【图像算法】图像特征：三个图像显著性区域特征提取方法-优快云博客

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【图像算法】图像特征：三个图像显著性区域特征提取方法

SkySeraph Aug 11st 2011 HQU

Email：zgzhaobo@gmail.com QQ：452728574

Latest Modified Date：Aug 11st 2011 HQU

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图像算法系列： http://skyseraph.com/2011/08/27/CV/图像算法专题/

》第一种方法：

原理：Frequency-tuned Salient Region Detection.CVPR.2009

定义：

简述：

三步，滤波+颜色空间转换+计算SaliencyMap(见源码)

效果：

待测试图(后同)

结果1：(原作者代码测试结果)

结果2：（我用OpenCV改写的代码测试结果）

结果3：（我的改进测试(空间选择不同)）

源码(matlab)：

%---------------------------------------------------------
% Read image and blur it with a 3x3 or 5x5 Gaussian filter
%---------------------------------------------------------
img = imread('input_image.jpg');%Provide input image path
gfrgb = imfilter(img, fspecial('gaussian', 3, 3), 'symmetric', 'conv');
%---------------------------------------------------------
% Perform sRGB to CIE Lab color space conversion (using D65)
%---------------------------------------------------------
cform = makecform('srgb2lab', 'whitepoint', whitepoint('d65'));
lab = applycform(gfrgb,cform);
%---------------------------------------------------------
% Compute Lab average values (note that in the paper this
% average is found from the unblurred original image, but
% the results are quite similar)
%---------------------------------------------------------
l = double(lab(:,:,1)); lm = mean(mean(l));
a = double(lab(:,:,2)); am = mean(mean(a));
b = double(lab(:,:,3)); bm = mean(mean(b));
%---------------------------------------------------------
% Finally compute the saliency map and display it.
%---------------------------------------------------------
sm = (l-lm).^2 + (a-am).^2 + (b-bm).^2;
imshow(sm,[]);
%--------------------------------------------------------

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》第二种方法：

原理：

Y. Zhai and M. Shah. Visual attention detection in video sequences using spatiotemporal cues. In ACM Multimedia, pages 815–824. ACM,2006.

定义：

效果：

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》第三种方法：

原理：http://www.klab.caltech.edu/~xhou/projects/spectralResidual/spectralresidual.html

源码（matlab）：

clear
clc

%% Read image from file 
inImg = im2double(rgb2gray(imread('yourImage.jpg')));
inImg = imresize(inImg, 64/size(inImg, 2));

%% Spectral Residual
myFFT = fft2(inImg); 
myLogAmplitude = log(abs(myFFT));
myPhase = angle(myFFT);
mySpectralResidual = myLogAmplitude - imfilter(myLogAmplitude, fspecial('average', 3), 'replicate'); 
saliencyMap = abs(ifft2(exp(mySpectralResidual + i*myPhase))).^2; 

%% After Effect
saliencyMap = mat2gray(imfilter(saliencyMap, fspecial('gaussian', [10, 10], 2.5)));
imshow(saliencyMap);

效果：