【图像评价】基于matlab CCF算法的图像质量评价【含Matlab源码 075期】

一、源代码

``
clear all
clc

im = imread(‘1.bmp’);

quality = CCF(im)
function [quality] = CCF(im)

%-------------CCF_colorfulness -----------------
imColor = double(im);

R = imColor(:,:,1);
G = imColor(:,:,2);
B = imColor(:,:,3);

RR = log(R+0.00001) - mean2(log(R+0.00001));
GG = log(G+0.00001) - mean2(log(G+0.00001));
BB = log(B+0.00001) - mean2(log(B+0.00001));

alpha = RR-GG;
beta = 0.5*(RR+GG)-BB;

mu_alpha=mean(mean(alpha));
mu_beta=mean(mean(beta));
var_alpha=var(var(alpha));
var_beta=var(var(beta));

CCF_colorfulness=1000*((sqrt(var_alpha+var_beta)+0.3*sqrt(mu_alpha*mu_alpha+mu_beta*mu_beta))/85.59);    

%-------------CCF_contrast----------------------

im1=rgb2gray(im);
CCF_contrast = CCFcontrast(im1);

%-------------CCF_FADE--------------------------

CCF_FADE = FADE(im);

%------------ normalization ------------------

CCF_colorfulness=mapminmax(CCF_colorfulness,1,10);
CCF_contrast=mapminmax(CCF_contrast,1,10);
CCF_FADE=10-mapminmax(CCF_FADE,1,10);

% ------------calculate image quality with coefficients---------------------

c=[0.17593 0.61759 0.33988 ];
quality = c(1)*(CCF_colorfulness) + c(2)*(CCF_contrast) + c(3)*(CCF_FADE)   

end

## 二、备注

完整代码或者代写添加QQ2449341593
往期回顾>>>>>>
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