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作 者:郑晶晶[1,2] 方金云[1,2] 韩承德[1,2]
机构地区:[1]中国科学院计算技术研究所,北京100190 [2]中国科学院研究生院,北京100049
出 处:《高技术通讯》2009年第12期1238-1244,共7页Chinese High Technology Letters
基 金:973计划(2004CB318202)资助项目
摘 要:为减少网络地理信息系统(GIS)海量数字高程模型(DEM)数据的存储与传输数据量,提出了一种基于嵌入式小波编码的DEM快速无损压缩算法——FEC算法,此算法编解码快速,压缩位流具有分辨率嵌入、感兴趣区域嵌入和质量嵌入特点。对2/6可逆整数小波变换系数的每级分辨率数据按照区域划分分区,利用时空邻居关系挖掘每个分区子带的数据冗余,对其系数的每一个位面在一次扫描中完成三个子编码过程的系数建模重组与自适应二进制游程Golomb_Rice熵编码。实验数据表明,FFC算法与JPEG2000算法相比,编码、解码时间分别减少了36.04%和44.49%,而压缩比仅仅降低了8.05%;与SPIHT算法相比,编码、解码时间分别减少了32.28%和37.49%,而压缩比仅仅降低了4.58%;与GZIP算法相比,压缩比提高了79.63%;与n点最优预测算法相比,压缩比提高了9.23%。FEC算法在保持良好的压缩性能的同时,大幅度减少了编解码时间。To decrease the digital elevation model (DEM) data volume for storage and transmission in a net-geographic information system (GIS), a fast embedded compression (FEC) algorithm for DEM lossless compression is proposed. It has characteristics of resolution embedding, region of interest (ROI) embedding, and fidelity embedding, and its computing complexity is low. Every resolution of 2/6 integer wavelet transform coefficients is partitioned into many precincts accord- ing to the area. In each sub-band of each precinct, only the spatio-temporal neighborhood relationship is used to remove redundancies, and the bits of every bit-plane are modeled and reordered to form three sub-processes and ran-length encoded only in one pass. The adaptive Golomb Rice coding is used to entropy cede effectively. The experiments show that, compared with JPEG2000, FEC's encoding and decoding time decrease 36.04 % and 44.49 % respectively, while the compression ratio decreases only 8.05 % ; compared with SPIHT, FEC' s encoding and decoding time can decrease 32.28% and 37.49% respectively, while the compression ratio decreases only 4.58%; compared with GZIP, FEC's compression ratio increases 79.63 % ; compared with the n neighbors' prediction algorithm, FEC' s compression ratio increases 9.23 %. Thus, FEC can decrease the coding and decoding time largely, while maintains favorable compression performance.
关 键 词:数字高程模型(DEM) 无损压缩 地理信息系统(GIS) Golomb编码 小波编码
分 类 号:TP391.41[自动化与计算机技术—计算机应用技术] TP391.1[自动化与计算机技术—计算机科学与技术]
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