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[5] X. Tang, S. Cho, and W. A. Pearlman, “3D set partition-ing coding methods in hyperspectral image compres-sion,” in the Proceedings of IEEE International Confer-ence on Image Processing, pp. 239-242, September 2003.

has been cited by the following article:

• TITLE: Lossy-to-Lossless Compression of Hyperspectral Image Using the 3D Set Partitioned Embedded ZeroBlock Coding Algorithm

  AUTHORS: Ying Hou

  KEYWORDS: Image Compression, Hyperspectral Image, 3D Wavelet Packet Transforms, Zeroblock Coding

  JOURNAL NAME: Journal of Software Engineering and Applications, Vol.2 No.2, July 15, 2009

  ABSTRACT: In this paper, we propose a three-dimensional Set Partitioned Embedded ZeroBlock Coding (3D SPEZBC) lossy-to-lossless compression algorithm for hyperspectral image which is an improved three-dimensional Embedded ZeroBlock Coding (3D EZBC) algorithm. The algorithm adopts the 3D integer wavelet packet transform proposed by Xiong et al. to decorrelate, the set-based partitioning zeroblock coding to process bitplane coding and the con-text-based adaptive arithmetic coding for further entropy coding. The theoretical analysis and experimental results demonstrate that 3D SPEZBC not only provides the same excellent compression performances as 3D EZBC, but also reduces the memory requirement compared with 3D EZBC. For achieving good coding performance, the diverse wave-let filters and unitary scaling factors are compared and evaluated, and the best choices were given. In comparison with several state-of-the-art wavelet coding algorithms, the proposed algorithm provides better compression performance and unsupervised classification accuracy.