Research of Remote Sensing Image Compression Technology Based on Compressed Sensing
Compressed Sensing (CS) theory is a new method of signal acquisition and processing proposed in recent years.With small amount of sampling data recovering original data to precisely reconstruct sparse signal or compression signal, the theory breaks though the restriction of Nyquist sampling theorem.CS can avoid enormous sampling data waste but also reduce the complexity of image coding.This paper reviews the basic theory of CS and its three key points, including signal sparse representation, design of measurement matrix and reconstruction algorithms.Then, the application of CS in the field of remote sensing image compression technology is studied.Using MATLAB software, we do a series of CS emulation experiments compared with the traditional compression methods.The results show that the proposed method has a good performance on the remote sensing image compression.
Compressed sensing Image compression Sparse signal Reconstruction algorithms
Tong Yu Shujun Deng
Institute of Geospatial Information, Information Engineering University,Zhengzhou 450000, China
国际会议
10th Conference on Image and Graphics Technologies and Applications(第十届图像图形技术与应用学术会议)
北京
英文
214-223
2015-06-19（万方平台首次上网日期，不代表论文的发表时间）