Image compression using auto-associative neural network and embedded zero-tree coding

@article{Patnaik2001ImageCU,
  title={Image compression using auto-associative neural network and embedded zero-tree coding},
  author={S. Patnaik and R. Pal},
  journal={2001 IEEE Third Workshop on Signal Processing Advances in Wireless Communications (SPAWC'01). Workshop Proceedings (Cat. No.01EX471)},
  year={2001},
  pages={388-390}
}
  • S. Patnaik, R. Pal
  • Published 2001
  • Mathematics
  • 2001 IEEE Third Workshop on Signal Processing Advances in Wireless Communications (SPAWC'01). Workshop Proceedings (Cat. No.01EX471)
This paper presents an image compression method using auto-associative neural network and embedded zero-tree coding. The role of the neural network (NN) is to decompose the image stage by stage, which enables analysis similar to wavelet decomposition. This works on the principle of principal component extraction (PCE). Network training is achieved through a recursive least squares (RLS) algorithm. The coefficients are arranged in a four-quadrant sub-band structure. The zero-tree coding… Expand

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References

SHOWING 1-4 OF 4 REFERENCES
Embedded image coding using zerotrees of wavelet coefficients
  • J. M. Shapiro
  • Mathematics, Computer Science
  • IEEE Trans. Signal Process.
  • 1993
The embedded zerotree wavelet algorithm (EZW) is a simple, yet remarkably effective, image compression algorithm, having the property that the bits in the bit stream are generated in order ofExpand
Principal component extraction using recursive least squares learning
TLDR
A new neural network-based approach is introduced for recursive computation of the principal components of a stationary vector stochastic process and the application of this learning algorithm to image data reduction and filtering of images degraded by additive and/or multiplicative noise is considered. Expand
Robust recursive least squares learning algorithm for principal component analysis
TLDR
It is shown that all information needed for PCA can be completely represented by the unnormalized weight vector which is updated based only on the corresponding neuron input-output product. Expand
A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
  • S. Mallat
  • Computer Science, Mathematics
  • IEEE Trans. Pattern Anal. Mach. Intell.
  • 1989
TLDR
It is shown that the difference of information between the approximation of a signal at the resolutions 2/sup j+1/ and 2/Sup j/ can be extracted by decomposing this signal on a wavelet orthonormal basis of L/sup 2/(R/sup n/), the vector space of measurable, square-integrable n-dimensional functions. Expand