Application of Hybrid Back Propagation Neural Network in Image Compression

A new hybrid neural network is showed in this paper for image compression, in which the hybrid genetic algorithm and BP algorithm approach are used to train the weight vector. The essence of the hybrid neural network in this paper is a feed-forward artificial neural network. It uses the hybrid intel...

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Bibliographic Details
Published in2015 8th International Conference on Intelligent Computation Technology and Automation (ICICTA) pp. 209 - 212
Main Author Jia Wei
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2015
Subjects
Artificial neural networks
Biological neural networks
BP algorithm
Convergence
genetic algorithm
Genetic algorithms
Image coding
image compression
neural network
Signal processing algorithms
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Summary:A new hybrid neural network is showed in this paper for image compression, in which the hybrid genetic algorithm and BP algorithm approach are used to train the weight vector. The essence of the hybrid neural network in this paper is a feed-forward artificial neural network. It uses the hybrid intelligent learning algorithm for training. The advantage of genetic algorithm is the parallel search and high search efficiency. So its convergent speed and precision are improved greatly. The results of this method show high compression ratio, high ratio of signal vs. noise, low errors of coding, high decoding speed and fine resuming effect on subject.
DOI:10.1109/ICICTA.2015.60