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Proceedings Paper

Design of subband coders for high-quality images based on perceptual criteria
Author(s): V. Ralph Algazi; Gary E. Ford; Matthew Mow; Azfar Najmi
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Paper Abstract

A number of new approaches to image coding are being developed to meet the increasing need for a broader range of quality and usage environments for image compression. Several of these new approaches, such as subband coders, are intended to provide higher quality images at the same bit rate as compared to the JPEG standard, because they are not subject to end of block artifacts, or because they are inherently better attuned to the image representation that occurs in the peripheral visual system. Still, in the absence of a pertinent quality criterion, the quality and performance of subband coders, or wavelet coders, can be mediocre. We have developed over the past few years the elements of a methodology applicable to this problem. We reported last year at the SPIE in San Diego, a Comparison of Coding Techniques based on a new Picture Quality Scale (PQS). In that work, we were able to rate coders designed by any criteria, on the basis of performance and quality. The problem that we are now considering is to design the coding technique so as to provide a better quality or a lower bit rate. The image quality, as evaluated by PQS, depends on a combination of several objective distortion factors, which can be identified with perceived coding artifacts, but the design of coders using all the factors is much too complex for an analytical approach. We make use instead of two design methodologies. The first one is to optimize the design of an existing subband coder using PQS as a distortion metric. The second one makes use of a methodology for the design of linear filters based on properties of human perception that we have developed previously and that may provide a tractable design method.

Paper Details

Date Published: 20 October 1993
PDF: 7 pages
Proc. SPIE 2028, Applications of Digital Image Processing XVI, (20 October 1993); doi: 10.1117/12.158655
Show Author Affiliations
V. Ralph Algazi, Univ. of California/Davis (United States)
Gary E. Ford, Univ. of California/Davis (United States)
Matthew Mow, Univ. of California/Davis (United States)
Azfar Najmi, Univ. of California/Davis (United States)


Published in SPIE Proceedings Vol. 2028:
Applications of Digital Image Processing XVI
Andrew G. Tescher, Editor(s)

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