Sparse coding of hyperspectral imagery using online learning


Ulku I., Toreyin B. U.

SIGNAL IMAGE AND VIDEO PROCESSING, cilt.9, sa.4, ss.959-966, 2015 (SCI İndekslerine Giren Dergi) identifier identifier

  • Cilt numarası: 9 Konu: 4
  • Basım Tarihi: 2015
  • Doi Numarası: 10.1007/s11760-015-0753-9
  • Dergi Adı: SIGNAL IMAGE AND VIDEO PROCESSING
  • Sayfa Sayıları: ss.959-966

Özet

Sparse coding ensures to express the data in terms of a few nonzero dictionary elements. Since the data size is large for hyperspectral imagery, it is reasonable to use sparse coding for compression of hyperspectral images. In this paper, a hyperspectral image compression method is proposed using a discriminative online learning-based sparse coding algorithm. Compression and anomaly detection tests are performed on hyperspectral images from the AVIRIS dataset. Comparative rate-distortion analyses indicate that the proposed method is superior to the state-of-the-art hyperspectral compression techniques.