
Time Optimization for Lossy Decompression of the LISA Sensor Data on LAPAN A3 Satellite Using a Grouping Method of HUFFMAN Code Bit Number
Author(s) -
Suhermanto M.T
Publication year - 2018
Publication title -
jurnal teknologi dirgantara/jurnal teknologi dirgantara
Language(s) - English
Resource type - Journals
eISSN - 2597-7849
pISSN - 1412-8063
DOI - 10.30536/j.jtd.2018.v16.a2960
Subject(s) - huffman coding , computer science , lossy compression , data compression , canonical huffman code , algorithm , computer hardware , real time computing , decoding methods , artificial intelligence , code rate , systematic code
The LAPAN-A3 satellite provides compressed multispectral data from LISA sensor using real-time lossy compression. The compression of the multispectral data of radiometric resolution 12bit/pixel is built from the Fourier transform and the use of Huffman decoder 514 binary length code. A problem arised in the data extraction process, that decompression performance is very slow because the search method of code value in Hufman table was done sequentially from one bit to the next bit in one block of data along 4000 pixels. The data extraction time for one scene in 12 minutes acquisition duration (one full path) takes up to 20 hours. This paper proposes a method of improving the LISA real-time lossy data decompression algorithm using the grouping method of bit code on the Huffman decoding algorithm and using pointer for reading data in the buffer memory. Using this method, the searching process of bit code for all characters in the Huffman decoder algorithm is done regularly, so the search processing time is significantly reduced. The performance test used 6 data samples. The result showed that extraction time has an average of 14 times faster. The lossy compression ratio is still in accordance with the design specification of LISA sensor that is less than 4 times and the appearance of the special character is very small i.e. less than 0.5%.