionnaires to collect data from a large number of participants. By comparison, visual experiments have been mainly performed in the laboratory, where it is possible to use calibrated devices and controlled viewing conditions. Recently, the Web has been exploited also for "uncontrolled" visual experiments, despite the lack of control on image rendering at the client side, assuming that the large number of participants involved in a Web investigation "averages out" the parameters that the experiments would require to keep fixed if, following a traditional approach, it was performed under controlled conditions. This paper describes the design and implementation of a Web-based visual experiment management system, which acts as a repository of visual experiment, and is designed with the purpose of facilitating the publishing of online investigations.

The psychological complexity of multivariate image quality evaluation makes it difficult to develop general image quality metrics. Quality evaluation includes several mental processes and ignoring these processes and the use of a few test images can lead to biased results. By using a qualitative/quantitative (Interpretation Based Quality, IBQ) methodology, we examined the process of pair-wise comparison in a setting, where the quality of the images printed by laser printer on different paper grades was evaluated. Test image consisted of a picture of a table covered with several objects. Three other images were also used, photographs of a woman, cityscape and countryside. In addition to the pair-wise comparisons, observers (N=10) were interviewed about the subjective quality attributes they used in making their quality decisions. An examination of the individual pair-wise comparisons revealed serious inconsistencies in observers' evaluations on the test image content, but not on other contexts. The qualitative analysis showed that this inconsistency was due to the observers' focus of attention. The lack of easily recognizable context in the test image may have contributed to this inconsistency. To obtain reliable knowledge of the effect of image context or attention on subjective image quality, a qualitative methodology is needed.

Images and videos are subject to a wide variety of distortions during acquisition, digitizing, processing, restoration, compression, storage, transmission and reproduction, any of which may result in degradation in visual quality. That is why image quality assessment plays a major role in many image processing applications. Image and video quality metrics can be classified by using a number of criteria such as the type of the application domain, the predicted distortion (noise, blur, etc.) and the type of information needed to assess the quality (original image, distorted image, etc.). In the literature, the most reliable way of assessing the quality of an image or of a video is subjective evaluation [1], because human beings are the ultimate receivers in most applications. The subjective quality metric, obtained from a number of human observers, has been regarded for many years as the most reliable form of quality measurement. However, this approach is too cumbersome, slow and expensive for most applications [2]. So, in recent years a great effort has been made towards the development of quantitative measures. The objective quality evaluation is automated, done in real time and needs no user interaction. But ideally, such a quality assessment system would perceive and measure image or video impairments just like a human being [3]. The quality assessment is so important and is still an active and evolving research topic because it is a central issue in the design, implementation, and performance testing of all systems [4, 5]. Usually, the relevant literature and the related work present only a state of the art of metrics that are limited to a specific application domain. The major goal of this paper is to present a wider state of the art of the most used metrics in several application domains such as compression [6], restoration [7], etc. In this paper, we review the basic concepts and methods in subjective and objective image/video quality assessment research and we discuss their performances and drawbacks in each application domain. We show that if in some domains a lot of work has been done and several metrics were developed, on the other hand, in some other domains a lot of work has to be done and specific metrics need to be developed.

To overcome shortcomings of digital image, or to reproduce grain of traditional silver halide photographs, some photographers add noise (grain) to digital image. In an effort to find a factor of preferable noise, we analyzed how a professional photographer introduces noise into B&W digital images and found two noticeable characteristics: 1) there is more noise in mid-tones, gradually decreasing in highlights and shadows toward the ends of tonal range, and 2) histograms in highlights are skewed toward shadows and vice versa, while almost symmetrical in mid-tones. Next, we examined whether the professional's noise could be reproduced. The symmetrical histograms were approximated by Gaussian distribution and skewed ones by chi-square distribution. The images on which the noise was reproduced were judged by the professional himself to be satisfactory enough. As the professional said he added the noise so that "it looked like the grain of B&W gelatin silver photographs," we compared the two kinds of noise and found they have in common: 1) more noise in mid-tones but almost none in brightest highlights and deepest shadows, and 2) asymmetrical histograms in highlights and shadows. We think these common characteristics might be one condition for "good" noise.

Most image quality metrics are derived from feature values of specified test charts. However, such test charts can explain only a small portion of the comprehensive performances on image quality of imaging systems. Thus, designers of imaging systems need to check every possible type of natural image to verify the performance even if they check every image quality factor by test charts. But it is not clear how many and what types of images should be used to verify the performances. Meanwhile a number of studies have shown that the amplitude spectrum of natural images falls inversely with spatial frequency. This paper proposes a new image quality evaluation methodology using a quasi-random noise image that has 1/f spectrum property as a generalized natural image. After being processed by image processing operations, the power spectra of the image show reasonable responses to the operations and their parameters. In addition, a metric derived from this image can predict the subjective judgments on the spatial reproducibility of imaging systems with a high correlation coefficient. The results suggest that this image can be used for the purpose of evaluation of the comprehensive performance on image quality of imaging systems.

