AWGN for a grayscale image

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Vivek Bhadouria
Vivek Bhadouria on 30 Aug 2011
Hello everyone,
I need to add AWGN to a grayscale image for the purpose of denoising. Till now I was using "imnoise" to add the gaussian noise but somewhere I doubt or I am confused whether I am adding correct noise or not.
Is this the correct method to add AWGN in an image? If not, please tell me how to add this kind of noise.
Thanking you in advance
Vivek Singh Bhadouria
India

Accepted Answer

Rick Rosson
Rick Rosson on 31 Aug 2011
Yes, imnoise is the right function to use.
Why are you concerned that it might not be the correct function to use?
Rick
  1 Comment
Vivek Bhadouria
Vivek Bhadouria on 22 Sep 2011
Dear Rick,
There is no problem in using imnoise function. Actually, I am interested in adding "Additive gaussian noise" and "multiplicative gaussian noise" to an image but I am not fully sure about the nature of the gaussian noise being added by imnoise function i.e. its behavior is additive or multiplicative.
Is there any way out to handle this?
Vivek Bhadouria

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More Answers (1)

Wayne King
Wayne King on 22 Sep 2011
Hi, The answer is both.
The Gaussian noise is additive if you use the 'Gaussian' option.
J = imnoise(I,'gaussian',M,V)
The Gaussian noise is multiplicative if you use 'speckle'
J = imnoise(I,'speckle',V)
Hope that helps, Wayne
  4 Comments
Wayne King
Wayne King on 27 Sep 2011
Sorry Vivek, you're right. I misread the help. The multiplicative option does use rand()
Image Analyst
Image Analyst on 27 Sep 2011
I'm not sure why they call it "speckle." At least it appears to have nothing to do with speckle in the laser imaging sense. My textbook on statistical optics says "Under the assumptions of the given statistical model, the speckle intensity follows a negative exponential law, and speckle phase follows a uniform law." The law (equation) it gives for laser speckle intensity distribution is p(i) = sigma^(-2) * exp(-i / sigma^2). This is definitely different than you'd get from MATLAB which says "adds multiplicative noise to the image I, using the equation J = I+n*I, where n is uniformly distributed random noise with mean 0 and variance v." So MATLAB's speckle noise is not laser speckle noise - it uses some other definition of speckle.

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