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Lossless image compression of hyperspectral image using matlab

Lossless image compression of hyperspectral image using matlab / Bernard Cheah Jun Kai
Piawaian Proses Pemampatan Tak Hilang Hyperspectral Imej (CCSDS-MHC) telah ditetapkan oleh Consultative Committee for Space Data System (CCSDS) dengan tujuan untuk mengurangkan jumlah isi padu data digital dalam imej hyperspectral. Matlamat muktamad CCSDS menetap piawaian ini adalah untuk memudahkan pelaksanaan CCSDS-MHC di satelit yang dapat mengurangkan penggunaan jalur lebar sistem penghantaran, masa penghantaran dan juga keperluan jumlah ruang simpanan untuk imej data. Dalam laporan penyelidikan ini, kami mengkaji semula dan membuat semakan tentang CCSDS-MHC untuk lebih memahami algorithm tersebut. Penilaian prestasi proses mampatan CCSDS-MHC dari segi masa pelaksanaannya telah dinilai dalam MATLAB R2016b (MATLAB) buat kali pertama dengan desktop. Penilaian ini bertujuan untuk mengurangkan masa pengiraan dalam MATLAB dan mengatasi keputusannya dalam Java software platform (NetBeans). Keputusan eksperimen menunjukkan bahawa pemampatan imej dengan imej hyperspectral dalam perisian MATLAB mengambil masa 4 jam 4 minit malahan perisian NetBeans menggunakan masa 9 minit 26 saat. NetBeans memcatat prestasinya 25.8 kali ganda lebih cepat berbanding dengan MATLAB. Oleh demikian, pelaksanaan CCSDS-MHC dalam MATLAB adalah tidak sesuai di satelit. _______________________________________________________________________________________________________ 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 sensing, 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.
Contributor(s):
Bernard Cheah Jun Kai - Author
Primary Item Type:
Final Year Project
Identifiers:
Accession Number : 875007244
Barcode : 00003107124
Language:
English
Subject Keywords:
Lossless Multispectral and Hyperspectral Image Compression standard; digital data; satellite
First presented to the public:
6/1/2017
Original Publication Date:
4/17/2018
Previously Published By:
Universiti Sains Malaysia
Place Of Publication:
School of Electrical & Electronic Engineering
Citation:
Extents:
Number of Pages - 76
License Grantor / Date Granted:
  / ( View License )
Date Deposited
2018-04-17 09:44:55.908
Date Last Updated
2019-01-07 11:24:32.9118
Submitter:
Mohd Jasnizam Mohd Salleh

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