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Proceedings Paper

Block distortion assessment for image compression through ANNs
Author(s): Davide Anguita; Ivano Barbieri; Filippo Passaggio; Sandro Ridella
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Paper Abstract

In this paper we propose a new method of image quality assessment for the evaluation of the block distortion through artificial neural networks (ANNs). The approach is new and intends to address the problem of the assessment of the visual quality of compressed images from an original point of view. ANNs in particular are applied in order to detect the presence of blocking errors inside pre-processed pictures. To this purpose, a new local blocking distortion parameter is introduced. Experiments and simulations, even if very preliminary, have confirmed the interest of the proposed approach. A complete formalization of the problem also is presented.

Paper Details

Date Published: 4 March 1996
PDF: 12 pages
Proc. SPIE 2664, Applications of Artificial Neural Networks in Image Processing, (4 March 1996);
Show Author Affiliations
Davide Anguita, Univ. di Genova (Italy)
Ivano Barbieri, Univ. di Genova (Italy)
Filippo Passaggio, Univ. di Genova (Italy)
Sandro Ridella, Univ. di Genova (Italy)

Published in SPIE Proceedings Vol. 2664:
Applications of Artificial Neural Networks in Image Processing
Nasser M. Nasrabadi; Aggelos K. Katsaggelos, Editor(s)

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