Hyper-spectral remote sensing image is a three-dimensional image, that is, add one-dimensional spectral information to the two-dimensional images, which make the Hyper-spectral images have a larger number of spectral channels, as well as high spatial resolution and high spectral resolution.

On Remote Sensing Hyper-spectral Image Compression Based on SPIHT Algorithm;

An effective and lossy compression algorithm of multispectral remote sensing images was proposed.

To avoid different results with the uncertainty of thresholds in classification of hyperspectral image,this paper presents a new approach to object identification based on the exhaustive method(EXM).

Each pixel spectrum in the hyperspectral imagery has an optimal matching spectrum selected from all possible reference spectra that are correlated with the study area.

For the problem of target detection and classification with remote sensing hyperspectral image,though analysis the traditionary binary coding method,a new binary coding method and the relevant spectral matching algorithm is given in this paper.

Research advances and analysis of hyperspectral remote sensing image band selection;

A compression algorithm of hyperspectral remote sensing image based on lifting scheme;

A compression algorithm of hyperspectral remote sensing image based on vector quantization;

A novel error compensated prediction tree method used for lossless compression of multispectral imagery is proposed in this paper.