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23‐2: An Adaptive Contrast Enhancement of Image Using Multi‐Scale Histogram Representation
Author(s) -
Jin Yu-Feng,
Syu Shen-Sian,
Jou Ming-Jong
Publication year - 2017
Publication title -
sid symposium digest of technical papers
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.351
H-Index - 44
eISSN - 2168-0159
pISSN - 0097-966X
DOI - 10.1002/sdtp.11634
Subject(s) - adaptive histogram equalization , lookup table , histogram equalization , computer science , histogram , representation (politics) , artificial intelligence , contrast (vision) , image (mathematics) , computer vision , equalization (audio) , filter (signal processing) , gaussian , scale (ratio) , function (biology) , table (database) , algorithm , data mining , decoding methods , physics , quantum mechanics , politics , political science , law , programming language , evolutionary biology , biology
A novel method is presented to enhance images using histogram equalization and provide excellent performance on local contrast improvement. The proposal includes multi‐scale function to make local LUT (Look‐Up Table; LUT) with global information to reduce boundary contour issue, and Gaussian filter is applied to reduce hardware cost. Furthermore, an adaptive parameter adjustment mechanism is also employed to optimize the enhancement performance under various scenes.