A Wavelet-Based Mammographic Image Denoising and Enhancement with Homomorphic Filtering
Journal of Medical Systems
Novel mean-shift based histogram equalization using textured regions
Expert Systems with Applications: An International Journal
Gaussian mixture modeling of histograms for contrast enhancement
Expert Systems with Applications: An International Journal
Image contrast enhancement for preserving mean brightness without losing image features
Engineering Applications of Artificial Intelligence
The Visual Computer: International Journal of Computer Graphics
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This paper proposes a new histogram equalization method, called RSWHE (recursively separated and weighted histogram equalization), for brightness preservation and image contrast enhancement. The essential idea of RSWHE is to segment an input histogram into two or more sub-histograms recursively, to modify the sub-histograms by means of a weighting process based on a normalized power law function, and to perform histogram equalization on the weighted sub-histograms independently. RSIHE (recursive sub-image histogram equalization) and RMSHE (recursive mean separate histogram equalization) are some methods similar to RSWHE, but they do not carry out the above weighting process. We show that compared to other existent methods, RSWHE preserves the image brightness more accurately and produces images with better contrast enhancement.