Quality assessment is a very challenging problem and will still as is since it is difficult to define universal tools. So, subjective assessment is one adapted way but it is tedious, time consuming and needs normalized room. Objective metrics can be with reference, with reduced reference and with no-reference. This paper presents a study carried out for the development of a no-reference objective metric dedicated to the quality evaluation of display devices. Initially, a subjective study has been devoted to this problem by asking a representative panel (15 male and 15 female; 10 young adults, 10 adults and 10 seniors) to answer questions regarding their perception of several criteria for quality assessment. These quality factors were hue, saturation, contrast and texture. This aims to define the importance of perceptual criteria in the human judgment of quality. Following the study, the factors that impact the quality evaluation of display devices have been proposed. The development of a no-reference objective metric has been performed by using statistical tools allowing to separate the important axes. This no-reference metric based on perceptual criteria by integrating some specificities of the human visual system (HVS) has a high correlation with the subjective data.

A quality metric based on a classification process is introduced. The main idea of the proposed method is to avoid the error pooling step of many factors (in frequential and spatial domain) commonly applied to obtain a final quality score. A classification process based on final quality class with respect to the standard quality scale provided by the UIT. Thus, for each degraded color image, a feature vector is computed including several Human Visual System characteristics, such as, contrast masking effect, color correlation, and so on. Selected features are of two kinds: 1) full-reference features and 2) no-reference characteristics. That way, a machine learning expert, providing a final class number is designed.

Multifunctional devices (MFDs) are increasingly used as a document hub. The MFD is used as a copier, scanner, printer, and it facilitates digital document distribution and sharing. This imposes new requirements on the design of the data path and its image processing. Various design aspects need to be taken into account, including system performance, features, image quality, and cost price. A good balance is required in order to develop a competitive MFD. A modular datapath architecture is presented that supports all the envisaged use cases. Besides copying, colour scanning is becoming an important use case of a modern MFD. The copy-path use case is described and it is shown how colour scanning can also be supported with a minimal adaptation to the architecture. The key idea is to convert the scanner data to an opponent colour space representation at the beginning of the image processing pipeline. The sub-sampling of chromatic information allows for the saving of scarce hardware resources without significant perceptual loss of quality. In particular, we have shown that functional FPGA modules from the copy application can also be used for the scan-to-file application. This makes the presented approach very cost-effective while complying with market conform image quality standards.

Ideally, a quality assessment system would perceive and measure image or video impairments just like a human being. But in reality, objective quality metrics do not necessarily correlate well with perceived quality [1]. Plus, some measures assume that there exists a reference in the form of an "original" to compare to, which prevents their usage in digital restoration field, where often there is no reference to compare to. That is why subjective evaluation is the most used and most efficient approach up to now. But subjective assessment is expensive, time consuming and does not respond, hence, to the economic requirements [2,3]. Thus, reliable automatic methods for visual quality assessment are needed in the field of digital film restoration. The ACE method, for Automatic Color Equalization [4,6], is an algorithm for digital images unsupervised enhancement. It is based on a new computational approach that tries to model the perceptual response of our vision system merging the Gray World and White Patch equalization mechanisms in a global and local way. Like our vision system ACE is able to adapt to widely varying lighting conditions, and to extract visual information from the environment efficaciously. Moreover ACE can be run in an unsupervised manner. Hence it is very useful as a digital film restoration tool since no a priori information is available. In this paper we deepen the investigation of using the ACE algorithm as a basis for a reference free image quality evaluation. This new metric called DAF for Differential ACE Filtering [7] is an objective quality measure that can be used in several image restoration and image quality assessment systems. In this paper, we compare on different image databases, the results obtained with DAF and with some subjective image quality assessments (Mean Opinion Score MOS as measure of perceived image quality). We study also the correlation between objective measure and MOS. In our experiments, we have used for the first image test set "Single Stimulus Continuous Quality Scale" (SSCQS) method and in the second "Double Stimulus Continuous Quality Scale" (DSCQS) method. The users, which are non-experts, were asked to identify their preferred image (between original and ACE filtered images) according to contrast, naturalness, colorfulness, quality, chromatic diversity and overall subjective preference. Test and results are presented.

