第21卷第8期
2013年8月文章编号
1004-924X(2013)08-2095-08
光学精密工程
Optics and Precision Engineering
Vol., 21No,8
Aug.2013
基于快速方向预测的高分辨率遥感影像压缩
张立保1.2*，丘兵昌1
（1.北京师范大学信息科学与技术学院，北京100875； 2.北京师范大学遥感科学国家重点实验室，北京100875）
摘要：针对传统的自适应方向提升小波变换（ADL-DWT)算法在高分辨率遥感影像压缩中计算复杂度过高的问题，提出一种新的基于方向预测的提升小波变换(DP-LWT)算法，实现了高分辨率遥感影像的快速、高效压缩。新算法首先将高分辨率遥感影像分为若干不重叠子块，然后采用梯度算子快速预测温感影像中每个图像块的最佳提升方向，并沿着最佳预测方向插值完成方向提升小波变换，最后进行多级树集合分裂(SPIHT)编码。实验结果表明，新算法有效削弱了遥感影像各子带中非水平与非垂直方向的高频系数；与传统自适应方向提升小波变换相比，在重建高分辨率遥感影像峰值信
噪比基本相同的情况下，有效减少了小波变换中方向预测的计算复杂度。关键调：遂感图像处理；图像压编；小波变换；自速应方向提升；方向预测
中图分类号：TP752;TP391
文献标识码：A
doi;10,3788/OPE,20132108.2095
Remotesensingimage compressionbasedonfastdirectionprediction
ZHANG Li-bao"-2·，QIU Bing-chang
(1.College of Information Science and Technology,Beijing Normal University，Beijing 100875,China; 2.StateKey Laboratory of RemoteSensing ScienceBeijingNormal Unitersity,Beijing 100875,China)
Correspondingauthor,E-mail;libaozhang@163.com
Abstract: As traditional Adaptive Direction Lifting based-Discrete Wavelet Transform(ADL-DWT) has higher computational complexity in the compression of high-resolution remote sensing images, this paper proposes a new lifting wavelet transform scheme based on Direction Prediction called DP LWT to implement the fast and efficient compression of high-resolution remote sensing images. The new algorithm first divides a high-resolution remote sensing image into a number of non-overlapping sub-blocks. Then, the gradient operator is used to predict the best lifting direction of every sub-block in the remote sensing image quickly, and completes the direction lifting wavelet transform by the in terpolation along the best lifting direction, Finally, the remote sensing image is coded by Set Parti-tioned in Hierarchical Tree(SPIHT). The experimental results show that the new algorithm effective ly weakens the high-frequency coefficients on the non-horizontal and non-vertical directions of every image subband. Compared with the traditional ADL, the DP-LWT can effectively reduce the time computational complexity of directional prediction in lifting wavelet transform, and keeps the Peak
收稿日期：2013-04-01；修订日期：2013-04-17，
基金项目：国家自然科学基金资助项目（No.60602035，No,61071103)；中央高校基本科研业务费专项资金资助项目
(No. 2012LYB50)