fastNlMeansDenoising1

Computational photographyfunctionOpenCV 5.0.0

import { fastNlMeansDenoising1 } from '@banou/opencv-wasm'

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

ARGUMENTSsrc, dst, h, templateWindowSize

→

FUNCTIONfastNlMeansDenoising1

→

RETURN TYPEvoid

Call structure. A void return can still write to destination arguments. The parameter descriptions define inputs, outputs and ownership.

Perform image denoising using Non-local Means Denoising algorithm http://www.ipol.im/pub/algo/bcm_non_local_means_denoising/ with several computational optimizations. Noise expected to be a gaussian white noise

fastNlMeansDenoising1(src: Mat, dst: Mat, h: FloatVector, templateWindowSize: number, searchWindowSize: number, normType: number): void;

4 available overloads

fastNlMeansDenoising1(src: Mat, dst: Mat, h: FloatVector): void;

fastNlMeansDenoising1(src: Mat, dst: Mat, h: FloatVector, templateWindowSize: number): void;

fastNlMeansDenoising1(src: Mat, dst: Mat, h: FloatVector, templateWindowSize: number, searchWindowSize: number): void;

fastNlMeansDenoising1(src: Mat, dst: Mat, h: FloatVector, templateWindowSize: number, searchWindowSize: number, normType: number): void;

src

Input 8-bit or 16-bit (only with NORM_L1) 1-channel, 2-channel, 3-channel or 4-channel image.

dst

Output destination, filled by the native operation. Output image with the same size and type as src .

h

Array of parameters regulating filter strength, either one parameter applied to all channels or one per channel in dst. Big h value perfectly removes noise but also removes image details, smaller h value preserves details but also preserves some noise

templateWindowSize

Size in pixels of the template patch that is used to compute weights. Should be odd. Recommended value 7 pixels

searchWindowSize

Size in pixels of the window that is used to compute weighted average for given pixel. Should be odd. Affect performance linearly: greater searchWindowsSize - greater denoising time. Recommended value 21 pixels

normType

Type of norm used for weight calculation. Can be either NORM_L2 or NORM_L1

This function expected to be applied to grayscale images. For colored images look at fastNlMeansDenoisingColored. Advanced usage of this functions can be manual denoising of colored image in different colorspaces. Such approach is used in fastNlMeansDenoisingColored by converting image to CIELAB colorspace and then separately denoise L and AB components with different h parameter.

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.