Image evaluation and quality measurements are fundamental components in all image processing applications and techniques. Recently, a no-reference perceptual blur metrics (PBM) was suggested for numerical evaluation of blur effects. The method is based on computing the intensity variations between neighboring pixels of the input image before and after low-pass filtering. The method was proved to demonstrate a very good correlation between the quantitative measure it provides and visual evaluation of perceptual image quality. However, this quantitative image blurriness measure has no intuitive meaning and has no association with conventionally accepted imaging system design parameters such as, for instance, image bandwidth. In this paper, we suggest an extended modification of this PBM-method that provides such a direct association and allows evaluation image in terms of the image efficient bandwidth. To this end we apply the PBM-method to a series of test pseudo-random images with uniform spectrum of different spread within the image base-band defined by the image sampling rate and map the image blur measurement results obtained for this set of test images to corresponding measures of their bandwidths. In this way we obtain a new image feature, which provides evaluation of image in terms of the image effective bandwidth measured in fractions, from 0 to 1, of the image base-band. In addition, we also show that the effective bandwidth measure provides a good estimation for the potential JPEG encoder compression rate, which allows one to choose the best compression quality for a requested compressed image size.

Colour information is not faithfully maintained by a CCTV imaging chain. Since colour can play an important role in identifying objects it is beneficial to be able to account accurately for changes to colour introduced by components in the chain. With this information it will be possible for law enforcement agencies and others to work back along the imaging chain to extract accurate colour information from CCTV recordings. A typical CCTV system has an imaging chain that may consist of scene, camera, compression, recording media and display. The response of each of these stages to colour scene information was characterised by measuring its response to a known input. The main variables that affect colour within a scene are illumination and the colour, orientation and texture of objects. The effects of illumination on the appearance of colour of a variety of test targets were tested using laboratory-based lighting, street lighting, car headlights and artificial daylight. A range of typical cameras used in CCTV applications, common compression schemes and representative displays were also characterised.

The goal of our study is to clarify the realistic viewing conditions surrounding flat panel display television (FPD TV) and the relationship between preferred luminance and TV screen size, as flat panel display TV is becoming increasingly popular. We have conducted an investigation of TV viewing conditions at homes. Our study of viewing conditions indicates that the viewing distance at home is 3 times of absolute display height at minimum with an average of 2.5m and mean screen illuminance is 100-300 lx. We also have conducted an investigation of the relationship between preferred luminance and TV screen size using LCD TV. Our study indicates that the most preferred luminance depends on visual angle (screen size and viewing distance). At fixed viewing distance, the most preferred luminance depends on TV screen size. As TV screen size gets larger, the most preferred luminance becomes darker. And in home, most preferred luminance of distance 3 times of absolute display height (3H) and screen illuminance at 180 lx is approximately 240cd/m². And as the screen illuminance becomes darker, the most preferred luminance becomes darker while the most preferred luminance depends on visual angle.

Display image quality, image reproducibility and compliance to standards are getting more and more important. It is known that LCDs suffer from viewing angle dependency, meaning that the characteristics of the LCD change with viewing angle. Display calibration and corresponding quality checks typically take place for on-axis viewing. However, users typically use their display under a rather broad range of viewing angles. Several studies have shown that when calibration is done for on-axis viewing then the display is not accurately complying with the standard when viewing off-axis. A possible solution is tracking the position of the user in real-time and adapting the configuration/characteristics of the display accordingly. In this way the user always perceives the display as being calibrated independently of the viewing angle. However, this method requires an expensive user tracking method (such as an infrared, ultrasound or vision based head tracking device) and is not useful for multiple concurrent users. This paper presents another solution: instead of tracking the user and dynamically changing the behavior of the display, we develop calibration algorithms that have inherent robustness against change of viewing angle. This new method also has the advantage that it is a very cheap solution that does not require additional hardware such as head tracking. In addition it also works for multiple viewers.

There are many uses of an image quality measure. It is often used to evaluate the effectiveness of an image processing algorithm, yet there is no one widely used objective measure. It can be used to compare similarity between two-dimensional data. In many papers, the mean squared error (MSE) or peak signal to noise ratio (PSNR) are used. These measures rely on pixel intensities instead of image structure. Though these measures are well understood and easy to implement, they do not correlate well with perceived image quality. This paper will present an image quality metric that analyzes image structure rather than entirely on pixels. It extracts image structure with the use of quadtree decomposition. A similarity comparison function based on contrast, luminance, and structure will be presented.

