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A novel method for design of gray‐level transformation functions for image contrast improvement based on the histogram equalization technique
Author(s) -
Murahira Kota,
Kawakami Takashi,
Taguchi Akira
Publication year - 2013
Publication title -
electronics and communications in japan
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.131
H-Index - 13
eISSN - 1942-9541
pISSN - 1942-9533
DOI - 10.1002/ecj.11397
Subject(s) - histogram equalization , adaptive histogram equalization , histogram matching , balanced histogram thresholding , histogram , image histogram , artificial intelligence , pattern recognition (psychology) , color normalization , computer vision , computer science , mathematics , image processing , image (mathematics) , image texture , color image
Summary Histogram equalization ( HE ) is a simple and effective method for contrast enhancement as it can automatically define the gray‐level transformation function based on the distribution of gray levels included in an image. HE fails to produce satisfactory results for a broad variety of low‐contrast images because HE does not use the spatial features included in the input image. This paper proposes a novel contrast enhancement method using not only the conventional histogram but also the differential gray‐level histogram of the input image. The differential gray‐level histogram contains edge information from the input image. Edge information is one of the important spatial features of the image. We can extract the regions that are to be emphasized by using both the conventional histogram and the differential gray‐level histogram. The input histogram is modified by the histogram of the extracted regions. The gray‐level transformation function is derived using the modified histogram. © 2013 Wiley Periodicals, Inc. Electron Comm Jpn, 96(7): 57–66, 2013; Published online in Wiley Online Library ( wileyonlinelibrary.com ). DOI 10.1002/ecj.11397