Compression of Hyperspectral Image Based on Independent Component Analysis
基于独立分量分析的高光谱图像压缩

Based on the estimation of virtual dimensionality,a lossy compression method using independent component analysis(ICA) with given initial projection vectors is proposed.Endmember vectors are extracted using distance maximization method.Fast ICA is used and the ICA images are coded using 2-D set partitioning in hierarchical trees(SPIHT).The experimental results show that the algorithm is an efficient method.High compression ratio is achieved and the spectral characteristics are preserved.