Adaptive Strata Selection in Parametric Histogram Equalization for Detail-Preserving Enhancement

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Authors: Dr. V. Sesha Srinivas, J. Nikhil Raj, A. Tejagna Chandra Karthikeya, CH. K. Bhanu Pradeep, A. Blessy Bhavini Beenal
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Abstract

A new adaptive contrast enhancement method based on Adaptive Strata Selection in Parametric Histogram Equalization (ASPHE) is proposed to adaptively select the stratification parameters according to the image content for robust contrast enhancement. Unlike the conventional SPOHE method based on the fixed stratification parameters determined empirically, the proposed ASPHE method uses the local complexity score based on the variance, entropy, and gradient information of each image region to adaptively select the number of strata. To efficiently compute the local complexity score of each image region, the integral image is employed. An adaptive mapping function is designed to guarantee the image regions with higher complexity are stratified finely while those with smoother image content are stratified coarsely. The proposed adaptive strategy has been demonstrated to enhance image contrast while avoiding the occurrence of artifacts like halos, blocking effects, and over-enhancement. The experimental results have demonstrated the ability of ASPHE to achieve an accurate approximation of the cdf while offering better adaptability to various images with efficient computation compared to the SPOHE method.

Fields of Study & Subjects

Image Enhancement Techniques Advanced Image Processing Techniques Image and Signal Denoising Methods

Publication details

Journal / source
Iconic Research and Engineering Journals
Volume
9
Issue
9
Publication date
10 March 2026
Language
EN