Question

Contrast enhancement using real coded genetic algorithm based modified histogram equalization for gray scale images

Answer 1

Answer:

The distance between two categorical attribute values can be measured by the following way:

distance(sydney, melbourne)=1-similarity(sydney,melbourne). I have also used this one in my clustering technique.

Answer 2

Explanation:

Histogram equalization is a well-known technique used for contrast enhancement. The global HE usually results in excessive contrast enhancement because of lack of control on the level of contrast enhancement. A new technique named modified histogram equalization using real coded genetic algorithm (MHERCGA) is aimed to sweep over this drawback. The primary aim of this paper is to obtain an enhanced method which keeps the original brightness. This method incorporates a provision to have a control over the level of contrast enhancement and applicable for all types of image including low contrast MRI brain images. The basic idea of this technique is to partition the input image histogram into two subhistograms based on a threshold which is obtained using Otsu's optimality principle.