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 compres sed images from an original point of view. ANN's in particular are applied in order to detect the presence of blocking errors inside pre-processed pictures. To this purpose, a new local blockirtg 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 will also be presented.
Block Distortion Assessment for Image Compression Through ANNs
ANGUITA, DAVIDE;RIDELLA, SANDRO
1996-01-01
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 compres sed images from an original point of view. ANN's in particular are applied in order to detect the presence of blocking errors inside pre-processed pictures. To this purpose, a new local blockirtg 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 will also be presented.
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