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Merge pull request #17120 from ganesh-k13:bugfix/documentation/16987

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Alexander Alekhin 2020-04-22 09:08:02 +00:00
commit 511d0fe198
1 changed files with 2 additions and 2 deletions
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modules/gapi/include/opencv2/gapi/imgproc.hpp
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@ -305,7 +305,7 @@ according to the specified border mode.
The function does actually compute correlation, not the convolution:
\f[\texttt{dst} (x,y) = \sum _{ \stackrel{0\leq x' < \texttt{kernel.cols},}{0\leq y' < \texttt{kernel.rows}} } \texttt{kernel} (x',y')* \texttt{src} (x+x'- \texttt{anchor.x} ,y+y'- \texttt{anchor.y} )\f]
\f[\texttt{dst} (x,y) = \sum _{ \substack{0\leq x' < \texttt{kernel.cols}\\{0\leq y' < \texttt{kernel.rows}}}} \texttt{kernel} (x',y')* \texttt{src} (x+x'- \texttt{anchor.x} ,y+y'- \texttt{anchor.y} )\f]
That is, the kernel is not mirrored around the anchor point. If you need a real convolution, flip
the kernel using flip and set the new anchor to `(kernel.cols - anchor.x - 1, kernel.rows -
@ -342,7 +342,7 @@ The function smooths an image using the kernel:
where
\f[\alpha = \fork{\frac{1}{\texttt{ksize.width*ksize.height}}}{when \texttt{normalize=true}}{1}{otherwise}\f]
\f[\alpha = \begin{cases} \frac{1}{\texttt{ksize.width*ksize.height}} & \texttt{when } \texttt{normalize=true} \\1 & \texttt{otherwise} \end{cases}\f]
Unnormalized box filter is useful for computing various integral characteristics over each pixel
neighborhood, such as covariance matrices of image derivatives (used in dense optical flow