Lossless Compression of MODIS Data Based on the Maximum Spanning Tree and 3D Context Prediction

摘要：

MODIS data Is increasingly important for oceanographk, terrestrial, and atmospheric science observation. Because of the high data rate, the lossless data compression becomes vital for MODE data transmission and storage .In this paper we present a new approach for lossless compression of MODIS data based on the maximum spanning tree and 3D context prediction. First we determine the prediction sequence uskig the maximum spanning tree derived from the inter-band correlation coefficient matrix, then the three dimensional context prediction method is performed. At last the reference band and residual bands are compressed using JPEG-LS. Experimental results show that our method outperforms WinRAR and JPEG-LS.

关键词： lossless compression maximum spanning tree 3D prediction correlation band ordering

作者: YunXian HUANG Xiang LI WeiHua AI

作者单位: Institute of Meteorology, PLA University of Science & Technology Nanjing, China

会议类型: 国际会议

会议名称: 2011 Fourth International Conference on Intelligent Computation Technology and Automation(2011年第四届智能计算技术与自动化国际会议 ICICTA 2011)

会议地点: 深圳

会议语种:英文

页码: 596-599

在线出版日期: 2011-03-28（万方平台首次上网日期，不代表论文的发表时间）