To efficiently enhance images, a novel algorithm using multi scale image features extracted
by top-hat transform is proposed in this paper. Firstly, the multi scale bright and dim regions …

This book systematically synthesizes research achievements in the field of fuzzy neural
networks in recent years. It also provides a comprehensive presentation of the …

Computer-aided diagnosis (CAD) systems are the best alternative for immediate disclosure
and diagnosis of skin diseases. Such systems comprise several image processing …

This paper presents a new enhancement technique using the fuzzy set theory for low
contrast and nonuniform illumination images. A new parameter called the contrast factor …

In this paper, a novel adaptive network-based fuzzy inference system (ANFIS)-based filter,
ABF, is presented for the restoration of images corrupted by impulsive noise (IN). The ABF is …

This paper aims to implement an iterative fuzzy edge detection (IFED) method on blurred
satellite images. Some degradation effects such as atmospheric effects, clouds and their …

Image filtering is a key technology in image processing applications for de-noising corrupted
images. Digital images are often polluted by noise during capturing and hence they may not …

This study follows the direct approach to image contrast enhancement, which changes the
image contrast at each its pixel and is more effective than the indirect approach that deals …

The performance and accuracy of computer vision systems are affected by noise in different
forms. Although numerous solutions and algorithms have been presented for dealing with …

The representation and processing of edges in images based on notions from fuzzy set
theory has become popular in recent years. There are several reasons for this direction, from …