Brightness preserving weight clustering histogram equalization

Histogram equalization (GHE) is a simple and widely accepted method for contrast enhancement. Although there are extensions of GHE that can preserve the brightness of the original image better than the original method, these extensions sometimes fail to enhance the visualization of the original image. Therefore, we propose a new method called "Brightness Preserving Weight Clustering Histogram Equalization" (BPWCHE) that cat? simultaneously preserve the brightness of the original image and enhance visualization of the original image. BPWCHE assigns each non-zero bin of the original images histogram to a separate cluster, and computes each cluster's weight. Then, to reduce the number of clusters, we use three criteria (cluster weight, weight ratio and widths of two neighboring clusters) to merge pairs of neighboring clusters. The clusters acquire the same partitions as the result image histogram. Finally, transformation functions for each cluster's sub-histogram are calculated based on the traditional GHE method in the new acquired partitions of the result image histogram, and the sub-histogram's gray levels are mapped to the result image by the corresponding transformation functions. We showed experimentally that BPWCHE can preserve image brightness and enhance visualization of images more effectively than GHE and other brightness preserving methods(1).