STUDY ON REAL-TIME LOSSLESS DATA COMPRESSION FOR REMOTE SENSING IMAGES
遥感图像数据实时无失真压缩的研究

The paper describes a real-time lossless data compression algorithm for both individual band and multi-spectral remote sensing images. This approach uses prediction to reduce the redundancy and classical Huffman coding to reduce the average code length. Several kinds of predictions were studied and the 2-D prediction was selected. Some simplifications were taken in the Huffman coding for real-time use. A comparison between the coding methods was discussed. The scheme was applied to the 8 bits/pixel, original images of LANDSAT TM, SPOT HRV, AIR SAR and imaging spectrometer by software emulation. An average compression ratio of 2, with the highest value of 3.1 and the lowest value of 1.2 for the radar images, was achieved.