Two internet-based psychophysical experiments were conducted to investigate the performance of an image sharpness enhancement method, based on adjustment of spatial frequencies in the image according to the contrast sensitivity function and compensation of MTF losses of the display. The method was compared with the widely-used unsharp mask (USM) filter from PhotoShop. The experiment was performed in two locations with different groups of observers: one in the UK, and the second in the USA. Three Apple LCD displays (15" studio, 23" HD cinema and 15" PowerBook) were used at both sites. Observers assessed the sharpness and pleasantness of the displayed images. Analysis of the results led to four major conclusions: (1) Performance of the sharpening methods; (2) Influence of MTF compensation; (3) Image dependency; and (4) Comparison between sharpness perception and preference judgement at both sites.

We propose a statistical technique for autonomously detecting defective pixels in a CCD sensor array. Our data-driven analysis technique can autonomously identify a wide range of faulty and 'suspect' pixels (hypo-sensitive or hyper-sensitive pixels), without the need for any defect model or prior knowledge of the nature of pixel faults. We apply our technique to the autonomous detection of the defective pixels in regular images captured with a camera, equipped with a CCD.

In traditional super-resolution methods, researchers generally assume that accurate subpixel image registration parameters are given a priori. In reality, accurate image registration on a subpixel grid is the single most critically important step for the accuracy of super-resolution image reconstruction. In this paper, we introduce affine invariant features to improve subpixel image registration, which considerably reduces the number of mismatched points and hence makes traditional image registration more efficient and more accurate for super-resolution video enhancement. Affine invariant interest points include those corners that are invariant to affine transformations, including scale, rotation, and translation. They are extracted from the second moment matrix through the integration and differentiation covariance matrices. Our tests are based on two sets of real video captured by a small Unmanned Aircraft System (UAS) aircraft, which is highly susceptible to vibration from even light winds. The experimental results from real UAS surveillance video show that affine invariant interest points are more robust to perspective distortion and present more accurate matching than traditional Harris/SIFT corners. In our experiments on real video, all matching affine invariant interest points are found correctly. In addition, for the same super-resolution problem, we can use many fewer affine invariant points than Harris/SIFT corners to obtain good super-resolution results.

The quality of encoded image sequences is often assessed by a subjective test. Depending of the test paradigm used in the subjective campaign the observer get as much time as he needs to find a stable result. In video sequences, three parameters have to be managed carefully: the bitrate, the frame-rate and the motion contained in video itself. Therefore it is desirable to know the relation between the frame rate, the motion, the bitrate and the quality. This study aims to allow the selection of coherent contents for the subjective assessment experiments. For example, at which frame-rate a sequence has to be displayed in order to have a correct judgment of its quality. The image sequences were presented with five different frame-rates ranging from 10 to 40 and four bitrates ranging between 0.12bpp and 0.32bpp. The video sequences were chosen with regards to their motion quantity. The motion has been characterized using the specification of MPEG-7 in order to organize the optical flux in several classes. Special care was taken to avoid the memorization effect usually present after short presentations.

From image retrieval to image classification, all research shares one common requirement: a good image database to test or train the algorithms. In order to create a large database of images, we set up a project that allowed gathering a collection of more than 33000 photographs with keywords and tags from all over the world. This project was part of the "We Are All Photographers Now!" exhibition at the Musee de l'Elysee in Lausanne, Switzerland. The "Flux," as it was called, gave all photographers, professional or amateur, the opportunity to have their images shown in the museum. Anyone could upload pictures on a website. We required that some simple tags were filled in. Keywords were optional. The information was collected in a MySQL database along with the original photos. The pictures were projected at the museum in five second intervals. A webcam snapshot was taken and sent back to the photographers via email to show how and when their image was displayed at the museum. During the 14 weeks of the exhibition, we collected more than 33000 JPEG pictures with tags and keywords. These pictures come from 133 countries and were taken by 9042 different photographers. This database can be used for non-commercial research at EPFL. We present some preliminary analysis here.

Assessing the perceptual quality of pictures still remains a difficult task even for humans. This is true, especially when there are many interesting regions to look at (e.g. sea and foreground subject) or when the differences among the pictures are subtle. Despite that, trends in user preference do exist and they can be a valuable source of information for designing enhancement algorithms. However, a major problem is to assess preference trends and to translate them in an algorithm with a formal methodology. The approach that we describe in this paper proposes a multi-step solution. In the first instance we relate the space of possible enhancement sequences (intended as chain of enhancement algorithms) to the content of the image and then reduce the number of sequences through an iterative selection penalizing the sequences that produce artifacts or that generates close results. We then present the user with pairs of images enhanced with the various sequences and we ask to select the best in each comparison. Finally, we perform a statistical analysis of users' votes through a statistical method. Preliminary results show preference for saturated and colorful sea and sky and "de-saturated" snow.

