Demo_TWSC_RGB2YUV_DND2017.m

%-------------------------------------------------------------------------------------------------------------
% This is an implementation of the TWSC algorithm for real-world image denoising
% by processing the YUV channels insead of RGB channels, it would improve
% TWSC by at 0.1dB on PSNR.
% Author:  Jun Xu, csjunxu@comp.polyu.edu.hk / nankaimathxujun@gmail.com
%          The Hong Kong Polytechnic University
%
% Please refer to the following paper if you find this code helps:
%
% @article{TWSC_ECCV2018,
% 	author = {Jun Xu and Lei Zhang and David Zhang},
% 	title = {A Trilateral Weighted Sparse Coding Scheme for Real-World Image Denoising},
% 	journal = {ECCV},
% 	year = {2018}
% }
%
% Please see the file License.txt for the license governing this code.
%-------------------------------------------------------------------------------------------------------------
clear;
Original_image_dir = 'dnd_2017/images_srgb/';
fpath = fullfile(Original_image_dir, '*.mat');
im_dir  = dir(fpath);
im_num = length(im_dir);
load 'dnd_2017/info.mat';

method = 'TWSC_rgb2yuv';
dataset = 'dnd';
% write image directory
write_MAT_dir = [dataset '_Results/'];
write_sRGB_dir = [write_MAT_dir method];
if ~isdir(write_sRGB_dir)
    mkdir(write_sRGB_dir)
end
% Parameters
Par.ps = 6;        % patch size
Par.step = 3;       % the step of two neighbor patches
Par.win = 20;   % size of window around the patch
Par.Outerloop = 8;
Par.Innerloop = 2;
Par.nlspini = 70;
Par.display = 0;
Par.delta = 0;
Par.nlspgap = 0; %10
Par.lambda1 = 0;
Par.lambda2 = 3;
% record all the results in each iteration
Par.PSNR = zeros(Par.Outerloop, im_num*20, 'double');
Par.SSIM = zeros(Par.Outerloop, im_num*20, 'double');
for i = 1 :im_num
    Par.image = i;
    load(fullfile(Original_image_dir, im_dir(i).name));
    S = regexp(im_dir(i).name, '\.', 'split');
    [h,w,ch] = size(InoisySRGB);
    for j = 1:size(info(1).boundingboxes,1)
        Par.nlsp = Par.nlspini;  % number of non-local patches
        IMinname = [S{1} '_' num2str(j)];
        bb = info(i).boundingboxes(j,:);
        Par.nim = InoisySRGB(bb(1):bb(3), bb(2):bb(4),:);
        Par.I = Par.nim;
        Par.nim = rgb2ycbcr(Par.nim);
        [h,w,ch] = size(Par.nim);
        % noise estimation
        for c = 1:ch
            Par.nSig(c) = NoiseEstimation(Par.nim(:, :, c)*255, Par.ps)/255;
        end
        [IMout, Par]  =  TWSC_Sigma_RW(Par);
        IMout = ycbcr2rgb(IMout);
        % initial PSNR and SSIM
        fprintf('%s: \n', IMinname);
        % calculate the PSNR
        Par.PSNR(Par.Outerloop, Par.image)  =   csnr( IMout*255, Par.I*255, 0, 0 );
        Par.SSIM(Par.Outerloop, Par.image)      =  cal_ssim( IMout*255, Par.I*255, 0, 0 );
        %% output
        imwrite(IMout, [write_sRGB_dir '/' method '_' dataset '_' IMinname '.png']);
    end
end