Contrast enhancement is an important factor in the image preprocessing step. One of the widely accepted contrast enhancement method is the histogram equalization. Although histogram equalization achieves comparatively better performance on almost all types of image, global histogram equalization sometimes produces excessive visual deterioration. A new extension of bi-histogram equalization call...

Base class for Contrast Limited Adaptive Histogram Equalization. Equalizes the histogram of a grayscale image using Contrast Limited Adaptive Histogram. Hello all. I would like to implement an extension of the well-known CLAHE histogram equalization method in Matlab. Currently, Matlab provides routines. Adaptive Histogram Equalization. Contrast Limited Adaptive Histogram Equalization. Histogram...

We present PRISMA’s Video Copy Detection system (P-VCD). The system is based on visual-only global descriptors, weighted combinations of distances, a pivotbased index structure, and a novel approximated search and voting algorithm for copy localization. We submitted four Runs to TRECVID 2010 CCD task: PRISMA.m.balanced.ehdNgryhst: a combination of edge histogram and gray histogram. PRISMA.m.bal...

Histogram equalization is a nonlinear technique for adjusting the contrast of an image using its histogram. It increases the brightness of a gray scale image which is different from the mean brightness of the original image. There are various types of Histogram equalization techniques like Histogram Equalization, Contrast Limited Adaptive Histogram Equalization, Brightness Preserving Bi Histogr...

Histogram warping is a novel histogram specification technique for use in color image processing. As a general purpose tool for color correction, our technique constructs a global color mapping function in order to transform the colors of a source image to match a target color distribution to any desired degree of accuracy. To reduce the risk of color distortion, the transformation takes place ...

To address the technical shortcomings of conventional histogram equalization (HE), such as over-enhancement and artifacts, we propose a histogram-constrained contrast-tunable HE technique for digital image enhancement. Firstly, input is partitioned into two parts, main constrained histogram, by cumulative probability density threshold; second, redistributed equally in whole grayscale range; fin...