A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Vector quantization and signal compression
Vector quantization and signal compression
Video and image processing in multimedia systems
Video and image processing in multimedia systems
Introduction to data compression (2nd ed.)
Introduction to data compression (2nd ed.)
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
DCC '00 Proceedings of the Conference on Data Compression
Embedded zerotree wavelet coding of multispectral images
ICIP '97 Proceedings of the 1997 International Conference on Image Processing (ICIP '97) 3-Volume Set-Volume 1 - Volume 1
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Optimal pruning with applications to tree-structured source coding and modeling
IEEE Transactions on Information Theory
Optimal bit allocation via the generalized BFOS algorithm
IEEE Transactions on Information Theory
Kronecker-product gain-shape vector quantization for multispectral and hyperspectral image coding
IEEE Transactions on Image Processing
Optimized quadtree for Karhunen-Loeve transform in multispectral image coding
IEEE Transactions on Image Processing
Compression of multispectral images by spectral classification and transform coding
IEEE Transactions on Image Processing
Image coding using wavelet transform
IEEE Transactions on Image Processing
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An effective and lossy compression technique for multispectral and hyperspectral image data minimizes both the spatial and spectral correlations while preserving the spectral characteristics of the data. In this paper, we combine wavelet transform and a variant of vector quantization for decorrelating both spatial and spectral information, and thus aim to achieve superior quality. We use 2-D wavelet transform followed by Kronecker-Product Gain-Shape Vector Quantization. This is coupled with the generalized BFOS for obtaining an optimal bit-rate. The pixels within the subbands of multi- and hyper-spectral images exhibit greater spectral redundancy which is thus exploited by designing multiresolution codebooks. Results are presented for multispectral and hyperspectral data taken from different sensors in different bands. The results obtained with our scheme are compared with other techniques designed for multi-/hyper-spectral image data and the Wavelet-based JPEG-2000. The computational requirement of the proposed technique is lower in comparison with other vector-quantization techniques.