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Proceedings Paper

Comparative study of logarithmic enhancement algorithms with performance measure
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Paper Abstract

Performance measures of image enhancement are traditionally subjective and have difficulty quantifying the improvement made by the algorithm. In this paper, we present the image enhancement measures and show how utilizing logarithmic arithmetic based addition, subtraction, and multiplication provides better results than previously used measures. In addition, for illustration of the performance of developed measures, we present a comprehensive study of several image enhancement algorithms from all three domains, including spatial, transform, and logarithmic algorithms.

Paper Details

Date Published: 17 February 2006
PDF: 12 pages
Proc. SPIE 6064, Image Processing: Algorithms and Systems, Neural Networks, and Machine Learning, 606412 (17 February 2006); doi: 10.1117/12.647489
Show Author Affiliations
Eric Wharton, Tufts Univ. (United States)
Sos Agaian, The Univ. of Texas at San Antonio (United States)
Karen Panetta, Tufts Univ. (United States)

Published in SPIE Proceedings Vol. 6064:
Image Processing: Algorithms and Systems, Neural Networks, and Machine Learning
Nasser M. Nasrabadi; Edward R. Dougherty; Jaakko T. Astola; Syed A. Rizvi; Karen O. Egiazarian, Editor(s)

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