• Corpus ID: 118719159

Kernel PCA for Image Compression

@inproceedings{Huhle2006KernelPF,
  title={Kernel PCA for Image Compression},
  author={Benjamin Huhle},
  year={2006}
}
  • B. Huhle
  • Published 1 April 2006
  • Computer Science
Hiermit versichere ich, die vorliegende Arbeit selbständig verfasst und keine anderen als die angegebenen Quellen und Hilfsmittel verwendet zu haben. 

A hybrid randomized algorithm for image compression

In this paper, we present a randomized algorithm for image compression by improving the Markov chain Monte Carlo algorithm and by applying the principal component analysis method. Some Numerical

Lossless coding of hyperspectral images with principal polynomial analysis

It is found that reversible PPA performs worse than PCA due to the high impact of the rounding operation errors and to the amount of side information, and two generalizations are proposed: Backwards PPA, where polynomial estimations are performed in reverse order, and Double-Sided P PA, where more than a single dimension is used in the predictions.

Low-loss image compression techniques for cutting tool images: a comparative study of compression quality measures

This work accomplishes a comparative study between two distinct image compression techniques, namely the Lifting technique and the Principal Components Analysis (PCA), in order to determine what of

Low-loss image compression techniques for cutting tool images: a comparative study of compression quality measures DOI: 10.5585/exacta.v8i2.2000

This work accomplishes a comparative study between two distinct image compression techniques, namely the Lifting technique and the Principal Components Analysis (PCA), in order to determine what of

Spectral decorrelation for coding remote sensing data

Hoy en dia, los datos de teledeteccion son esenciales para muchas aplicaciones dirigidas a la observacion de la tierra. El potencial de los datos de teledeteccion en ofrecer informacion valiosa

References

SHOWING 1-10 OF 44 REFERENCES

Learning with kernels

This book is intended to be a guide to the art of self-consistency and should not be used as a substitute for a comprehensive guide to self-confidence.

Transform coding with backward adaptive updates

The Karhunen-Loeve transform (KLT) is optimal for transform coding of a Gaussian source. This is established for all scale-invariant quantizers, generalizing previous results. A backward adaptive

Information Theory, Inference, and Learning Algorithms

  • D. Mackay
  • Computer Science
    IEEE Transactions on Information Theory
  • 2004
Fun and exciting textbook on the mathematics underpinning the most dynamic areas of modern science and engineering.

Wavelet transforms in a JPEG-like image coder

The discrete wavelet transform is incorporated into the JPEG baseline coder for image coding. The discrete cosine transform is replaced by an association of two-channel filter banks connected

Iterative kernel principal component analysis for image modeling

A new iterative method for performing KPCA is proposed, the kernel Hebbian algorithm, which iteratively estimates the kernel principal components with only linear order memory complexity.

Analysis of low bit rate image transform coding

Calculations based on high-resolution quantizations prove that the distortion rate D(R) of an image transform coding is proportional to 2/sup -2R/ when R is large enough, and shows that the compression performance of an orthonormal basis depends mostly on its ability to approximate images with a few nonzero vectors.

Implicit Wiener Series for Higher-Order Image Analysis

First results show that image structures such as lines or corners can be predicted correctly, and that pixel interactions up to the order of five play an important role in natural images.

Suboptimality of the Karhunen-Loeve transform for transform coding

This paper shows that in both the fixed-rate and the variable-rate coding frameworks there exist sources for which the performance penalty for using a "worst" KLT can be made arbitrarily large, and demonstrates in both frameworks that even a best KLT gives suboptimal performance.

Suboptimality of the Karhunen-Loève Transform for Transform Coding

This paper shows that in both the fixed-rate and the variable-rate coding frameworks there exist sources for which the performance penalty for using a "worst" KLT can be made arbitrarily large, and demonstrates in both frameworks that even a best KLT gives suboptimal performance.

Embedded image coding using zerotrees of wavelet coefficients

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 of