Compression of hyperspectral images using adaptive luminance transform
Ergün Can, Ali Can Karaca, Mehmetali Danisman, Oğuzhan Urhan, M. Kemal Güllü · 2018
In this paper, compression of hyperspectral images with luminance transform is explained. First, similar image bands are grouped on hyperspectral image and luminance transform is performed independently on these groups. After luminance transform, compression is carried out by using discrete cosine transform (3D-DCT), quantization and entropy coding, for each group. In experimental studies, compression performances are measured using signal-to-noise ratio and bit rates. The proposed method increases signal-to-noise ratio 10 dB at 0.1 bit-per-pixel compared to 3D-DCT based compression.