fastNlMeansDenoisingMulti

Computational photographyfunctionOpenCV 5.0.0

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

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

Explore visually: Non-local means denoising →

Average pixels whose surrounding patches look similar, even when they are not immediate neighbours.

VISUAL WALKTHROUGHPhotography

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 156.2.

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

Modification of fastNlMeansDenoising function for images sequence where consecutive images have been captured in small period of time. For example video. This version of the function is for grayscale images or for manual manipulation with colorspaces. See [Buades2005DenoisingIS] for more details (open access here).

fastNlMeansDenoisingMulti(srcImgs: MatVector, dst: Mat, imgToDenoiseIndex: number, temporalWindowSize: number, h: number, templateWindowSize: number, searchWindowSize: number): void;

4 available overloads

fastNlMeansDenoisingMulti(srcImgs: MatVector, dst: Mat, imgToDenoiseIndex: number, temporalWindowSize: number): void;

fastNlMeansDenoisingMulti(srcImgs: MatVector, dst: Mat, imgToDenoiseIndex: number, temporalWindowSize: number, h: number): void;

fastNlMeansDenoisingMulti(srcImgs: MatVector, dst: Mat, imgToDenoiseIndex: number, temporalWindowSize: number, h: number, templateWindowSize: number): void;

fastNlMeansDenoisingMulti(srcImgs: MatVector, dst: Mat, imgToDenoiseIndex: number, temporalWindowSize: number, h: number, templateWindowSize: number, searchWindowSize: number): void;

srcImgs

Input 8-bit 1-channel, 2-channel, 3-channel or 4-channel images sequence. All images should have the same type and size.

dst

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

imgToDenoiseIndex

Target image to denoise index in srcImgs sequence

temporalWindowSize

Number of surrounding images to use for target image denoising. Should be odd. Images from imgToDenoiseIndex - temporalWindowSize / 2 to imgToDenoiseIndex + temporalWindowSize / 2 from srcImgs will be used to denoise srcImgs[imgToDenoiseIndex] image.

h

Parameter regulating filter strength. Bigger 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

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.