An adaptive VQ method used on interferential multi-spectral image lossless compression

In this paper, a high efficient adaptive LBG VQ (vector quantization) method is proposed, which is an improved version of the expansion LBG VQ method [1] (proposed in 2009)and exploits the shortest distance from a point to line segment. Moreover, the proposed method is used on the lossless compression of LASIS (Large Aperture Static Imaging Spectrometer) interferential multi-spectral images. Compared with the expansion LBG VQ method proposed in 2009, the experimental results showed that the adaptive LBG VQ method improved the compression performance obviously. And the experiment also showed that when using these LBG VQ methods above without Dual-Direction Prediction [2], the entropy generated by expansion LBG VQ method [1] sometimes will be larger than that generated by traditional LBG VQ method [3], and when using these LBG VQ methods above after Dual-Direction Prediction [2], CR (compression ratio) generated by expansion LBG VQ method [1] sometimes will be less than that generated by traditional LBG VQ method [3], while the entropy generated by the method proposed in this paper will be much less than that generated by either traditional LBG VQ method [3] or the expansion LBG VQ method [1], and CR generated by the method proposed in this paper will be much larger than that generated by either traditional LBG VQ method [3] or the expansion LBG VQ method [1].