Lossless compression of hyperspectral imagery by IPCT and 3-D Tarp coder

Based on the factorization of transform matrix in triangular elementary reversible matrices (TERM), an integer approximation algorithm of the principal component transform (IPCT) was proposed. The pivoting method of TERM factorization was improved in order to obtain limited error and enhance computational efficiency. And a new lossless compression algorithm for hyperspectral imagery was developed by combining the perfectly reversible integer PCT with the 3-D Tarp coder. After an integer wavelet transform was applied in spatial domain, the improved IPCT was used as the inter-band decorrelating transform. In coding stage the novel 3-D Tarp coder allows probability estimation with five simple recursive filters. And this probability estimate can be used to drive a non-adaptive arithmetic coder to entropy code significance-map and refinement information of transformed coefficients. The main advantage of our compression algorithm is of low complexity and it can yield embedded bitstreams with higher compression ratios compared with the existing algorithms.