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Video Compression Using Spiht and Neural Network

By Sangeeta Mishra and Sudhir Sawarkar

Abstract

Apart from the existing technology on image compression represented by series of JPEG, MPEG and H.26x standards, new technology such as neural networks and genetic algorithms are being developed to explore the future of image coding. Successful applications of neural networks to basic propagation algorithm have now become well established and other aspects of neural network involvement in this technology. In this paper different algorithms were implemented like gradient descent back propagation, gradient descent with momentum back propagation, gradient descent with adaptive learning back propagation, gradient descent with momentum and adaptive learning back propagation and Levenberg-Marquardt algorithm. The compression ratio obtained is 1.1737089:1. It was observed that the size remains same after compression but the difference is in the clarity

Topics: Macroblock, Neural Network, SPIHT
Year: 2014
OAI identifier: oai:CiteSeerX.psu:10.1.1.412.6930
Provided by: CiteSeerX
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