Compression of Hyperspectral Images using Adaptive Luminance Transform

被引：0

作者：

Can, Ergun ^{[1
]}

Karaca, Ali Can ^{[2
]}

Danisman, Mehmetali ^{[2
]}

Urhan, Oguzhan ^{[2
]}

Gullu, M. Kemal ^{[2
]}

机构：

[1] Piri Reis Univ, Elekt Elekt Muhendisligi, Istanbul, Turkey

[2] Kocaeli Univ, Elekt & Haberlesme Muhendisligi, Kocaeli, Turkey

来源：

2018 26TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU) | 2018年

关键词：

Luminance transform; correlation matrix; 3D-DCT;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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.

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页数：4

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