Parallel Compression Based on Prediction Algorithm of Hyper-spectral Imagery

Abstract

Along with the development of the spectral imaging technology, the precision of the hyper-spectral imagery becomes very high, and the size of the hyper-spectral imagery becomes very large. In order to solve the problem of the transmission and the storage, it is necessary to research the compression algorithm. The traditional prediction algorithm is adopted in the serial processing mode, and the processing time is long. In this paper, we improve the efficiency of the parallel prediction compression algorithm, to meet the needs of the rapid compression. We select bands along the direction of spectral or the direction of space, so that the hyper-spectral imagery can be divided into sub images. We number the sub images, then send them to different processing units. Each unit does compression tasks at the same time. This paper also compares the relationship between the processing unit number and the compression time. The experiment shows that, the parallel predictive compression algorithm can improve the efficiency of compression effectively.