Digital Image Processing
Recursive sub-image histogram equalization applied to gray scale images
Pattern Recognition Letters
Contrast enhancement for image by WNN and GA combining PSNR with information entropy
Fuzzy Optimization and Decision Making
Parametric indices of fuzziness for automated image enhancement
Fuzzy Sets and Systems
An image contrast enhancement method based on genetic algorithm
Pattern Recognition Letters
Contrast enhancement using brightness preserving bi-histogram equalization
IEEE Transactions on Consumer Electronics
Image enhancement based on equal area dualistic sub-image histogram equalization method
IEEE Transactions on Consumer Electronics
IEEE Transactions on Consumer Electronics
Minimum mean brightness error bi-histogram equalization in contrast enhancement
IEEE Transactions on Consumer Electronics
Brightness preserving histogram equalization with maximum entropy: a variational perspective
IEEE Transactions on Consumer Electronics
Fast Image/Video Contrast Enhancement Based on Weighted Thresholded Histogram Equalization
IEEE Transactions on Consumer Electronics
Brightness preserving weight clustering histogram equalization
IEEE Transactions on Consumer Electronics
IEEE Transactions on Consumer Electronics
Image sharpening using sub-regions histogram equalization
IEEE Transactions on Consumer Electronics
An Optimal Fuzzy System for Color Image Enhancement
IEEE Transactions on Image Processing
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A novel technique, Optimized Bi-Histogram Equalization (OBHE), is proposed in this paper for preserving brightness and enhancing the contrast of any input image. The central idea of this technique is to first segment the histogram of the input image into two, based on its mean and then weighting constraints are applied to each of the sub-histograms separately. Those two histograms are equalized independently and their union produces a brightness-preserved and contrast-enhanced output image. While formulating the weighting constraints, Particle Swarm Optimization (PSO) is employed to find the optimal constraints in order to maximize the degree of brightness preservation and contrast enhancement. This technique is found to have an edge over the other contemporary methods in terms of Entropy and Absolute Mean Brightness Error.