Hyperspectral image compression using low complexity integer KLT and three-dimensional asymmetric significance tree

2009 ◽  
Author(s):  
Jing Huang ◽  
Rihong Zhu
Keyword(s):  
Image Compression ◽  
Hyperspectral Image ◽  
Three Dimensional ◽  
Low Complexity ◽  
Hyperspectral Image Compression

Low-Complexity Approaches for Lossless and Near-Lossless Hyperspectral Image Compression

2011 ◽  
pp. 47-65
Author(s):  
Andrea Abrardo ◽  
Mauro Barni ◽  
Andrea Bertoli ◽  
Raoul Grimoldi ◽  
Enrico Magli ◽  
...  
Keyword(s):  
Image Compression ◽  
Hyperspectral Image ◽  
Low Complexity ◽  
Hyperspectral Image Compression

The Application of Vector Quantization Algorithm in Hyperspectral Image Compression

2013 ◽  
Vol 756-759 ◽  
pp. 1479-1483
Author(s):  
Xue Jun Zhao ◽  
Yuan Fei Jing
Keyword(s):  
Remote Sensing ◽  
Image Compression ◽  
Vector Quantization ◽  
Data Transmission ◽  
Hyperspectral Image ◽  
Three Dimensional ◽  
Compression Method ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Hyperspectral Image Compression

With the development of Aerospace remote sensing technology, the hyperspectral remote sensing technology is widely applied in earth resources detection, environment investigation and military reconnaissance, etc. It is different from multispectral image, hyperspectral image spectrum period is as many as dozens to hundreds of band, with high resolution, large amount of data, corresponding to the data transmission problem, so the hyperspectral image compression is become necessary. In this paper the vector quantization algorithm is applied for hyperspectral image compression, first convert the three dimensional hyperspectral images into two dimensional pixel vectors, and then applied the vector quantization on the transformed pixel vectors. The experimental results show that the algorithm not only has better compression ratio, and can effectively save image spectrum section characteristics, which is a kind of efficient three-dimensional compression method.

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