A Survey of Quality Measures for Gray Scale Image Compression

Although a variety of techniques are available today for gray-scale image compression, a complete evaluation of these techniques cannot be made as there is no single reliable objective criterion for measuring the error in compressed images. The traditional subjective criteria are burdensome, and usually inaccurate or inconsistent. On the other hand, being the most common objective criterion, the mean square error (MSE) does not have a good correlation with the viewer's response. It is now understood that in order to have a reliable quality measure, a representative model of the complex human visual system is required. In this paper, we survey and give a classification of the criteria for the evaluation of monochrome image quality.

[1]  Charles F. Hall Subjective Evaluation Of A Perceptual Quality Metric , 1981, Optics & Photonics.

[2]  David R. Ahlgren,et al.  Compression Of Digitized Images For Transmission And Storage Applications , 1988, Photonics West - Lasers and Applications in Science and Engineering.

[3]  D. Sakrison,et al.  On the Role of the Observer and a Distortion Measure in Image Transmission , 1977, IEEE Trans. Commun..

[4]  D.J. Granrath,et al.  The role of human visual models in image processing , 1981, Proceedings of the IEEE.

[5]  John A. Saghri,et al.  Image Quality Measure Based On A Human Visual System Model , 1989 .

[6]  P. Ferrelle Recursive block coding for image data compression , 1990 .

[7]  Anil K. Jain Fundamentals of Digital Image Processing , 2018, Control of Color Imaging Systems.

[8]  Hans Marmolin,et al.  Subjective MSE Measures , 1986, IEEE Transactions on Systems, Man, and Cybernetics.

[9]  Anil K. Jain,et al.  Image data compression: A review , 1981, Proceedings of the IEEE.

[10]  Ian H. Witten,et al.  Text Compression , 1990, 125 Problems in Text Algorithms.

[11]  N B Nill Scene power spectra: the moment as an image quality merit factor. , 1976, Applied optics.

[12]  Pamela C. Cosman,et al.  Tree-structured vector quantization of CT chest scans: image quality and diagnostic accuracy , 1993, IEEE Trans. Medical Imaging.

[13]  Harry L. Snyder,et al.  Image Quality: Measures and Visual Performance , 1985 .

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

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

[16]  King Ngi Ngan,et al.  Adaptive cosine transform coding of images in perceptual domain , 1989, IEEE Trans. Acoust. Speech Signal Process..

[17]  Mark Nelson,et al.  The Data Compression Book , 2009 .

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