filter2Dp

Image processingfunctionOpenCV 5.0.0

import { filter2Dp } from '@banou/opencv-wasm'

Use after await initOpenCV(). See the initialization and named imports guide.

Convolves an image with the kernel.

The function applies an arbitrary linear filter to an image. In-place operation is supported. When the aperture is partially outside the image, the function interpolates outlier pixel values according to the specified border mode.

The function does actually compute correlation, not the convolution:

\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} )

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 - anchor.y - 1).

The function uses the DFT-based algorithm in case of sufficiently large kernels (~`11 x 11` or larger) and the direct algorithm for small kernels.

See: sepFilter2D, dft, matchTemplate

filter2Dp(src: Mat, dst: Mat, kernel: Mat, params: Filter2DParams): void;

2 available overloads

filter2Dp(src: Mat, dst: Mat, kernel: Mat): void;

filter2Dp(src: Mat, dst: Mat, kernel: Mat, params: Filter2DParams): void;

src: input image.
dst: Output destination, filled by the native operation. output image of the same size and the same number of channels as src.
kernel: convolution kernel (or rather a correlation kernel), a single-channel floating point matrix; if you want to apply different kernels to different channels, split the image into separate color planes using split and process them individually.
params: params argument (Filter2DParams).

Upstream declaration ↗

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