Image Enhancement with Histogram Local Minimas

摘要

In this paper work, the author introduces local minima based image enhancement. Enhancing of images is a primary step in any advanced image processing analysis. Initially, the histogram of an unprocessed image is computed to analyze the gray level distribution of an image. Later the local minima's of histogram image is calculated. Based on these minima's the image is partitioned in to intensity based distributed images. Finally these images undergo mapping process with mean and equalization computational values. The effectiveness of proposed work is verified with PSNR (peak signal to noise ratio), entropy, AMBE (Absolute mean brightness error) & visual quality in both quantitatively, qualitatively.