– Histogram equalization – Preserving the original brightness to avoid annoying artifacts ‹ Bright preserving Bi-Histogram Equalization – Not handling well to avoid annoying artifacts ‹ Recursive Mean-Separate Histogram Equalization – Separating each new histogram further based on respective mean Abstract 3 / 28 ‹ Histogram equalization – Base on the probability distribution of the input gray l...

Anomaly detection is the task of detecting samples that behave differently from rest data or include abnormal values. Unsupervised anomaly most common scenario, which implies algorithms cannot train with a labeled input and do not know behavior beforehand. Histogram-based methods are one approaches in unsupervised detection, remarking good performance low runtime. Despite performance, histogram...

introduction: content based image retrieval (cbir) is a method of image searching and retrieval in a  database. in medical applications, cbir is a tool used by physicians to compare the previous and current  medical images associated with patients pathological conditions. as the volume of pictorial information  stored in medical image databases is in progress, efficient image indexing and retri...

Histogram Equalization is a contrast enhancement technique in the image processing which uses the histogram of image. However histogram equalization is not the best method for contrast enhancement because the mean brightness of the output image is significantly different from the input image. There are several extensions of histogram equalization has been proposed to overcome the brightness pre...

Histogram equalization is widely used in different ways to perform contrast enhancement in images. In this paper, a new Histogram modification algorithm is proposed for contrast enhancement of images. Histogram Equalization (HE) is one of the most popular technique used for digital image enhancement, but it is not suitable to be implemented directly in consumer electronics, such as television, ...

This Contrast enhancement is frequently referred to as one of the most important issues in image processing. Histogram equalization (HE) is one of the common methods used for improving contrast in digital images. Histogram equalization (HE) has proved to be a simple and effective image contrast enhancement technique. However, the conventional histogram equalization methods usually result in exc...