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Spie Press Book

High Dynamic Range Imaging: Sensors and Architectures
Author(s): Arnaud Darmont
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Book Description

Illumination is a crucial element in many applications, matching the luminance of the scene with the operational range of a camera. When luminance cannot be adequately controlled, a high dynamic range (HDR) imaging system may be necessary. These systems are being increasingly used in automotive on-board systems, road traffic monitoring, and other industrial, security, and military applications. This book provides readers with an intermediate discussion of HDR image sensors and techniques for industrial and non-industrial applications. It describes various sensor and pixel architectures capable of achieving HDR imaging, as well as software approaches to make high dynamic range images out of lower dynamic range sensors or image sets. Some methods for automatic control of exposure and dynamic range of image sensors are also introduced.

Book Details

Date Published: 3 January 2013
Pages: 138
ISBN: 9780819488305
Volume: PM214

Table of Contents
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1 Introduction
1.1 Applications Requiring a Higher Dynamic Range
1.2 High Dynamic Range Photography
1.3 Scientific Applications
1.4 High Dynamic Range, Wide Dynamic Range, and Extended Dynamic Range
1.5 Outline and Goals
1.6 Defining a Camera

2 Dynamic Range
2.1 Image Sensor Theory
     2.1.1 Light source, scene, pixel, and irradiance
     2.1.2 Sensing node and light-matter interaction
     2.1.3 Pixel
     2.1.4 Pixel array
     2.1.5 Readout circuits
     2.1.6 Image encoding
2.2 Low-Light Imaging Limitations
     2.2.1 Noise sources summary
     2.2.2 Lowest detectable limit
2.3 Bright-Light Imaging Limitations
     2.3.1 Saturation
     2.3.2 Highest detectable level
2.4 Signal-to-Noise Ratio
2.5 Dynamic Range Gaps
     2.5.1 Response curve
     2.5.2 Dynamic range gaps
     2.5.3 Presence function of dynamic range gaps
2.6 Dynamic Range
     2.6.1 Definition
     2.6.2 Remark
     2.6.3 Relative measurement
2.7 Image Information
2.8 Human Vision System and Its Dynamic Range
     2.8.1 General properties of human vision
     2.8.2 Dynamic range of the human eye
     2.8.3 Noise perception
     2.8.4 Optical performance

3 Hardware Methods to Extend the Dynamic Range
3.1 Introduction: Integrating Linear Pixels
     3.1.1 Rolling-shutter pixel architecture
     3.1.2 Global-shutter pixel architecture
     3.1.3 SNR and dynamic range study
3.2 Multilinear Pixels
     3.2.1 Principle
     3.2.2 How can multiple segments be practically realized?
     3.2.3 Multiple segments method based on well sizing
     3.2.4 Dynamic compression
     3.2.5 SNR and dynamic range study
3.3 Multiple Sampling
3.4 Multiple-Sensing Nodes
3.5 Logarithmic Pixels
3.6 Logarithmic Photovoltaic Pixel
3.7 Time to Saturation
3.8 Gradient-Based Image
3.9 Light to Frequency
3.10 Other Methods
3.11 Multiple Readout Gains
3.12 Multiple-Exposure Windows
3.13 Summary
3.14 Companding ADCs
3.15 Extended Dynamic Range Color Imaging
3.16 Sensors Used in Applications

4 Software Methods to Extend the Dynamic Range
4.1 General Structure of a Software Approach
4.2 High Dynamic Range Image Data Merging
     4.2.1 Ideal case
     4.2.2 Real sensors and cameras
     4.2.3 Debevec's algorithm
     4.2.4 Alternate method: Mann and Picard
     4.2.5 Alternate method: Mitsunaga and Nayar
     4.2.6 Alternate method: Robertson et al.
4.3 Noise Removal
     4.3.1 Temporal pixel noise
     4.3.2 Ghosts and misalignments
4.4 Tone Mapping
4.5 Software Methods Applicable to Certain Image Processing Applications
4.6 Sensors with Integrated Processing
4.7 Simulated High Dynamic Range Images

5 Optical Limitations
5.1 Lens Glare
5.2 Modulation Transfer Function
5.3 Conclusions

6 Automatic High Dynamic Range Control
6.1 Automatic Exposure of Linear Sensors
     6.1.1 Principle
     6.1.2 Brightness calculation
     6.1.3 Filtering and stability for machine vision
     6.1.4 Filtering and stability for display
     6.1.5 Guard band based filtering
6.2 Automatic Exposure of High Dynamic Range Sensors

7 High Dynamic Range File Formats
7.1 Color Space
     7.1.1 Introduction
     7.1.2 Color space definition
7.2 Storing Image Data of Extended Dynamic Range Cameras
7.3 Storing Data of Radiance Maps and High Dynamic Range Software: Direct Pixel Encoding Methods
     7.3.1 IEEE single precision floating point
     7.3.2 Pixar log encoding
     7.3.3 Radiance RGBE
     7.3.4 SGI LogLuv TIFF
     7.3.5 Industrial Light and Magic OpenEXR
     7.3.6 Unified Color BEF
     7.3.7 Microsoft/HP scRGB
     7.3.8 JPEG XR
     7.3.9 Summary of file formats
7.4 Storing Data of Radiance Maps and High Dynamic Range Software: Gradient-Based and Flow-Based Methods

8 Testing High Dynamic Range Sensors, Cameras, and Systems
8.1 Testing of Software-Based Systems
8.2 Testing of Non-High Dynamic Range (Linear) Sensors and Cameras
     8.2.1 The ISO approach
     8.2.2 The EMVA1288 approach
8.3 Testing of High Dynamic Range Sensors and High Dynamic Range Sensor-Based Cameras
     8.3.1 The ISO approach
     8.3.2 The EMVA1288 approach

9 Conclusions
9.1 Important Figures of Merit of a High Dynamic Range Sensor
9.2 Questions

References



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