A Comparative Study between Brightness Preserving Bi-histogram and Tri-histogram Equalization for Image Contrast Enhancement
Author(s) -
Al Mehdi,
M. Shahidur
Publication year - 2016
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/ijca2016909233
Subject(s) - histogram equalization , adaptive histogram equalization , computer science , histogram matching , brightness , histogram , contrast (vision) , artificial intelligence , equalization (audio) , computer vision , pattern recognition (psychology) , color normalization , image (mathematics) , image processing , algorithm , color image , optics , physics , decoding methods
This paper compares brightness preserving image enhancement techniques using bi-histogram equalization and tri-histogram equalization methods. Traditionally for image contrast enhancement, global histogram equalization technique is used extensively. However, global histogram equalization tends to change the mean brightness of any image to the middle gray level of the dynamic range, which often results in over or under enhancement and introduce some annoying artifacts. To overcome such problems, several bi-histogram based techniques and tri-histogram based technique has been proposed. While bi-histogram based techniques divides the histogram of any image into two subhistograms and equalize them independently, tri-histogram based technique divides the histogram into three sub histograms. This paper compares some of these equalization techniques. Simulation results can be quantitative and qualitative in nature. For quantitative analysis, Absolute Mean Brightness Error (AMBE) measurement has been used. And qualitative results can be observed from the image itself. General Terms Digital Image Processing, Computer Vision
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