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101 lines
4.4 KiB
Matlab
101 lines
4.4 KiB
Matlab
% [Im] = nonlocalTV_GPU(Im0,CloseInd, Neighbours, Rwin,Niter,lambda, dt, eps)
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% FUNCTION
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% nonlocal total variation solved by a simple steepest descent solver
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% Inputs:
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% Im0 - regularized array (3D volume)
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% CloseInd - close indices generated by nonlocalTV_weight code
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% Neighbours - number of neighbors used for calculation
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% Rwin - radius of the window used to find similar regions
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% Niter - number of reconstruction iterations
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% lambda - step size (tunning value), usually < 1, if zero ->
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% completelly ignore data and just find the solution that most fits to
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% nonlocal TV constraint
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% dt - also kind of step size (tunning value), usually << 1
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% eps - regularization constant (tunning value), usually << 1
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% RECOMPILE COMMAND
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% mexcuda -output +regularization/private/nonlocalTV_tex +regularization/private/TV_cuda_texture.cu +regularization/private/nonlocalTV_mex.cpp
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%*-----------------------------------------------------------------------*
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%| |
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%| Except where otherwise noted, this work is licensed under a |
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%| Creative Commons Attribution-NonCommercial-ShareAlike 4.0 |
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%| International (CC BY-NC-SA 4.0) license. |
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%| |
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%| Copyright (c) 2017 by Paul Scherrer Institute (http://www.psi.ch) |
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%| |
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%| Author: CXS group, PSI |
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%*-----------------------------------------------------------------------*
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% You may use this code with the following provisions:
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%
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% If the code is fully or partially redistributed, or rewritten in another
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% computing language this notice should be included in the redistribution.
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%
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% If this code, or subfunctions or parts of it, is used for research in a
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% publication or if it is fully or partially rewritten for another
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% computing language the authors and institution should be acknowledged
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% in written form in the publication: “Data processing was carried out
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% using the “cSAXS matlab package” developed by the CXS group,
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% Paul Scherrer Institut, Switzerland.”
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% Variations on the latter text can be incorporated upon discussion with
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% the CXS group if needed to more specifically reflect the use of the package
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% for the published work.
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%
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% A publication that focuses on describing features, or parameters, that
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% are already existing in the code should be first discussed with the
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% authors.
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%
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% This code and subroutines are part of a continuous development, they
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% are provided “as they are” without guarantees or liability on part
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% of PSI or the authors. It is the user responsibility to ensure its
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% proper use and the correctness of the results.
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function [Im] = nonlocalTV_GPU(Im0,CloseInd, Neighbours, Rwin,Niter,lambda, dt, eps)
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keep_on_gpu = isa(Im0, 'gpuArray');
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CloseInd = gpuArray(uint8(CloseInd));
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Im0 = gpuArray(single(Im0));
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try
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%Input should be between 0 and 1 to make the regularizations constants selection
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%kind of repeatable for similar samples
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minIm=min(Im0(:));
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Im0=Im0-minIm;
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maxIm=prctile(Im0(1:10:end), 99);
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Im0=Im0/maxIm;
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catch err
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error(err.message)
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end
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Nclose = size(CloseInd,ndims(CloseInd));
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%% primitive replacement of the real weights based on assumption that CloseInd is sorted by importance !!!
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Nnbrs = size(CloseInd,ndims(CloseInd));
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% Nbrs_weights = single(exp(-linspace(0,1,Nnbrs)));
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Nbrs_weights = single(1./(1:Nnbrs));
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% Nbrs_weights = ones(Nnbrs,1, 'single');
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% keyboard
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% tic
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Im = nonlocalTV_tex(Im0,CloseInd,uint8(Neighbours), Nbrs_weights, dt, eps, lambda, Nclose, Rwin,Niter);
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% wait(gpu)
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% toc
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%Back to original pixel range
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Im=Im*maxIm;
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Im=Im+minIm;
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if ~keep_on_gpu
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Im = gather(Im);
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end
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end
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