用 OpenCV 实现 Guided Filter

标签：c++   源码   opencv   filter   matlab   

最近发现 OpenCV 的 C++ 接口写得和 Matlab 实在是太相似了。我用 OpenCV 2.49 来实现 Guided Filter 的时候几乎是直接照抄作者公开的 Matlab 代码。废话不多直接贴我的代码：

cv::Mat guidedFilter(cv::Mat I, cv::Mat p, int r, double eps)
{
	/*
	% GUIDEDFILTER   O(1) time implementation of guided filter.
	%
	%   - guidance image: I (should be a gray-scale/single channel image)
	%   - filtering input image: p (should be a gray-scale/single channel image)
	%   - local window radius: r
	%   - regularization parameter: eps
	*/
 
	cv::Mat _I;
	I.convertTo(_I, CV_64FC1);
	I = _I;
 
	cv::Mat _p;
	p.convertTo(_p, CV_64FC1);
	p = _p;
 
	//[hei, wid] = size(I);
	int hei = I.rows;
	int wid = I.cols;
 
	//N = boxfilter(ones(hei, wid), r); % the size of each local patch; N=(2r+1)^2 except for boundary pixels.
	cv::Mat N;
	cv::boxFilter(cv::Mat::ones(hei, wid, I.type()), N, CV_64FC1, cv::Size(r, r));
 
	//mean_I = boxfilter(I, r) ./ N;
	cv::Mat mean_I;
	cv::boxFilter(I, mean_I, CV_64FC1, cv::Size(r, r));
	
	//mean_p = boxfilter(p, r) ./ N;
	cv::Mat mean_p;
	cv::boxFilter(p, mean_p, CV_64FC1, cv::Size(r, r));
 
	//mean_Ip = boxfilter(I.*p, r) ./ N;
	cv::Mat mean_Ip;
	cv::boxFilter(I.mul(p), mean_Ip, CV_64FC1, cv::Size(r, r));
 
	//cov_Ip = mean_Ip - mean_I .* mean_p; % this is the covariance of (I, p) in each local patch.
	cv::Mat cov_Ip = mean_Ip - mean_I.mul(mean_p);
 
	//mean_II = boxfilter(I.*I, r) ./ N;
	cv::Mat mean_II;
	cv::boxFilter(I.mul(I), mean_II, CV_64FC1, cv::Size(r, r));
 
	//var_I = mean_II - mean_I .* mean_I;
	cv::Mat var_I = mean_II - mean_I.mul(mean_I);
 
	//a = cov_Ip ./ (var_I + eps); % Eqn. (5) in the paper;	
	cv::Mat a = cov_Ip/(var_I + eps);
 
	//b = mean_p - a .* mean_I; % Eqn. (6) in the paper;
	cv::Mat b = mean_p - a.mul(mean_I);
 
	//mean_a = boxfilter(a, r) ./ N;
	cv::Mat mean_a;
	cv::boxFilter(a, mean_a, CV_64FC1, cv::Size(r, r));
	mean_a = mean_a/N;
 
	//mean_b = boxfilter(b, r) ./ N;
	cv::Mat mean_b;
	cv::boxFilter(b, mean_b, CV_64FC1, cv::Size(r, r));
	mean_b = mean_b/N;
 
	//q = mean_a .* I + mean_b; % Eqn. (8) in the paper;
	cv::Mat q = mean_a.mul(I) + mean_b;
 
	return q;
}

用 OpenCV 实现 Guided Filter,布布扣,bubuko.com

用 OpenCV 实现 Guided Filter

标签：c++   源码   opencv   filter   matlab   

原文地址：http://blog.csdn.net/holybang/article/details/28093305