On the Optimal Choice of Quality Metric in Image Compression A Soft Computing Approach

Authors

Hung T. Nguyen
Olga Kosheleva, The University of Texas at El PasoFollow
Vladik Kreinovich, The University of Texas at El PasoFollow
Liya Ding

Publication Date

8-2000

Comments

UTEP-CS-00-25b.

Published in Proceedings of the Sixth International Conference on Control, Automation, Robotics and Vision ICARCV'2000, Singapore, December 5--8, 2000.

Abstract

In a lossy compression, the reconstructed image I' differs from the original image I. In different situations, different compressions lead to different quality reconstruction, so it is important to select, in each situation, the best compression method. It's natural to select the compression method for which the average value of some quality metric d(I,I') is the smallest. Which quality metric should we choose? We show that under reasonable symmetry conditions, L^p metrics d(I,I')=integral of |I(x)-I'(x)|^p are the best, and how to compute the optimal value of p from the expected relative size of the informative part of the image.