Reduction of JPEG compression artifacts by kernel regression and probabilistic self-organizing maps

Authors:
María Nieves Florentín-Núñez;Ezequiel López-Rubio;Francisco Javier López-Rubio
Affiliations:
Department of Computer Languages and Computer Science, University of Málaga, Málaga, Spain;Department of Computer Languages and Computer Science, University of Málaga, Málaga, Spain;Department of Computer Languages and Computer Science, University of Málaga, Málaga, Spain
Venue:
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part II
Year:
2011

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Abstract

There is a wide range of methods for lossy compression, but among those most used we find JPEG (Joint Photographic Experts Group) for still images. In this paper we present an intelligent system which is capable of restoring a compressed JPEG image by combining the knowledge extracted from the image domain and the transformed domain. It is based on probabilistic self-organizing maps and function approximation by kernel regression.