Denoise image

Perform image denoising

Documentation

Algorithms

Bilateral

Edge-preserving denoising filter

window size:

Window size for filtering

sigma color:

Standard deviation for grey/color distance. Larger values resultsin averaging of pixels with larger grey/color differences. If 0.0 then compute and use the standard deviation in the image.

sigma spatial:

Standard deviation for range distances. A larger value results in averaging pixels that are further apart.

bins:

Number of discrete values for gaussian weights of color filtering

edge mode:

How to handle values outside the image borders

cval:

Value used when mode is constant

multichannel:

Wheter to treat the channels as colors or a separate spatial dimension

Non-local means

A de-noising technique suited for images with specific textures. It finds other pixels in a neighbourhood that have a similartexture within the given patch size, and computes the average ofthese pixels.

sigma:

Optional: standard deviation of a presumed white gaussian noise

patch size:

Size of the texture area that must match

patch distance:

Maximum distance to search for similar pixels

h:

Cut-off distance (grey levels). Higher values accept more patches.

fast:

Uses an alternative faster algorithm

multichannel:

Process multiple channels at the same time

Total variation Bregman

Total variation denoising using split-Bregman optimization

weight:

Controls amount of denoising performed. Smaller values give higher denoising

iter:

Maximum number of iterations of algoritm

isotropic:

If false use anisotropic filtering instead

Total variation Chambolle

Total variation denoising using split-Bregman optimization

weight:

Controls amount of denoising performed. Greater values give higher denoising

iter:

Maximum number of iterations of algoritm

Wavelet

Wavelet denoising

sigma:

Estimated standard deviation of noise, if 0.0 then an automatic estimate is calculated

wavelet levels:

Number of wavelet decomposition levels to use, if 0 then use 3 less levels than the maximum given the image size

wavelet:

Type of wavelet to calculate

mode:

Type of denoising to perform, soft is best for additive noise

convert to YCbCr:

If true and if multichannel is true, then convert RGB to the YCbCr colorspace.

method:

Thresholding method to use

multichannel:

Applies denoising for each channel separately vs. together

Definition

Input ports

source image

source image to denoise

Output ports

result image

result after denoising

Configuration

Algorithm (algorithm)

(no description)

bins (bins)

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convert to YCbCr (convert to YCbCr)

(no description)

cval (cval)

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edge mode (edge mode)

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fast (fast)

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h (h)

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isotropic (isotropic)

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iter (iter)

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method (method)

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mode (mode)

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multichannel (multichannel)

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patch distance (patch distance)

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patch size (patch size)

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sigma (sigma)

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sigma color (sigma color)

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sigma spatial (sigma spatial)

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wavelet (wavelet)

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wavelet levels (wavelet levels)

(no description)

weight (weight)

(no description)

window size (window size)

(no description)

Implementation

class node_noise.ImageDenoise