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VapourSynth port of TNLMeans
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VFR-maniac/VapourSynth-TNLMeans
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TNLMeans for VapourSynth originally for AviSynth v2.5.x by tritical, and for VapourSynth by Yusuke Nakamura HELP FILE ------------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------------ INFO: TNLMeans is an implementation of the NL-means denoising algorithm. Aside from the original method, TNLMeans also supports extension into 3D and a faster, block based approach. Syntax => tnlm.TNLMeans(int ax, int ay, int az, int sx, int sy, int bx, int by, float a, float h, int ssd) THEORY OF OPERATION: The NL-means algorithm works in the following manner. For each pixel in the image define a search window in which to look for similar pixels. The search window is defined by the parameters ax and ay, which set the x-axis radius and y-axis radius. For each pixel in the window determine a weight based on the similarity of that pixel's gray level neighborhood to the center pixel's gray level neighborhood. The neighborhood is defined by the sx and sy parameters, which set the x-axis radius and y-axis radius. The similarity between two neighborhoods is measured using gaussian weighted (as a function of distance, the standard deviation is set by the "a" parameter) sum of squared differences. The final weight for a pixel is computed as: exp(-(total_sse_difference/sum_of_gaussian_weights)/(h*h)); If the parameter 'ssd' is set to false, then sum of absolute differences is used instead of sum of squared differences. In that case, the final weight for a pixel is computed as: exp(-(total_sad_difference/sum_of_gaussian_weights)/h); Once a weight for each pixel in the window is acquired, the final pixel value is simply the weighted average of all the pixels. In order for the center pixel to not be too heavily weighted, it is assigned a weight equal to the largest weight given to another pixel in the search window. The block based modification changes the base step (or base window) from 1 pixel to blocks with size bx and by where bx and by set the x-axis radius and y-axis radius. The support and search windows still work the same way, but now whole blocks are computed/averaged at once instead of individual pixels. This modification cuts the computation time down by (bx*2+1)*(by*2+1) times. The 3D extension allows extending the search window into neighbor frames. The parameter az sets the temporal (z-axis) radius. With az=1 frames n-1 and n+1 would be included. More information can be found by following the links to papers about NL-means under the TNLMeans portion of http://bengal.missouri.edu/~kes25c/. PARAMETERS: ax, ay, az - These set the x-axis, y-axis, and z-axis radii of the search window. These must be greater than or equal to 0. The full window size will be: (ax*2+1) x (ay*2+1) x (az*2+1) Generally, the larger the search window the better the result of the denoising. Of course, the larger the search window the longer the denoising takes. Default: ax = 4 (int) ay = 4 (int) az = 0 (int) sx, sy - These set the x-axis and y-axis radii of the support (similarity neighborhood) window. These must be greater than or equal to 0. A larger similarity window will retain more detail/texture but will also cause less noise removal. Typical values for sx/sy are 2 or 3. The full window size will be: (sx*2+1) x (sy*2+1) Default: sx = 2 (int) sy = 2 (int) bx, by - These set the x-axis and y-axis radii of the base window. In the original NL-means algorithm the base was a single pixel (bx=0 and by=0). Using blocks larger than a single pixel will sacrifice some quality for speed. Note that sx must be greater than or equal to bx and sy must be greater than or equal to by. It is recommended that sx/sy be larger than bx/by. Default: bx = 1 (int) by = 1 (int) a - Sets the standard deviation of the gaussian used for weighting the difference calculation used for computing neighborhood similarity. Smaller values will result in less noise removal but will retain more detail/texture. Default: 1.0 (float) h - Controls the strength of the filtering (blurring). Larger values will remove more noise but will also destroy more detail. 'h' should typically be set equal to the standard deviation of the noise in the image when using ssd=true and assuming the noise fits the zero mean, gaussian model. Default: if ssd = 1 - 1.8 (float) if ssd = 0 - 0.5 (float) ssd - Controls whether sum of squared differences or sum of absolute differences is used when computing neighborhood similarity. ssd is slightly slower but retains fine detail/texture better. sad typically works better for cartoons/anime. The 'h' parameter usually needs to be set about 4 times lower when using sad than when using ssd. 1 - use ssd 0 - use sad Default: 1 CHANGE LIST: 02/22/2015 - Supported up to 16 bit-depth per plane. 01/15/2015 - Supported VapourSynth native frame-based multi-threading. 01/14/2015 + Imported for VapourSynth. + Supported all planar 8-bit formats. + Use VapourSynth native reference counting for frame data instead of copying. - Removed YUY2 format support. - Removed multiscale version (parameters ms/rm). - Renamed 'sse' to 'ssd'. - Renamed all parameters into lowercases because of the plugin guidelines. CHANGE LIST (from the AviSynth plugin): 08/28/2007 v1.0.3 - Removed fast exp() approximation that was used for sse=false. Turns out it was quite inaccurate and had overflow problems resulting in artifacts. 07/30/2006 v1.0.2 - Fixed a problem with small weights causing artifacts 06/19/2006 v1.0.1 - Fixed a bug that caused a crash when ms=true was used with yuy2 input 05/31/2006 v1.0 Final - Fixed always creating the downsampled clip unless ms=false was explicitly specified 05/25/2006 v1.0 Beta 2 + Added multiscale version (parameters ms/rm) + Added sse parameter + optimized non-block based routines by buffering (100% speed increase) - removed b parameter - fixed a bug in the block based routines that caused some blocks in the search window not to be tested - changed defaults for ax/ay/sx/sy/h 05/17/2006 v1.0 Beta 1 - Initial Release
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