图像质量评价指标uiqm
时间: 2023-07-29 21:03:46 浏览: 259
图像质量评价指标UIQM(Underwater Image Quality Measure)是用于评估水下图像质量的一种指标。它是基于感知的图像质量评价模型,旨在提供更准确、更符合人眼感知的图像质量评价结果。
UIQM综合考虑了图像亮度、对比度和饱和度等因素。其中,图像亮度指标评估图像是否具有明确的亮度信息,对图像的视觉感知影响较大。对比度指标评估图像中不同区域的灰度差异,对图像的视觉感知和细节呈现能力有影响。饱和度指标评估图像的颜色饱和度,衡量图像中颜色的鲜艳程度。
UIQM通过计算这些指标的加权系数,综合评价图像的质量。通过与主观评价的实验证明,UIQM能够有效地模拟人眼对水下图像质量的感知,具有较高的准确性和稳定性。
UIQM的应用广泛,可用于水下图像采集、处理和传输等方面。对于水下摄像机和图像处理算法的研发,UIQM可以作为一个客观的评价指标,帮助改进水下图像质量和细节的捕捉。同时,在水下影像的传输和压缩中,UIQM也可以用于评估不同压缩算法对图像质量的影响,提供有效的参考依据。
总而言之,UIQM是一种用于评估水下图像质量的指标,具有较高的准确性和稳定性。它综合考虑了图像的亮度、对比度和饱和度等因素,能够模拟人眼对水下图像质量的感知,对水下影像的研究和应用具有重要意义。
相关问题
Matlab简单计算水下图像质量指标UIQM的代码
UIQM(Underwater Image Quality Measure)是一种用于评估水下图像质量的指标,可以用MATLAB进行计算。下面是一个简单的MATLAB代码示例:
```
% 读取水下图像
I = imread('underwater_image.jpg');
% 计算UIQM
uiqm = compute_uiqm(I);
% 显示结果
disp(['UIQM值为:', num2str(uiqm)]);
function u = compute_uiqm(I)
% 计算UIQM
% I: 输入的水下图像
% 从图像中提取颜色分量
R = double(I(:,:,1));
G = double(I(:,:,2));
B = double(I(:,:,3));
% 计算图像的均值和标准差
meanR = mean(R(:));
stdR = std(R(:));
meanG = mean(G(:));
stdG = std(G(:));
meanB = mean(B(:));
stdB = std(B(:));
% 计算对比度
C1 = sqrt(stdR^2 + stdG^2 + stdB^2);
C2 = sqrt(meanR^2 + meanG^2 + meanB^2);
% 计算饱和度
S = std(R(:))/(mean(R(:)) + eps) + std(G(:))/(mean(G(:)) + eps) + std(B(:))/(mean(B(:)) + eps);
% 计算清晰度
G = fspecial('gaussian', [7 7], 1.5);
Rg = imfilter(R, G, 'symmetric');
Gg = imfilter(G, G, 'symmetric');
Rgg = imfilter(Rg, G, 'symmetric');
Rx = R - Rgg;
Rxx = imfilter(Rx.^2, G, 'symmetric');
Q = sqrt(Rxx./Gg);
% 计算UIQM值
u = C1*C2*S*mean(Q(:));
end
```
上述代码中,我们首先读入水下图像,然后通过 `compute_uiqm` 函数计算UIQM值。其中,我们首先从图像中提取RGB颜色分量,然后计算每个通道的均值和标准差,接着计算对比度、饱和度和清晰度,并最终将它们相乘得到UIQM值。
Matlab计算水下彩色图像质量指标UIQM的代码
以下是计算水下彩色图像质量指标UIQM的Matlab代码:
```matlab
function [uiqm] = UIQM(img)
% RGB to YCbCr conversion
if size(img,3)==3
img = rgb2ycbcr(img);
end
% Parameters initialization
mu = [0.01 0.03];
mask = fspecial('gaussian', 7, 7/6);
mask = mask / sum(mask(:));
K = 0.01;
% Mean and variance calculation
Y = img(:,:,1)/255;
Cb = img(:,:,2)/255;
Cr = img(:,:,3)/255;
muY = filter2(mask, Y, 'same');
muCb = filter2(mask, Cb, 'same');
muCr = filter2(mask, Cr, 'same');
Y = Y - muY;
Cb = Cb - muCb;
Cr = Cr - muCr;
sigmaY = sqrt(abs(filter2(mask, Y.^2, 'same')));
sigmaCb = sqrt(abs(filter2(mask, Cb.^2, 'same')));
sigmaCr = sqrt(abs(filter2(mask, Cr.^2, 'same')));
% Colorfulness calculation
RG = img(:,:,1) - img(:,:,2);
YB = (img(:,:,1) + img(:,:,2))/2 - img(:,:,3);
stdRG = sqrt(abs(filter2(mask, RG.^2, 'same')));
stdYB = sqrt(abs(filter2(mask, YB.^2, 'same')));
meanRG = filter2(mask, RG, 'same');
meanYB = filter2(mask, YB, 'same');
colorfulness = sqrt(stdRG.^2 + stdYB.^2 + (K*meanRG).^2 + (K*meanYB).^2);
% Contrast calculation
contrast = (sigmaY + sigmaCb + sigmaCr) / 3;
% Structure calculation
L = YCbCr2Luminance(img);
muL = filter2(mask, L, 'same');
L = L - muL;
sigmaL = sqrt(abs(filter2(mask, L.^2, 'same')));
structure = sigmaL;
% Sharpness calculation
S = sharpness(img);
sharpness = filter2(mask, S, 'same');
% Overall quality calculation
uiqm = (mu(1)*colorfulness) - (mu(2)*contrast) + ((1-mu(1)-mu(2))*structure.*sharpness);
end
function [L] = YCbCr2Luminance(img)
% YCbCr to Luminance conversion
Y = img(:,:,1);
Cb = img(:,:,2);
Cr = img(:,:,3);
L = 0.299*Y + 0.587*Cb + 0.114*Cr;
end
function [S] = sharpness(img)
% Sobel operator for edge detection
SobelX = [-1 0 1; -2 0 2; -1 0 1];
SobelY = SobelX';
% Image gradients calculation
grayImg = rgb2gray(img);
Ix = imfilter(double(grayImg), SobelX, 'replicate');
Iy = imfilter(double(grayImg), SobelY, 'replicate');
G = sqrt(Ix.^2 + Iy.^2);
% Sharpness calculation
S = mean2(G);
end
```
其中,`img`为输入的水下彩色图像,`uiqm`为计算得到的UIQM指标。注意,该代码需要调用Matlab Image Processing Toolbox中的函数,如`rgb2ycbcr`和`imfilter`,请确保已经安装并加载该工具箱。