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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: 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 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 - 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 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 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 neighborhood, such as covariance matrices of image derivatives (used in dense optical flow