Çokdegiskenliligi Yükseltilmis Çarpimlar Gösterimi (ÇYÇG) yöntemi ile hiperspektral görüntülerin kayipli sikistirilmasi

Aleksei Sukhanov, Suha Tuna, Behcet Ugur Toreyin

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde BölümKonferans katkısıbilirkişi

4 Atıf (Scopus)

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 başlığıLossy compression of hyperspectral images by using Enhanced Multivariance Products Representation (EMPR) method
Orijinal dilTürkçe
Ana bilgisayar yayını başlığı2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings
YayınlayanInstitute of Electrical and Electronics Engineers Inc.
Sayfalar1925-1928
Sayfa sayısı4
ISBN (Elektronik)9781509016792
DOI'lar
Yayın durumuYayınlandı - 20 Haz 2016
Etkinlik24th Signal Processing and Communication Application Conference, SIU 2016 - Zonguldak, Turkey
Süre: 16 May 201619 May 2016

Yayın serisi

Adı2016 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
Ülke/BölgeTurkey
ŞehirZonguldak
Periyot16/05/1619/05/16

Bibliyografik not

Publisher Copyright:
© 2016 IEEE.

Keywords

  • Compression
  • Decomposition
  • Enhanced Multivariance Products Representation
  • Haar Wavelet
  • Hyperspectral Image

Parmak izi

Çokdegiskenliligi Yükseltilmis Çarpimlar Gösterimi (ÇYÇG) yöntemi ile hiperspektral görüntülerin kayipli sikistirilmasi' araştırma başlıklarına git. Birlikte benzersiz bir parmak izi oluştururlar.

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