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Video Compression Algorithm Based on Neural Network Structures

Authors :
Nimit Shah
Michał Knop
Robert Cierniak
Source :
Artificial Intelligence and Soft Computing ISBN: 9783319071725, ICAISC (1)
Publication Year :
2014
Publisher :
Springer International Publishing, 2014.

Abstract

The presented here paper describes a new approach to the video compression problem. Our method uses the neural network image compression algorithm which is based on the predictive vector quantization (PVQ). In this method of image compression two different neural network structures are exploited in the following elements of the proposed system: a competitive neural networks quantizer and a neuronal predictor. For the image compression based on this approach it is important to correctly detect scene changes in order to improve performance of the algorithm. We describe the image correlation method and discuss its effectiveness.

Details

ISBN :
978-3-319-07172-5
ISBNs :
9783319071725
Database :
OpenAIRE
Journal :
Artificial Intelligence and Soft Computing ISBN: 9783319071725, ICAISC (1)
Accession number :
edsair.doi...........28466807de090a3632e9f8b5bd0f1d12
Full Text :
https://doi.org/10.1007/978-3-319-07173-2_61