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    <p>In OpenCV2.x, there's a new interface called <code>Mat::inv(int method)</code> to compute the inverse of a matrix. See <a href="http://opencv.itseez.com/modules/core/doc/basic_structures.html">reference</a>.</p> <blockquote> <p>C++: MatExpr Mat::inv(int method=DECOMP_LU) const</p> <p>Parameters: method –</p> <pre><code> Matrix inversion method. Possible values are the following: DECOMP_LU is the LU decomposition. The matrix must be non-singular. DECOMP_CHOLESKY is the Cholesky LL^T decomposition for symmetrical positively defined matrices only. This type is about twice faster than LU on big matrices. DECOMP_SVD is the SVD decomposition. If the matrix is singular or even non-square, the pseudo inversion is computed. </code></pre> </blockquote> <p>I made a test with each of the method, it shows that DECOMP_CHOLESKY is the fastest for the test case, and LU gives the similar result.</p> <pre><code>#include &lt;opencv2/core/core.hpp&gt; #include &lt;opencv2/highgui/highgui.hpp&gt; #include &lt;opencv2/imgproc/imgproc.hpp&gt; #include &lt;iostream&gt; int main(void) { cv::Mat img1 = cv::imread("2.png"); cv::Mat img2, img3, img; cv::cvtColor(img1, img2, CV_BGR2GRAY); img2.convertTo(img3, CV_32FC1); cv::resize(img3, img, cv::Size(200,200)); double freq = cv::getTickFrequency(); double t1 = 0.0, t2 = 0.0; t1 = (double)cv::getTickCount(); cv::Mat m4 = img.inv(cv::DECOMP_LU); t2 = (cv::getTickCount()-t1)/freq; std::cout &lt;&lt; "LU:" &lt;&lt; t2 &lt;&lt; std::endl; t1 = (double)cv::getTickCount(); cv::Mat m5 = img.inv(cv::DECOMP_SVD); t2 = (cv::getTickCount()-t1)/freq; std::cout &lt;&lt; "DECOMP_SVD:" &lt;&lt; t2 &lt;&lt; std::endl; t1 = (double)cv::getTickCount(); cv::Mat m6 = img.inv(cv::DECOMP_CHOLESKY); t2 = (cv::getTickCount()-t1)/freq; std::cout &lt;&lt; "DECOMP_CHOLESKY:" &lt;&lt; t2 &lt;&lt; std::endl; cv::waitKey(0); } </code></pre> <p>Here is the running resutls:</p> <blockquote> <p>LU:0.000423759</p> <p>DECOMP_SVD:0.0583525</p> <p>DECOMP_CHOLESKY:9.3453e-05</p> </blockquote>
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