15 November 2007 Hyperspectral image compression using SPIHT based on DCT and DWT
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Proceedings Volume 6787, MIPPR 2007: Multispectral Image Processing; 67870H (2007) https://doi.org/10.1117/12.747874
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China
Abstract
In this paper, an algorithm for hyperspectral image compression is presented. It carries DCT (Discrete Cosine Transform) on spectral bands to exploit the spectral correlation and then DWT (Discrete Wavelet Transform) on every eigen image to exploit the spatial correlation. After that, 3D-SPIHT (three-dimensional Set Partitioning in Hierarchical Trees) is performed for encoding. Experiments were done on the OMIS-I (Operational Modular Imaging Spectrometer) image and the performance of this algorithm was compared with that of 2D-SPIHT. The results show that the performance of 3D-SPIHT based on DCT and DWT is much better than that of 2D-SPIHT and the quality of the reconstructed images is satisfying.
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Haiping Wei, Haiping Wei, Baojun Zhao, Baojun Zhao, Peikun He, Peikun He, } "Hyperspectral image compression using SPIHT based on DCT and DWT", Proc. SPIE 6787, MIPPR 2007: Multispectral Image Processing, 67870H (15 November 2007); doi: 10.1117/12.747874; https://doi.org/10.1117/12.747874
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