noise levels

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Gova ReDDy
Gova ReDDy 2011-6-21
how to add different noise levels to a image

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Sean de Wolski
Sean de Wolski 2011-6-21
A = 20; %amplitude of 10 - noise
noise = (rand(size(I))-.5)*A);
Inoisy = I+noise;
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Gova ReDDy
Gova ReDDy 2011-6-21
What 0.5 and A represents...And which of them represents how much noise added in uints
Walter Roberson
Walter Roberson 2011-6-21
There are an infinite number of different random noise distributions that can be used, and you need to decide whether the noise is additive or multiplicative, and you need to decide whether noise can ever reduce the value of a pixel, and you need to decide whether your noise "overwrites" pixels instead of adding or multiplying them.
In Sean's formula above, A is the peak-to-peak spread of the uniformly distributed noise generated.
Sean's formula is for noise which is uniformly randomly distributed between -A/2 and +A/2 (a total spread of A). Each uniformly distributed random number from rand() is in the range 0 to 1, so subtracting 0.5 from those values translates the range to -0.5 to +0.5; the multiplication by A scales that to -A/2 to +A/2 .
If it would make things clearer for you, Sean's code can be rewritten as
A = 10; %maximum noise amplitude
noise = (2 * rand(size(I)) - 1) * A;
Inoisy = I + noise;
That is, 0 to +1 gets magnified to 0 to +2, which gets translated to -1 to +1 and that gets multiplied by A to scale it to the desired magnitude.
The code would differ for normally distributed noise. (And caution: normally distributed noise can range from -infinity to +infinity in theory.)

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