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Proceedings Paper

Quantifying coding performance for preprocessed images
Author(s): V. Ralph Algazi; Niranjan Avadhanam; Robert R. Estes
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Paper Abstract

Typical objective methods for quantifying image quality, as part of evaluating coder performance, are obtained by computing a single or several numbers as a function of the difference image between the original and coded images. Pre- processing images prior to encoding can remove noise, or unimportant detail, and thus improve the overall performance of the coder.However, the error image obtained with the pre- processed image as a reference is substantially different than the one obtained if the original. This paper addresses the issue of combining the changes in the image due to pre- processing and the degradation due to encoding. The objective is to obtain global quality measures that quantify the value of pre-processing for image coding.

Paper Details

Date Published: 4 April 1997
PDF: 11 pages
Proc. SPIE 3025, Very High Resolution and Quality Imaging II, (4 April 1997); doi: 10.1117/12.270045
Show Author Affiliations
V. Ralph Algazi, Univ. of California/Davis (United States)
Niranjan Avadhanam, Univ. of California/Davis (United States)
Robert R. Estes, Univ. of California/Davis (United States)

Published in SPIE Proceedings Vol. 3025:
Very High Resolution and Quality Imaging II
V. Ralph Algazi; Sadayasu Ono; Andrew G. Tescher, Editor(s)

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