EVALUATION OF IMAGE QUALITY METRICS

Chief investigator: Martin Čadík, email: cadikm@fel.cvut.cz, homepage: http://www.cgg.cvut.cz/~cadikm

Project web page: http://www.cgg.cvut.cz/~cadikm/iqm

Project description:

The goal of the project is the evaluation of state-of the art image quality metrics. We conduct both the subjective and objective comparisons of metrics.

FULL-REFERENCE IMAGE QUALITY METRICS

Full-reference image quality metrics

IMPLEMENTED IMAGE QUALITY METRICS

Original image	Distorted image	Map of differences	Method
			S. Daly The Visible Differences Predictor: An Algorithm for the Assessment of Image Fidelity
			Z. Wang, A. C. Bovik A Universal Image Quality Index http://www.cns.nyu.edu/~zwang/files/papers/uqi.html Matlab code available
			Z. Wang, A. C. Bovik, H. R. Seikh, E. P. Simoncelli Image quality assessment: From error visibility to structural similarity Matlab code available
			A. Shnayderman, A. Gusev, A. M. Eskicioglu An SVD-Based Gray-Scale Image Quality Measure for Local and Global Assessment http://www.sci.brooklyn.cuny.edu/~eskicioglu/papers Published also in [An SVD-Based Gray-Scale Image Quality Measure for Local and Global Assessment]

METHODS TO IMPLEMENT

TODO	J. L. Mannos, D. J. Sakrison The Effects of a visual fidelity criterion on the encoding of images
TODO	H. Rushmeier, G. Ward, C. Piatko, P. Sanders Comparing Real and Synthetic Images: Some Ideas About Metrics Model after [Gervais84]
TODO	Patrick C. Teo, David J. Heeger Perceptual image distortion
TODO	J. Lubin A visual discrimination model for imaging system design and evaluation
TODO	C.C. Taylor, Z. Pizlo, J.P. Allebach, C.A. Bouman Image Quality Assessment with a Gabor Pyramid Model of the Human Visual System
TODO	M.R.M. Nijenhuis, F.J.J. Blommaert Perceptual-error measure and its application to sampled and interpolated single-edged images
TODO	L. Neumann, K. Matkovic, W. Purgathofer Perception based color image difference
TODO	A. P. Bradley A Wavelet Visible Difference Predictor
TODO	J. Oh, S. I. Wooley, T. N. Arvanitis, J. N. Townend A multistage perceptual quality assessment for compressed digital angiogram images
TODO	X. Tong, D. Heeger, C. J. van den B. Lambrecht Video quality evaluation using ST-CIELAB
TODO	R. Mantiuk, S. Daly, K. Myszkowski, H.-P. Seidel Predicting Visible Differences in High Dynamic Range Images - Model and its Calibration Extends VDP for HDR, also published in [Visible Difference Predicator for High Dynamic Range Images] http://www.mpi-inf.mpg.de/resources/hdr/vdp/
TODO	Kuang, J., Johnson, G.M., Fairchild M.D. iCAM06: A refined image appearance model for HDR image rendering Extends iCAM, MatLab code available
TODO	Tunc Ozan Aydin, Rafal Mantiuk, Karol Myszkowski, Hans-Peter Seidel Dynamic Range Independent Image Quality Assessment 3 types of distortion: loss of visible contrast, amplification of invisible contrast, reversal of visible contrast, project page (online implementation)
TODO	Rafal Mantiuk, Kil Joong Kim, Allan G. Rempel, Wolfgang Heidrich HDR-VDP-2: A calibrated visual metric for visibility and quality predictions in all luminance conditions

PUBLICATIONS

*Author*	*Title*	*Publishing* *details*
Čadík, M., Slavík, P.	Evaluation of Two Principal Approaches to Objective Image Quality Assessment [bibTeX entry (bib)]	8th International Conference on Information Visualization. Los Alamitos: IEEE Computer Society Press, 2004.
Čadík, M.	Perceptual Image Quality Assessment Metrics	CODATA Information Visualization Workshop 2004. Prague, 2004.
Čadík, M.	Human Perception and Computer Graphics	Postgraduate Study Report. Czech Technical University in Prague, 2004.
Čadík, M., Slavík, P.	Comparing Image-Processing Operators by Means of the Visible Differences Predictor	WSCG 2004. Pilsen: University of West Bohemia, 2004.

RESOURCES

Our experimental data and input images

Image and Video Quality Assessment at LIVE
Video Quality Experts Group (VQEG)