Creating a Noisy Image and Removing Noise Using randg Gamma Law in Matlab?

Question

I want to add Multiplicative Gamma Noise to a image using "randg" function in Matlab and remove that noise. We have to keep in mind that the noise should have mean 1 and level 4. It should follow Gamma law ( with Gamma Probability Distribution Function). The image after addition of noise becomes

f=u*v; where f=noisy image, u=original image, v=noisy image.

The gamma law is: gv(v)=L^L/(Γ(L)) v^(L-1) exp(-Lv) 1_(v≥0)

where L is the noise level and v is the noise.

Here is the code that I've tried:

  img = imread('lena.png');
  img1 = img./ 255;
  imgdob = double(img1);
  noisyimg = imgdob + randg(1,size(imgdob)) .* 0.4;
  noisyimg(noisyimg< 0) = 0;
  noisyimg(noisyimg> 1) = 1;
  figure,imshow(img);
  figure,imshow(noisyimg);
  imwrite(img, 'lenaOriginal.jpg', 'Quality', 100);
  imwrite(noisyimg, 'lenaNoisy.jpg', 'Quality', 100);

But I could not get the expected result. Please suggest me a way.

Answer 1

0.4 is VERY destructive. So destructive that it'll force it to threshold values to 0 or 1. You should try 0.2 instead. Also if you're looking for a normal distribution noise, you should use randn instead of randg. The following code is here.

Note that I don't have sexylena.png on my computer so I must use bag.png instead.

imgdob = im2double(imread('bag.png'));
noisyimg = imgdob + randg(1,size(imgdob)) .* 0.15;
noisyimg(noisyimg< 0) = 0;
noisyimg(noisyimg> 1) = 1;
figure,imshow(imgdob);
figure,imshow(noisyimg);
imwrite(imgdob, 'lenaOriginal.jpg', 'Quality', 100);
imwrite(noisyimg, 'lenaNoisy.jpg', 'Quality', 100);

These are the results. Normal image.

Noisy image using randg.

If you wish to use randn instead, you can use this line of code instead.

noisyimg = imgdob + randn(size(imgdob)) .* 0.2;

Noisy image using randn.

As for noise reduction, please refer to Matlab's tutorial for noise removal.