Feature/add strred runner (#53)

* Add matlab/strred.

* Make strred matlab cmd work.

* Add StrredFeatureExtractor and StrredQualityRunner.

* Update VERSION.

CHANGELOG.md

@@ -1,5 +1,10 @@
 # Change Log
 
+## (12/20/2016) [1.1.20]
+
+**New features:**
+- Add STRRED runner.
+
 ## (12/19/2016) [1.1.19]
 
 **New features:**

VERSION

@@ -1 +1 @@
-VMAF Development Kit (VDK) Version 1.1.19
+VMAF Development Kit (VDK) Version 1.1.20

matlab/.gitignore

@@ -0,0 +1 @@
+*~

matlab/strred/README

@@ -0,0 +1,23 @@
+** modifications **
+
+(12/19/2016 zli@netflix.com) Three modifications are made to fit into the VDK framework:
+1) Instead of specifying number of seconds to read, read file until the end.
+2) Instead of calculating a frame score every two frames, change it to one score
+every frame.
+3) Original algorithm averages frame SRRED and TRRED scores first, and the final
+STRRED score is the product of the two. In this modified version, only the per-
+frame SRRED and TRRED scores are calculated and passed out. The computation of
+the STRRED score is performed outside, by first computing the per-frame STRRED
+score via:
+per-frame STRRED = (per-frame SRRED) * (per-frame TRRED)
+and then aggregating (e.g. via taking the mean).
+
+** run **
+
+Command run_strred takes in arguments:
+ref_yuv_file_path dis_yuv_file_path width height
+
+After installing Matlab and setting path, run STRRED in command line:
+matlab -nodisplay -nosplash -nodesktop -r "run_strred('../../resource/yuv/src01_hrc00_576x324.yuv', '../../resource/yuv/src01_hrc01_576x324.yuv', 576, 324); exit;"
+
+

matlab/strred/SR_SIM.m

@@ -0,0 +1,112 @@
+function sim = SR_SIM(image1, image2)
+% ========================================================================
+% SR_SIM Index with automatic downsampling, Version 1.0
+% Copyright(c) 2011 Lin ZHANG
+% All Rights Reserved.
+%
+% ----------------------------------------------------------------------
+% Permission to use, copy, or modify this software and its documentation
+% for educational and research purposes only and without fee is hereQ
+% granted, provided that this copyright notice and the original authors'
+% names appear on all copies and supporting documentation. This program
+% shall not be used, rewritten, or adapted as the basis of a commercial
+% software or hardware product without first obtaining permission of the
+% authors. The authors make no representations about the suitability of
+% this software for any purpose. It is provided "as is" without express
+% or implied warranty.
+%----------------------------------------------------------------------
+%
+% This is an implementation of the algorithm for calculating the
+% Spectral Residual based Similarity (SR-SIM) index between two images. For
+% more details, please refer to our paper:
+% Lin Zhang and Hongyu Li, "SR-SIM: A fast and high performance IQA index based on spectral residual", in: Proc. ICIP 2012.
+%
+%----------------------------------------------------------------------
+%
+%Input : (1) image1: the first image being compared
+%        (2) image2: the second image being compared
+%
+%Output: sim: the similarity score between two images, a real number
+%        
+%-----------------------------------------------------------------------
+[rows, cols, junk] = size(image1);
+if junk == 3
+    Y1 = 0.299 * double(image1(:,:,1)) + 0.587 * double(image1(:,:,2)) + 0.114 * double(image1(:,:,3));
+    Y2 = 0.299 * double(image2(:,:,1)) + 0.587 * double(image2(:,:,2)) + 0.114 * double(image2(:,:,3));
+else
+    Y1 = double(image1);
+    Y2 = double(image2);
+end
+
+%%%%%%%%%%%%%%%%%%%%%%%%%
+% Download the image
+%%%%%%%%%%%%%%%%%%%%%%%%%
+minDimension = min(rows,cols);
+F = max(1,round(minDimension / 256));
+aveKernel = fspecial('average',F);
+
+aveY1 = conv2(Y1, aveKernel,'same');
+aveY2 = conv2(Y2, aveKernel,'same');
+Y1 = aveY1(1:F:rows,1:F:cols);
+Y2 = aveY2(1:F:rows,1:F:cols);
+
+%%%%%%%%%%%%%%%%%%%%%%%%%
+% Calculate the visual saliency maps
+%%%%%%%%%%%%%%%%%%%%%%%%%
+saliencyMap1 = spectralResidueSaliency(Y1);
+saliencyMap2 = spectralResidueSaliency(Y2);
+%%%%%%%%%%%%%%%%%%%%%%%%%
+% Calculate the gradient map
+%%%%%%%%%%%%%%%%%%%%%%%%%
+dx = [3 0 -3; 10 0 -10;  3  0 -3]/16;
+dy = [3 10 3; 0  0   0; -3 -10 -3]/16;
+IxY1 = conv2(Y1, dx, 'same');     
+IyY1 = conv2(Y1, dy, 'same');    
+gradientMap1 = sqrt(IxY1.^2 + IyY1.^2);
+
+IxY2 = conv2(Y2, dx, 'same');     
+IyY2 = conv2(Y2, dy, 'same');    
+gradientMap2 = sqrt(IxY2.^2 + IyY2.^2);
+
+%%%%%%%%%%%%%%%%%%%%%%%%%
+% Calculate the SR-SIM
+%%%%%%%%%%%%%%%%%%%%%%%%%
+C1 = 0.40; %fixed
+C2 = 225; 
+alpha = 0.50;%fixed
+
+GBVSSimMatrix = (2 * saliencyMap1 .* saliencyMap2 + C1) ./ (saliencyMap1.^2 + saliencyMap2.^2 + C1);
+gradientSimMatrix = (2*gradientMap1.*gradientMap2 + C2) ./(gradientMap1.^2 + gradientMap2.^2 + C2);
+
+weight = max(saliencyMap1, saliencyMap2);
+SimMatrix = GBVSSimMatrix .* (gradientSimMatrix .^ alpha) .* weight;
+sim = sum(sum(SimMatrix)) / sum(weight(:));
+
+return;
+
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+function saliencyMap = spectralResidueSaliency(image)
+%this function is used to calculate the visual saliency map for the given
+%image using the spectral residue method proposed by Xiaodi Hou and Liqing
+%Zhang. For more details about this method, you can refer to the paper:
+%Saliency detection: a spectral residual approach.
+
+%there are some parameters needed to be adjusted
+scale = 0.25; %fixed
+aveKernelSize = 3; %fixed
+gauSigma = 3.8; %fixed
+gauSize = 10; %fixed
+
+inImg = imresize(image, scale);
+
+%%%% Spectral Residual
+myFFT = fft2(inImg);
+myLogAmplitude = log(abs(myFFT));
+myPhase = angle(myFFT);
+
+mySpectralResidual = myLogAmplitude - imfilter(myLogAmplitude, fspecial('average', aveKernelSize), 'replicate');
+saliencyMap = abs(ifft2(exp(mySpectralResidual + 1i*myPhase))).^2;
+
+%%%% After Effect
+saliencyMap = mat2gray(imfilter(saliencyMap, fspecial('gaussian', [gauSize, gauSize], gauSigma)));
+saliencyMap = imresize(saliencyMap,[size(image,1) size(image,2)]);