【图像处理】Schmid滤波器

迈不过友情╰ 2022-08-27 03:56 229阅读 0赞

Schmid也是一种类Gabor图像滤波器，在[这篇文章][Link 1]\[1\]中有具体推导和介绍。

一种更简洁的表达公式是：

![20140506151235406][]

其中，r为核半径，Z为归一化参数，τ和σ是比较重要的参数，在ReID提取TextFeature中，经常使用如下一系列参数：

(2,1), (4,1), (4,2), (6,1), (6,2), (6,3), (8,1), (8,2), (8,3), (10,1), (10,2), (10,3), (10,4)

此外，还结合前面的[Gabor滤波器][Gabor]，γ,θ,λ,σ的参数分别使用：(0.3,0,4,2), (0.3,0,8,2), (0.4,0,4,1), (0.4,0,4,1), (0.3,π/2,4,2), (0.3,π/2,8,2), (0.4,π/2 ,4,1), (0.4,π/2,4,1)

以下是11个滤波核的示意图：

![20140506151758109][]

生成Schmid核函数代码：

Mat getSchmidFilter(float tao, float sigma){
    	float r = sigma/(4.0f*tao);
    	float sigma2 = sigma*sigma;
    	//int half_filter_size = int(r+0.5);
    	int half_filter_size = 10;
    	int filter_size = 2*half_filter_size+1;
    	Mat schmid = Mat::zeros(filter_size,filter_size,CV_32F);
    	float filter_sum = 0.0f;
    	for(int i=0;i<filter_size;i++){
    		float* s = schmid.ptr<float>(i);
    		for(int j=0;j<filter_size;j++){
    			float x = i-half_filter_size;
    			float y = j-half_filter_size;
    			r = sqrt(x*x+y*y);
    			float tmp = 2*PI*tao*r/sigma;
    			float tmp2 = r*r/(2.0f*sigma2);
    			s[j] = cos(tmp)*exp(-tmp2);
    			filter_sum += s[j];
    		}
    	}
    	//cout<<filter_size<<" "<<filter_sum<<endl;
    	//cout<<schmid<<endl;
    	if(abs(filter_sum-0.0f)<1e-6){
    		return schmid;
    	}
    	for(int i=0;i<filter_size;i++){
    		float* s = schmid.ptr<float>(i);
    		for(int j=0;j<filter_size;j++){
    			s[j]/=filter_sum;
    		}
    	}
    	return schmid;
    }

对图像进行卷积滤波效果如图：

![20140506161455015][]

参考文献：

\[1\] Schmid, Cordelia. "Constructing models for content-based image retrieval."Computer Vision and Pattern Recognition, 2001. CVPR 2001. Proceedings of the 2001 IEEE Computer Society Conference on. Vol. 2. IEEE, 2001.

\[2\] Gray, Douglas, and Hai Tao. "Viewpoint invariant pedestrian recognition with an ensemble of localized features." Computer Vision–ECCV 2008. Springer Berlin Heidelberg, 2008. 262-275.

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[Link 1]: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=990922
[20140506151235406]: /images/20220824/389caf0ef99c46fab51dc848924f998a.png
[Gabor]: http://blog.csdn.net/xiaowei_cqu/article/details/24745945
[20140506151758109]: /images/20220824/cfe5483700e2488c92728d9a40bd271f.png
[20140506161455015]: /images/20220824/e55ca7aef57f4aaba4b5a0b04eef15bb.png
[http_blog.csdn.net_xiaowei_cqu]: http://blog.csdn.net/xiaowei_cqu