Paper
15 November 2007 Hyperspectral image compression using SPIHT based on DCT and DWT
Haiping Wei, Baojun Zhao, Peikun He
Author Affiliations +
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.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Haiping Wei, Baojun Zhao, and Peikun He "Hyperspectral image compression using SPIHT based on DCT and DWT", Proc. SPIE 6787, MIPPR 2007: Multispectral Image Processing, 67870H (15 November 2007); https://doi.org/10.1117/12.747874
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Cited by 6 scholarly publications.
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KEYWORDS
Image compression

Discrete wavelet transforms

Hyperspectral imaging

3D image reconstruction

Computer programming

Wavelets

Infrared imaging

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