Abstract:
We present a neural network visual model (NNVM) which extracts multi-scale edge features from the decompressed image and uses these visual features as input to estimate a...Show MoreMetadata
Abstract:
We present a neural network visual model (NNVM) which extracts multi-scale edge features from the decompressed image and uses these visual features as input to estimate and compensate the coding distortions. Our approach is a generic postprocessing technique and can be applied to all the main coding methods. Experimental results involving post-processing four coding systems show that the NNVM significantly improves the quality of reconstructed images, both in terms of the objective peak signal to noise ratio and subjective visual assessment.
Published in: Neural Networks for Signal Processing VIII. Proceedings of the 1998 IEEE Signal Processing Society Workshop (Cat. No.98TH8378)
Date of Conference: 02-02 September 1998
Date Added to IEEE Xplore: 06 August 2002
Print ISBN:0-7803-5060-X
Print ISSN: 1089-3555