SmoothPatchBased node — Natron 2.5.0 documentation

# SmoothPatchBased node

This documentation is for version 2.0 of SmoothPatchBased (net.sf.cimg.CImgDenoise).

## Description

Denoise selected images by non-local patch averaging.

This uses the method described in: Non-Local Image Smoothing by Applying Anisotropic Diffusion PDE’s in the Space of Patches (D. Tschumperlé, L. Brun), ICIP’09 (https://tschumperle.users.greyc.fr/publications/tschumperle_icip09.pdf).

Uses the ‘blur_patch’ function from the CImg library.

CImg is a free, open-source library distributed under the CeCILL-C (close to the GNU LGPL) or CeCILL (compatible with the GNU GPL) licenses. It can be used in commercial applications (see http://cimg.eu).

## Inputs

Input | Description | Optional
--- | --- | ---
Source |  | No
Mask |  | Yes

## Controls

Parameter / script name | Type | Default | Function
--- | --- | --- | ---
Spatial Std Dev / `sigma_s` | Double | 10 | Standard deviation of the spatial kernel, in pixel units (>=0).
Value Std Dev / `sigma_r` | Double | 0.05 | Standard deviation of the range kernel, in intensity units (>=0). In the context of denoising, Liu et al. (“Noise estimation from a single image”, CVPR2006) recommend a value of 1.95*sigma_n, where sigma_n is the local image noise.
Patch Size / `psize` | Integer | 5 | Size of the patchs, in pixels (>=0).
Lookup Size / `lsize` | Integer | 6 | Size of the window to search similar patchs, in pixels (>=0).
Smoothness / `smoothness` | Double | 1 | Smoothness for the patch comparison, in pixels (>=0).
fast Approximation / `is_fast_approximation` | Boolean | On | Tells if a fast approximation of the gaussian function is used or not
(Un)premult / `premult` | Boolean | Off | Divide the image by the alpha channel before processing, and re-multiply it afterwards. Use if the input images are premultiplied.
Invert Mask / `maskInvert` | Boolean | Off | When checked, the effect is fully applied where the mask is 0.
Mix / `mix` | Double | 1 | Mix factor between the original and the transformed image.