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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yan Feng Jiakai Lv Jinshan Su |
| Copyright Year | 2009 |
| Description | Author affiliation: College of Physics and Electronic Information, I LI Normal University, Yining, China (Jinshan Su) || School of Electronics and Information, Northwestern Polytechnical University, NPU, Xi'an, China (Yan Feng; Jiakai Lv) |
| Abstract | This paper proposes a dimensionality reduction and compression method of hyperspectral images based on independent component analysis(ICA) and mixed contourlet and wavelet transform (MCWT) for hyperspectral image analysis. At first, the spectral correlations of hyperspectral images are removed using ICA and dimensionality reduction is accomplished. Then, dimensionality reduction images are compressed by MCWT and set partitioning in hierarchical trees(SPIHT)-like coder. The experimental results by using 64 band hyperspectral data show that the proposed compression method preserves more spacial detail information and spectral features of hyperspectral images and achieves higher peak signal-to-noise ratio at high compression ratio than the compression method based on principal component analysis and wavelet transform. |
| Starting Page | 3843 |
| Ending Page | 3847 |
| File Size | 586403 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781424427994 |
| DOI | 10.1109/ICIEA.2009.5138926 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-05-25 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Image coding Hyperspectral sensors Hyperspectral imaging Remote sensing Independent component analysis Wavelet analysis Wavelet transforms Image analysis PSNR Principal component analysis SPIHT hyperspectral image compression independent component analysis contourlet transform wavelet transforn |
| Content Type | Text |
| Resource Type | Article |
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