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Proceedings Paper

Image segmentation by multiresolution histogram decomposition
Author(s): Ramana L. Rao; Lakshman Prasad
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Paper Abstract

An image segmentation scheme based on multiresolutional, successive approximations of the image histogram is proposed. The algorithm begins with a coarse, initial segmentation of the image obtained by selecting thresholds from a coarse sampling of a low-pass filtered version of the image histograms. This segmentation is refined by selecting thresholds from increasingly better approximations of the histogram. The algorithm is linear in the size of the input image and handles images with multimodal histograms. Preliminary results indicate that the approach shows promise as a simple, computationally efficient algorithm for hierarchical image segmentation. The algorithm may easily be embedded in the `split' phase of any of the well known split-and-merge type segmentation algorithms.

Paper Details

Date Published: 1 September 1995
PDF: 12 pages
Proc. SPIE 2569, Wavelet Applications in Signal and Image Processing III, (1 September 1995); doi: 10.1117/12.217630
Show Author Affiliations
Ramana L. Rao, Los Alamos National Lab. (United States)
Lakshman Prasad, Los Alamos National Lab. (United States)


Published in SPIE Proceedings Vol. 2569:
Wavelet Applications in Signal and Image Processing III
Andrew F. Laine; Michael A. Unser, Editor(s)

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