Introduction

MAD (Most Apparent Distortion) index is presented by Larson and Chandler on 2010 [1].

Source Code

The authors of MAD provide two different implementations. They claim that the newer version can get better result. Here, we adopt their newer version, which can be downloaded from here http://vision.eng.shizuoka.ac.jp/mad/MAD_index_2011_10_07.zip

Usage Notes

1. Do not change the default parameter settings.

2. [Index] = MAD_index(imRef, imDis);
    madMetricValue = Index.MAD;

Evaluation Results

The results (in Matlab .mat format) are provided here. Each result file contains a n by 2 matrix, where n denotes the number of distorted images in the database. The first column is the IFC values, and the second column is the mos/dmos values provided by the database. For example, you can use the following matlab code to calculate the SROCC and KROCC values for IFC values obtained on the TID2008 database:

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matData = load('MADOnTID.mat');
MADOnTID= matData.MADOnTID;
MAD_TID_SROCC = corr(MADOnTID(:,1), MADOnTID(:,2), 'type', 'spearman');
MAD_TID_KROCC = corr(MADOnTID(:,1), MADOnTID(:,2), 'type', 'kendall');

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The source codes to calculate the PLCC and RMSE are also provided for each database. This needs a nonlinear regression procedure which is dependant on the initialization of the parameters. We try to adjust the parameters to get a high PLCC value. For different databases, the parameter initialization may be different. The nonlinear fitting function is of the form as described in [2].

Evaluation results of MAD on seven databases are given below. Besides, for each evaluation metric, we present its weighted-average value over all the testing datasets; and the weight for each database is set as the number of distorted images in that dataset.

Reference                

[1] E.C. Larson and D.M. Chandler, "Most apparent distortion: full-reference image quality assessment and the role of strategy", Journal of Electronic Imaging, vol. 19, no. 1,  pp. 011006-1-011006-21, 2010.

[2] H.R. Sheikh, M.F. Sabir, and A.C. Bovik, "A statistical evaluation of recent full reference image quality assessment algorithms", IEEE Trans. on Image Processing, vol. 15, no. 11, pp. 3440-3451, 2006.

Created on: May 08, 2011

Last update: Jul. 14, 2016