Huffman decoding performance analysis of lossy compressed LAPAN-A3/IPB multispectral images

LAPAN-A3/IPB multispectral imager has the ability to produce realtime acquisition images anywhere in the world as long as there is X-band receiver in ground station to receive the image data. The received image data is the compressed version of the original image data, compressed by lossy algorithm of Fast-Fourier Transform and Huffman encoding. Processing of the received image data can be considered complicated in terms of decompressed image data validity and processing time needed. This research aims to develop robust decoding algorithm for LAPAN-A3/IPB multispectral image received in realtime acquisition mode from Bogor ground station. The research focuses on developing efficient method on Huffman decoding for relatively big image data by using look-up-table approach. The developed decoding algorithm has successfully produced daily LAPAN-A3/IPB realtime images with good image quality, where the results have been validated by using original images, recorded on satellite memory. However, the time processing needed for processing any single image is still poor, where 1 GB of compressed image data needs around 1 hour of processing time. Therefore, although the algorithm has been used to regularly produce daily LAPAN-A3/IPB realtime image data, the faster algorithm is needed to achieve better overall processing performance.