The authors propose an efficient compression algorithm for hyperspectral images, which is based on the correlation coefficients adaptive asymmetric tree three-dimensional (3d) set partitioning in hierarchical trees (A...
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The authors propose an efficient compression algorithm for hyperspectral images, which is based on the correlation coefficients adaptive asymmetric tree three-dimensional (3d) set partitioning in hierarchical trees (AT-3dSPIHT) coding of the asymmetric 3d wavelet transform (A3d-dWT) coefficients. According to the characteristics of the correlation coefficients between adjacent spectral bands, a binary tree spectral band grouping algorithm is carried out to divide the adjacent spectral bands into different mode groups. Along with this, an appropriate A3d-dWT with the corresponding decomposition levels and a proper AT-3dzerotree are determinedadaptively. Several airborne visible/infrared imaging spectrometer images are used to evaluate the proposed algorithm. Compared with the state-of-the-art 3d-dWT based algorithms, the proposedadaptive AT-3dSPIHT achieves the best compression performance at lower bit rates. Moreover, at the low correlated adjacent bands, the proposed algorithm also outperforms the 2dSPIHT algorithm.
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