Compare Image Quality Using PSNR

This example shows how to compare the quality of a noisy and denoised image from the PSNR value computed using the PSNR block.

Read an image into the MATLAB® workspace.

I = imread('cameraman.tif');

Read the corresponding noisy image into the MATLAB workspace.

noisyI =  imread('noisyCameraman.tif');

Example Model

Open the Simulink® model. The model reads the original and the noisy images from the MATLAB workspace and denoises the noisy image by using the Median Filter block.

modelname='ex_blkpsnr.slx';
open_system(modelname);

The model computes the PSNR value for the noisy and the denoised image with respect to the original image and outputs as variables named psnr_noisy and psnr_denoised respectively. The denoised image and the computed PSNR values are exported to the MATLAB workspace.

Simulate and Display Results

Simulate the model.

out = sim(modelname);

Display the noisy image and the corresponding PSNR value

imshow(noisyI,[]);
title(['PSNR = ', num2str(out.psnr_noisy)]);

Display the denoised image and the corresponding PSNR value. The denoised image is of better perceptual quality than the noisy image and hence, has comparatively high PSNR value.

imshow(out.denoisedImage,[]);
title(['PSNR = ', num2str(out.psnr_denoised)]);