A Review on Image Distortion Measures

Within this paper we review image distortion measures. A distortion measure is a criterion that assigns a "quality number" to an image. We distinguish between mathematical distortion measures and those distortion measures in-cooperating a priori knowledge about the imaging devices ( e.g. satellite images), image processing algorithms or the human physiology. We will consider representative examples of different kinds of distortion measures and are going to discuss them.

[1]  E. M. Lowry,et al.  Sine-wave response of the visual system. I. The Mach phenomenon. , 1961, Journal of the Optical Society of America.

[2]  DAVID J. SAKRISON,et al.  The Rate Distortion Function for a Class of Sources , 1969, Inf. Control..

[3]  R A Kirsch,et al.  Computer determination of the constituent structure of biological images. , 1971, Computers and biomedical research, an international journal.

[4]  Toby Berger,et al.  Rate distortion theory : a mathematical basis for data compression , 1971 .

[5]  A D Schnitzler Image-detector model and parameters of the human visual system. , 1973, Journal of the Optical Society of America.

[6]  David J. Sakrison,et al.  The effects of a visual fidelity criterion of the encoding of images , 1974, IEEE Trans. Inf. Theory.

[7]  G. Matheron Random Sets and Integral Geometry , 1976 .

[8]  D. J. Sakrison,et al.  Structure and properties of a single channel in the human visual system , 1976, Vision Research.

[9]  W A Pearlman A visual system model and a new distortion measure in the context of image processing. , 1978, Journal of the Optical Society of America.

[10]  John O. Limb,et al.  Distortion Criteria of the Human Viewer , 1979, IEEE Transactions on Systems, Man, and Cybernetics.

[11]  Edward H. Adelson,et al.  Orthogonal Pyramid Transforms For Image Coding. , 1987, Other Conferences.

[12]  W. Vervaat Narrow and vague convergence of set functions , 1988 .

[13]  Eero P. Simoncelli Orthogonal sub-band image transforms , 1988 .

[14]  Brian Bouzas,et al.  Objective image quality measure derived from digital image power spectra , 1992 .

[15]  A. Baddeley An Error Metric for Binary Images , 1992 .

[16]  Andrew B. Watson,et al.  Digital images and human vision , 1993 .

[17]  V. Ralph Algazi,et al.  Comparison of image coding techniques with a picture quality scale , 1993, Optics & Photonics.

[18]  Aaron D. Wyner,et al.  Coding Theorems for a Discrete Source With a Fidelity CriterionInstitute of Radio Engineers, International Convention Record, vol. 7, 1959. , 1993 .

[19]  Avideh Zakhor,et al.  Multirate 3-D subband coding of video , 1994, IEEE Trans. Image Process..

[20]  C. A. Laffan Vision in communication , 1994 .

[21]  Pamela C. Cosman,et al.  Evaluating quality of compressed medical images: SNR, subjective rating, and diagnostic accuracy , 1994, Proc. IEEE.

[22]  Matthew Brand,et al.  Physics-Based Visual Understanding , 1997, Comput. Vis. Image Underst..

[23]  Pamela C. Cosman,et al.  Image quality in lossy compressed digital mammograms , 1997, Signal Process..

[24]  Julian Magarey,et al.  Motion estimation using a complex-valued wavelet transform , 1998, IEEE Trans. Signal Process..

[25]  V. Ralph Algazi,et al.  Objective picture quality scale (PQS) for image coding , 1998, IEEE Trans. Commun..