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Proceedings Paper

Hyperspectral images lossless compression using the 3D binary EZW algorithm
Author(s): Kai-jen Cheng; Jeffrey Dill
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Paper Abstract

This paper presents a transform based lossless compression for hyperspectral images which is inspired by Shapiro (1993)’s EZW algorithm. The proposed compression method uses a hybrid transform which includes an integer Karhunrn-Loeve transform (KLT) and integer discrete wavelet transform (DWT). The integer KLT is employed to eliminate the presence of correlations among the bands of the hyperspectral image. The integer 2D discrete wavelet transform (DWT) is applied to eliminate the correlations in the spatial dimensions and produce wavelet coefficients. These coefficients are then coded by a proposed binary EZW algorithm. The binary EZW eliminates the subordinate pass of conventional EZW by coding residual values, and produces binary sequences. The binary EZW algorithm combines the merits of well-known EZW and SPIHT algorithms, and it is computationally simpler for lossless compression. The proposed method was applied to AVIRIS images and compared to other state-of-the-art image compression techniques. The results show that the proposed lossless image compression is more efficient and it also has higher compression ratio than other algorithms.

Paper Details

Date Published: 19 February 2013
PDF: 8 pages
Proc. SPIE 8655, Image Processing: Algorithms and Systems XI, 865515 (19 February 2013); doi: 10.1117/12.2002820
Show Author Affiliations
Kai-jen Cheng, Ohio Univ. (United States)
Jeffrey Dill, Ohio Univ. (United States)


Published in SPIE Proceedings Vol. 8655:
Image Processing: Algorithms and Systems XI
Karen O. Egiazarian; Sos S. Agaian; Atanas P. Gotchev, Editor(s)

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