Özet
In preceding paper, a compression algorithm for hyperspectral images using a novel multivariate data decomposition method called Enhanced Multivariance Products Representation (EMPR) is developed. The test results obtained by performing some EMPR approximations of different orders and their qualities are reported. In order to improve performance, EMPR approach is applied to high-subband of hyperspectral data which is spectrally decorrelated using Haar wavelet transform. Low subbands are losslessly compressed using JPEG2000 Proposed methods are tested with AVIRIS data, promising compression vs. Peak-Signal-to-Noise Ratios (PSNR) are obtained.
Tercüme edilen katkı başlığı | Lossy compression of hyperspectral images by using Enhanced Multivariance Products Representation (EMPR) method |
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Orijinal dil | Türkçe |
Ana bilgisayar yayını başlığı | 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings |
Yayınlayan | Institute of Electrical and Electronics Engineers Inc. |
Sayfalar | 1925-1928 |
Sayfa sayısı | 4 |
ISBN (Elektronik) | 9781509016792 |
DOI'lar | |
Yayın durumu | Yayınlandı - 20 Haz 2016 |
Etkinlik | 24th Signal Processing and Communication Application Conference, SIU 2016 - Zonguldak, Turkey Süre: 16 May 2016 → 19 May 2016 |
Yayın serisi
Adı | 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings |
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???event.eventtypes.event.conference??? | 24th Signal Processing and Communication Application Conference, SIU 2016 |
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Ülke/Bölge | Turkey |
Şehir | Zonguldak |
Periyot | 16/05/16 → 19/05/16 |
Bibliyografik not
Publisher Copyright:© 2016 IEEE.
Keywords
- Compression
- Decomposition
- Enhanced Multivariance Products Representation
- Haar Wavelet
- Hyperspectral Image