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Proceedings Paper

Logarithmic transform coefficient histogram matching with spatial equalization
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Paper Abstract

In this paper we propose an image enhancement algorithm that is based on utilizing histogram data gathered from transform domain coefficients that will improve on the limitations of the histogram equalization method. Traditionally, classical histogram equalization has had some problems due to its inherent dynamic range expansion. Many images with data tightly clustered around certain intensity values can be over enhanced by standard histogram equalization, leading to artifacts and overall tonal change of the image. In the transform domain, one has control over subtle image properties such as low and high frequency content with their respective magnitudes and phases. However, due to the nature of many of these transforms, the coefficient’s histograms may be so tightly packed that distinguishing them from one another may be impossible. By placing the transform coefficients in the logarithmic transform domain, it is easy to see the difference between different quality levels of images based upon their logarithmic transform coefficient histograms. Our results demonstrate that combing the spatial method of histogram equalization with logarithmic transform domain coefficient histograms achieves a much more balanced enhancement, that out performs classical histogram equalization.

Paper Details

Date Published: 25 May 2005
PDF: 13 pages
Proc. SPIE 5817, Visual Information Processing XIV, (25 May 2005); doi: 10.1117/12.603542
Show Author Affiliations
Blair Silver, Tufts Univ. (United States)
Sos Agaian, Univ. of Texas at San Antonio (United States)
Karen Panetta, Tufts Univ. (United States)

Published in SPIE Proceedings Vol. 5817:
Visual Information Processing XIV
Zia-ur Rahman; Robert A. Schowengerdt; Stephen E. Reichenbach, Editor(s)

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