How do I calculate PNSR of an Image

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Chidiebere Ike el 7 de Nov. de 2018
Comentada: DGM el 16 de En. de 2024
Hello,
I have an image named "Foreman". I wish to estimate it's PSNR initial value in dB.
How do I achieve this ?
Thank you
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Rik el 15 de En. de 2024
Did you Google how to read an image? And how to calculate the PSNR?

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Respuestas (2)

Shreeya el 16 de En. de 2024
For an m*n image "I" and it's noisy approximation "J" of 8-bit unsigned integer data type, the PSNR can be calculated using the following code implementation:
R = 255;
mse = mean((I-J).^2, "all");
if (mse ~= 0)
psnr = 20*log10(R/sqrt(mse));
end
Apart from the editor, these computations can also be performed in Simulink through the PSNR block. You can refer to the link below to understand more about it:
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DGM el 16 de En. de 2024
Even for uint8, this will be wrong unless both inputs were already mis-cast into a wider numeric class; otherwise truncation occurs in taking the MSE.
To avoid the whole problem, don't presume the input class. Expect only that it is properly-scaled for whatever class it has. Cast both images to floating point to take the MSE. Calculate the peak value based on whatever the class of the incoming images is.
% some test images
I = int16(I); % it's not uint8 anymore
J = imnoise(I,'gaussian',0.1);
% test it
R = diff(getrangefromclass(I));
mse = mean((double(I)-double(J)).^2, "all");
if (mse ~= 0)
P1 = 20*log10(R/sqrt(mse))
end
P1 = 16.9947
% compare
P2 = psnr(J,I)
P2 = 16.9947
This makes the same assumptions that IPT psnr() makes. I and J must both have the same class and must be properly-scaled for their class. The supported classes are only those handled by IPT getrangefromclass(), so it's still not totally class-agnostic, but neither is psnr().

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Image Analyst el 16 de En. de 2024
There is a psnr function in the Image Processing Toolbox.
help psnr
PSNR Peak Signal-To-Noise Ratio. PEAKSNR = PSNR(A, REF) calculates the peak signal-to-noise ratio for the image in array A, with the image in array REF as the reference. A and REF can be N-D arrays, and must be of the same size and class. PEAKSNR = PSNR(A, REF, PEAKVAL) uses PEAKVAL as the peak signal value for calculating the peak signal-to-noise ratio. [PEAKSNR, SNR] = PSNR(A, REF, __) also returns the simple signal-to-noise in SNR, in addition to the peak signal-to-noise ratio. [___] = PSNR(___,Name,Value) accepts name value pairs to control aspects of computation. Supported options include: 'DataFormat' Dimension labels of the input data A and REF specified as a string scalar or character vector. The format options 'S','C', and 'B' are supported. The options 'S', 'C' and 'B' correspond to spatial, channel, and batch dimensions, respectively. For data with a batch or 'B' dimension, the output PEAKSNR and SNR will contain a separate result for each index along the batch dimension. As an example, input RGB data with two spatial dimensions and one channel dimension would have a 'SSC' DataFormat. Default: All input dimensions in A treated as spatial dimensions. Notes ----- 1. When dlarray input is labeled and contains a batch dimension, psnr yields a separate result for each element along the batch dimension. Class Support ------------- Input arrays A and REF must be one of the following classes: uint8, int16, uint16, single, or double. Both A and REF must be of the same class. They must be nonsparse. PEAKVAL is a scalar of any numeric class. PEAKSNR and SNR are scalars of class double, unless A and REF are of class single in which case PEAKSNR and SNR are scalars of class single. Example --------- % This example shows how to compute PSNR for noisy image given the % original reference image. ref = imread('pout.tif'); A = imnoise(ref,'salt & pepper', 0.02); [peaksnr, snr] = psnr(A, ref); fprintf('\n The Peak-SNR value is %0.4f', peaksnr); fprintf('\n The SNR value is %0.4f \n', snr); See also IMMSE, MEAN, MEDIAN, SSIM, SUM, VAR. Documentation for psnr doc psnr Other uses of psnr dlarray/psnr
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