Lossless image compression of hyperspectral image using matlab
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Date
2017-06
Authors
Bernard Cheah Jun Kai
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Abstract
A Lossless Multispectral and Hyperspectral Image Compression standard (CCSDS-MHC) was issued by Consultative Committee for Space Data System (CCSDS), targeting to minimize the volume of digital data from three-dimensional (3D) hyperspectral image for remote sensingļ¼ losslessly. CCSDS aims to facilitate the inclusion of on-board compression in satellite by reducing transmission channel bandwidth utilization, time of data transmission and on-board storage requirement. In this research, a review of CCSDS-MHC is presented to understand and look for improvement of its performance. The performance in terms of execution time is evaluated for the first time in MATLAB R2016b software (MATLAB) on a desktop computer. This research aims to reduce CCSDS-MHC computational time using MATLAB software coding platform and expect the result to be better than the implementation of same code in Java software platform (NetBeans). Experimental result shows that Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) hyperspectral image could be compressed in 4 hours 4 minutes using MATLAB software whereas 9 minutes 26 seconds using NetBeans software. The compression of AVIRIS image achieves 25.8 times faster in NetBeans than the performance in MATLAB. Thus, MATLAB is not suitable to be used for the implementation of CCSDS-MHC in term of execution time.