You are an expert in writing code in many different languages. Your goal is to perform code completion for the following code, keeping in mind the rest of the code and the file meta data.
    Metadata details:
    filename: Demo_SISR_direct_downsampler_real_application.m
    path of file: ./repos/IRCNN
    
    the code of the file until where you have to start completion: %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Demo of IRCNN for image super-resolution where the latent HR
    
function is given by min_x 1/(Isigma^2)||x*k_{direct downsampler with scale factor sf}-y||^2 + Phi(x)
%
%                  k  --  blur kernel, not limited to Gaussian blur
% direct downsampler  --  implemented by matlab function "downsample",
%                 sf  --  scale factor, 2,3,4,...
%             Isigma  --  estimated noise level of y, should be larger than the true one.
%
% @inproceedings{zhang2017learning,
%   title={Learning Deep CNN Denoiser Prior for Image Restoration},
%   author={Zhang, Kai and Zuo, Wangmeng and Gu, Shuhang and Zhang, Lei},
%   booktitle={IEEE Conference on Computer Vision and Pattern Recognition},
%   year={2017}
% }
%
%
% If you have any question, please feel free to contact with me.
% Kai Zhang (e-mail: cskaizhang@gmail.com)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% clear; clc;

addpath('utilities');

imageSets   = {'SISR_set1','SISR_set2'}; % testing dataset

%%% setting
setTest     = imageSets(1); % select the dataset
showResult  = 1;
pauseTime   = 0;
useGPU      = 1; % 1 or 0, true or false

folderTest  = 'testsets';
folderResult= 'results';
taskTestCur = 'SISR';
if ~exist(folderResult,'file')
    mkdir(folderResult);
end