Backpropagation Neural Network Implementation for Medical Image Compression

Medical images require compression, before transmission or storage, due to constrained bandwidth and storage capacity. An ideal image compression system must yield high-quality compressed image with high compression ratio. In this paper, Haar wavelet transform and discrete cosine transform are consi...

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Bibliographic Details
Published in:Journal of Applied Mathematics 2013-01, Vol.2013 (2013), p.564-571-354
Main Author: Dimililer, Kamil
Format: Article
Language:English
Subjects:
Analysis
Compression ratio
Data compression
Diagnostic imaging
Image compression
Mathematical analysis
Medical
Neural networks
Optimization
Storage capacity
Technology application
Wavelet transforms
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Summary:Medical images require compression, before transmission or storage, due to constrained bandwidth and storage capacity. An ideal image compression system must yield high-quality compressed image with high compression ratio. In this paper, Haar wavelet transform and discrete cosine transform are considered and a neural network is trained to relate the X-ray image contents to their ideal compression method and their optimum compression ratio.
ISSN:1110-757X
1687-0042
DOI:10.1155/2013/453098