filter2D

Image processingfunctionOpenCV 5.0.0

import { filter2D } from '@banou/opencv-wasm'

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

Explore visually: Custom correlation kernels →

Apply your own linear filter to every pixel neighbourhood.

VISUAL WALKTHROUGHFiltering

REFERENCE INPUTNoisy or uneven image

The same scene stays here while the working view changes.

→

RESULTApply the rule at every pixel

The whole image has now been processed. The highlighted input value 156 becomes 232.3.

Computed teaching example on a 24 × 16 image. Small kernels and simplified settings keep each change visible; use the image laboratory for native OpenCV.

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

filter2D(src: Mat, dst: Mat, ddepth: number, kernel: Mat, anchor: Point, delta: number, borderType: number): void;

4 available overloads

filter2D(src: Mat, dst: Mat, ddepth: number, kernel: Mat): void;

filter2D(src: Mat, dst: Mat, ddepth: number, kernel: Mat, anchor: Point): void;

filter2D(src: Mat, dst: Mat, ddepth: number, kernel: Mat, anchor: Point, delta: number): void;

filter2D(src: Mat, dst: Mat, ddepth: number, kernel: Mat, anchor: Point, delta: number, borderType: number): 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.

ddepth

desired depth of the destination image, see filter_depths "combinations"

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.

anchor

anchor of the kernel that indicates the relative position of a filtered point within the kernel; the anchor should lie within the kernel; default value (-1,-1) means that the anchor is at the kernel center.

delta

optional value added to the filtered pixels before storing them in dst.

borderType

pixel extrapolation method, see #BorderTypes. #BORDER_WRAP is not supported.

Upstream declaration ↗

These signatures describe this package. Upstream documentation can mention optional backends that are absent from this build. Check runtime compatibility before choosing a backend or file format.