Vector quantization and signal compression
Vector quantization and signal compression
JPEG 2000: Image Compression Fundamentals, Standards and Practice
JPEG 2000: Image Compression Fundamentals, Standards and Practice
Optimal bit allocation for biorthogonal wavelet coding
DCC '96 Proceedings of the Conference on Data Compression
On-Board Compression Algorithm for Satellite Multispectral Images
DCC '06 Proceedings of the Data Compression Conference
Low-Complexity Principal Component Analysis for Hyperspectral Image Compression
International Journal of High Performance Computing Applications
Lossy Hyperspectral Images Coding with Exogenous Quasi Optimal Transforms
DCC '09 Proceedings of the 2009 Data Compression Conference
Compression of multicomponent satellite images using independent components analysis
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
Fast algorithms for mutual information based independent component analysis
IEEE Transactions on Signal Processing - Part I
Analysis of low bit rate image transform coding
IEEE Transactions on Signal Processing
IEEE Transactions on Information Theory
Transform coding with backward adaptive updates
IEEE Transactions on Information Theory
Suboptimality of the Karhunen-Loeve transform for transform coding
IEEE Transactions on Information Theory
High performance scalable image compression with EBCOT
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Image coding using wavelet transform
IEEE Transactions on Image Processing
A filter based bit allocation scheme for subband compression of HDTV
IEEE Transactions on Image Processing
A new, fast, and efficient image codec based on set partitioning in hierarchical trees
IEEE Transactions on Circuits and Systems for Video Technology
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It is well known in transform coding, that the Karhunen-Loeve transform (KLT) is optimal only for Gaussian sources. However, in many applications using JPEG2000 Part 2 codecs, the KLT is generally considered as the optimal linear transform for reducing redundancies between components of multicomponent images. In this paper we present the criterion satisfied by an optimal transform of a JPEG2000 compatible compression scheme, under high resolution quantization hypothesis and without the Gaussianity assumption. We also introduce two variants of the compression scheme and the associated criteria minimized by optimal transforms. Then we give two algorithms, derived of the Independent Component Analysis algorithm ICAinf, that compute the optimal transform, one under the orthogonality constraint and the other without no constraint but invertibility. The computational complexity of the algorithms is evaluated. Finally, comparisons with the KLT are presented on hyperspectral and multispectral satellite images with different measures of distortion, as it is recommended for evaluating the performances of the codec in applications (like classification and target detection). For hyperspectral images, we observe a little but significant gain at medium and high bit-rates of the optimal transforms compared to the KLT. The actual drawback of the optimal transforms is their heavy computational complexity.