An adaptive OPD and dislocation prediction used characteristic of interference pattern for interference hyperspectral image compression

According to the imaging principle and characteristic of LASIS (Large Aperture Static Interference Imaging Spectrometer), we discovered that the 3D (three dimensional) image sequences formed by different interference pattern frames, which were formed in the imaging process of LASIS Interference hyperspectral image, had much stronger correlation than the original interference hyperspectral image sequences, either in 2D (two dimensional) spatial domain or in the spectral domain. We put this characteristic into image compression and proposed an adaptive OPD (optical path difference) and dislocation prediction algorithm for interference hyperspectral image compression. Compared the new algorithm proposed in this paper with Dual-Direction Prediction [1] proposed in 2009, lots of experimental results showed that the prediction error entropy of the new algorithm was much smaller. In the prediction step of lifting wavelet transform, this characteristic would also reduce the entropy of coefficients in high frequency significantly, which would be more advantageous for quantification coding [2].