Image Quality measures / Performance metrics between Images [MATLAB code]

This coding will calculate the performance metrics or image quality measures between two images. This code will be very helpful in fields like Digital Image processing, Image Steganography.  Copy the codes in matlab and execute main.m.

CONTENTS

Main.m

MaximumDifference.m

MeanSquareError.m

NormalizedAbsoluteError.m

NormalizedCrossCorrelation.m

PeakSignaltoNoiseRatio.m

StructuralContent.m

AverageDifference.m

%Program for Image / Picture Quality Measures Calculation

%Program Description

%This program is the main entry of the application.

%This program calculates the difference Image/Picture Quality Measures

%Clear Memory & Command Window

clc;

clear all;

close all;

%Read Original & Distorted Images

origImg = imread('dc_shift_10.bmp');

distImg = imread('gaussian_noise_50.bmp');

%If the input image is rgb, convert it to gray image

noOfDim = ndims(origImg);

if(noOfDim == 3)

    origImg = rgb2gray(origImg);

end

noOfDim = ndims(distImg);

if(noOfDim == 3)

    distImg = rgb2gray(distImg);

end

%Size Validation

origSiz = size(origImg);

distSiz = size(distImg);

sizErr = isequal(origSiz, distSiz);

if(sizErr == 0)

    disp('Error: Original Image & Distorted Image should be of same dimensions');

    return;

end

%Mean Square Error

MSE = MeanSquareError(origImg, distImg);

disp('Mean Square Error = ');

disp(MSE);

%Peak Signal to Noise Ratio

PSNR = PeakSignaltoNoiseRatio(origImg, distImg);

disp('Peak Signal to Noise Ratio = ');

disp(PSNR);

%Normalized Cross-Correlation

NK = NormalizedCrossCorrelation(origImg, distImg);

disp('MNormalized Cross-Correlation  = ');

disp(NK);

%Average Difference

AD = AverageDifference(origImg, distImg);

disp('Average Difference  = ');

disp(AD);

%Structural Content

SC = StructuralContent(origImg, distImg);

disp('Structural Content  = ');

disp(SC);

%Maximum Difference

MD = MaximumDifference(origImg, distImg);

disp('Maximum Difference = ');

disp(MD);

%Normalized Absolute Error

NAE = NormalizedAbsoluteError(origImg, distImg);

disp('Normalized Absolute Error = ');

disp(NAE);

%Program for Peak Signal to Noise Ratio Calculation

function PSNR = PeakSignaltoNoiseRatio(origImg, distImg)

origImg = double(origImg);

distImg = double(distImg);

[M N] = size(origImg);

error = origImg - distImg;

MSE = sum(sum(error .* error)) / (M * N);

if(MSE > 0)

    PSNR = 10*log(255*255/MSE) / log(10);

else

    PSNR = 99;

end

%Program for Average Difference Calculation

function AD = AverageDifference(origImg, distImg)

origImg = double(origImg);

distImg = double(distImg);

[M N] = size(origImg);

error = origImg - distImg;

AD = sum(sum(error)) / (M * N);

%Program for Maximum Difference Calculation

function MD = MaximumDifference(origImg, distImg)

origImg = double(origImg);

distImg = double(distImg);

error = origImg - distImg;

MD = max(max(error));

%Program for Mean Square Error Calculation

function MSE = MeanSquareError(origImg, distImg)

origImg = double(origImg);

distImg = double(distImg);

[M N] = size(origImg);

error = origImg - distImg;

MSE = sum(sum(error .* error)) / (M * N);

%Program for Normalized Absolute Error Calculation

function NAE = NormalizedAbsoluteError(origImg, distImg)

origImg = double(origImg);

distImg = double(distImg);

error = origImg - distImg;

NAE = sum(sum(abs(error))) / sum(sum(origImg));

%Program for Normalized Cross Correlation Calculation

function NK = NormalizedCrossCorrelation(origImg, distImg)

origImg = double(origImg);

distImg = double(distImg);

NK = sum(sum(origImg .* distImg)) / sum(sum(origImg .* origImg));

%Program for Structural Content Calculation

function SC = StructuralContent(origImg, distImg)

origImg = double(origImg);

distImg = double(distImg);

SC = sum(sum(origImg .* origImg)) / sum(sum(distImg .* distImg));