Title
Lossy compression of hyperspectral images using shearlet transform and 3D SPECK Lossy compression of hyperspectral images using shearlet transform and 3D SPECK
Author
Faculty/Department
Faculty of Sciences. Physics
Publication type
conferenceObject
Publication
Bellingham :Spie-int soc optical engineering ,
Subject
Economics
Physics
Engineering sciences. Technology
Source (journal)
IMAGE AND SIGNAL PROCESSING FOR REMOTE SENSING XXI
Source (book)
Conference on Image and Signal Processing for Remote Sensing XXI, SEP 21-23, 2015, Toulouse, FRANCE
Volume/pages
9643(2015) , 6 p.
ISSN
0277-786X
Article Reference
UNSP 96431J
ISBN
978-1-62841-853-8
ISI
000367469500052
Carrier
E-only publicatie
Target language
English (eng)
Full text (Publishers DOI)
Affiliation
University of Antwerp
Abstract
In this paper, a new lossy compression method for hyperspectral images (HSI) is introduced. HSI are considered as a 3D dataset with two dimensions in the spatial and one dimension in the spectral domain. In the proposed method, first 3D multidirectional anisotropic shearlet transform is applied to the HSI. Because, unlike traditional wavelets, shearlets are theoretically optimal in representing images with edges and other geometrical features. Second, soft thresholding method is applied to the shearlet transform coefficients and finally the modi fied coefficients are encoded using Three Dimensional-Set Partitioned Embedded bloCK (3D SPECK). Our simulation results show that the proposed method, in comparison with well-known approaches such as 3D SPECK (using 3D wavelet) and combined PCA and JPEG2000 algorithms, provides a higher SNR (signal to noise ratio) for any given compression ratio (CR). It is noteworthy to mention that the superiority of proposed method method is distinguishable as the value of CR grows. In addition, the effect of proposed method on the spectral unmixing analysis is also evaluated.
E-info
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