how to enhance color image using fuzzy logic

to convert the given RGB image of size P × Q into HSV and then calculate the histogram h(x) where x Є V. h(x) indicates the number of pixels in the image with intensity value x. Proposed method uses two intensification parameters M and K, which controls the degree at which the intensity value x has to be intensified. The control parameter M, M= sum(Xh(x))/sum(h(x)) & k=128

The parameter M divides the histogram h(x) into two classes C1([0,M-1])& C2([M,255]). The stretching of V component is performed based on two fuzzy membership values D1 and D2,Parameter M has a significant role in the computation of fuzzy membership values,

D1=1-(M-X)/M

the contrast enhanced or intensified value xe for class C1

xe=X + D1(X)K

D2=E-X/E-M

the contrast enhanced or intensified value xe for class C2

Xe = (XD2(X))+(E −D2(X)K))

The replacement of the old x values of the V component with the enhanced xe values will cause the V component to be stretched resulting in contrast and brightness enhanced component Ve. This enhanced achromatic information Ve can be combined with the preserved chromatic information (Hue and Saturation components) to obtain enhanced image HSVe which is finally converted to enhanced RGBe image.

[Image Analyst]

Do you have a question?

[bindhu a]

how can you an image as an input in fuzzy?

[Walter Roberson]

If the fis needs to examine the entire array to work out the histogram and the appropriate parameters, then use a fis with as many variables as (image length) times (image width) times (number of color planes).

[Subhadeep Koley]

I have a 512*512 grayscale image to be given as the input of a FIS. What should be the no. of variables in the FIS.