It is a myth that more pixels alone result in better images. The marketing of camera phones in particular has focused on their pixel numbers. However, their performance varies considerably according to the conditions of image capture. Camera phones are often used in low-light situations where the lack of a flash and limited exposure time will produce underexposed, noisy and blurred images. Camera utilization can be quantitatively described by photospace distributions, a statistical description of the frequency of pictures taken at varying light levels and camera-subject distances. If the photospace distribution is known, the user-experienced distribution of quality can be determined either directly by direct measurement of subjective quality, or by photospace-weighting of objective attributes. The population of a photospace distribution requires examining large numbers of images taken under typical camera phone usage conditions. ImagePhi was developed as a user-friendly software tool to interactively estimate the primary photospace variables, subject illumination and subject distance, from individual images. Additionally, subjective evaluations of image quality and failure modes for low quality images can be entered into ImagePhi. ImagePhi has been applied to sets of images taken by typical users with a selection of popular camera phones varying in resolution. The estimated photospace distribution of camera phone usage has been correlated with the distributions of failure modes. The subjective and objective data show that photospace conditions have a much bigger impact on image quality of a camera phone than the pixel count of its imager. The 'megapixel myth' is thus seen to be less a myth than an ill framed conditional assertion, whose conditions are to a large extent specified by the camera's operational state in photospace.

The image quality circle is a commonly accepted framework to model the relation between the technology variables of a display and the resulting image quality. 3D-TV systems, however, go beyond the concept of image quality. Research has shown that, although 3D scenes are clearly more appreciated by subjects, the concept 'image quality' does not take this added value of depth into account. Concepts as 'naturalness' and 'viewing experience' have turned out to be more useful when assessing the overall performance of 3D displays. In this paper, experiments are described that test 'perceived depth', 'perceived image quality' and 'perceived naturalness' in images with different levels of blur and different depth levels. Results show that naturalness incorporates both blur level as well as depth level, while image quality does not include depth level. These results confirm that image quality is not a good measure to assess the overall performance of 3D displays. Naturalness is a more promising concept.

Texture is an important element of the world around us. It can convey information about the object at hand. Although embossing has been used in a limited way, to enhance the appearance of greeting cards and book covers for example, texture is something that printed material traditionally lacks. Recently, techniques have been developed that allow the incorporation of texture in printed material. Prints made using such processes are similar to traditional 2D prints but have added texture such that a reproduction of an oil painting can have the texture of oil paint on canvas or a picture of a lizard can actually have the texture of lizard skin. It seems intuitive that the added dimensionality would add to the perceived quality of the image, but to what degree? To examine the question of the impact of a third dimension on the perceived quality of printed images, a survey was conducted asking participants to determine the relative worth of sets of print products. Pairs of print products were created, where one print of each pair was 2D and the other was the same image with added texture. Using these print pairs, thirty people from the Rochester Institute of Technology community were surveyed. The participants were shown seven pairs of print products and asked to rate the relative value of each pair by apportioning a specified amount of money between the two items according to their perception of what each item was worth. The results indicated that the addition of a third dimension or texture to the printed images gave a clear boost to the perceived worth of the printed products. The rating results were 50% higher for the 3D products than the 2D products, with the participants apportioning approximately 60% of each dollar to the 3D product and 40% to the 2D product. About 80% of the time participants felt that the 3D items had at least some added value over their 2D counterparts, about 15% of the time, they felt the products were essentially equivalent in value and 4% of the time they rated the 3D product as having lower value than the 2D product. The comments of the participants indicated that they were clearly impressed with the 3D technology and their ratings indicated that they were might be willing to pay more for it, meaning advertisers and package designers will be interested in using this technology in their products. As 3D printing technology emerges it will add yet another dimension to the work of print quality analysis.

Stereoscopic technologies have developed significantly in recent years. These advances require also more understanding of the experiental dimensions of stereoscopic contents. In this article we describe experiments in which we explore the experiences that viewers have when they view stereoscopic contents. We used eight different contents that were shown to the participants in a paired comparison experiment where the task of the participants was to compare the same content in stereoscopic and non-stereoscopic form. The participants indicated their preference but were also interviewed about the arguments they used when making the decision. By conducting a qualitative analysis of the interview texts we categorized the significant experiental factors related to viewing stereoscopic material. Our results indicate that reality-likeness as well as artificiality were often used as arguments in comparing the stereoscopic materials. Also, there were more emotional terms in the descriptions of the stereoscopic films, which might indicate that the stereoscopic projection technique enhances the emotions conveyed by the film material. Finally, the participants indicated that the three-dimensional material required longer presentation time, as there were more interesting details to see.