Compression of multispectral images by three-dimensional SPIHT algorithm

By Pier Luigi Dragotti, Giovanni Poggi, Arturo R. P. Ragozini. IEEE Transactions on Geoscience and Remote Sensing, 2000

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Transform Coding Techniques for Lossy Hyperspectral Data Compression (2007, methodology): “In [12], vector quantization and spectral KLT are employed to exploit the correlation between multispectral bands.”
Kronecker Compressive Sensing (2012, methodology): “However , they rely on linear low-dimensional approximations rather than nonlin ear sparse representations [17, 38, 39]; thus, the approaches are more data-dependent and more difficult to gene ralize among different datasets.”
Denoising and Dimensionality Reduction Using Multilinear Tools for Hyperspectral Images (2008, background): “Hence, instead of adapting data to classical matrix-based techniques, the 3-D representation has proven its usefulness for compression applications [11], [12].”