Denoising of Hyperspectral Remote Sensing Image using Multiple Linear Regression and Wavelet Shrinkage

摘要：

　　Hyperspectral remote sensing image is easily contaminated by noise,which will affect the application of hyperspectral image,such as target detection,classification and segmentation,etc.Therefore,a denoising method of hyperspectral remote sensing image based on multiple linear regression (MLR) and wavelet shrinkage (WS) is proposed.Firstly,the residual image and the predicted image are obtained via MLR.Secondly,WS is performed on the residual image to remove the noise in the spatial domain.Lastly,a final denoised image is obtained by the predicted image and the corrected residual image.The experimental results show that the proposed method can improve signal-tonoise ratio (SNR) of the hyperspectral image efficiently.

关键词： hyperspectral remote sensing image denoising multiple linear regression wavelet shrinkage

作者: Dong Xu Lei Sun Jianshu Luo

作者单位: Department of Mathematics and System Science, College of Science, National University of Defense Technology, Changsha, Hunan, P.R.China 410073

会议类型: 国际会议

会议名称: 2013 International Conference on Information, Business and Education Technology (2013信息、商业与教育技术国际会议(ICIBET 2013))

会议地点: 北京

会议语种:英文

页码: 152-155

在线出版日期: 2013-03-14（万方平台首次上网日期，不代表论文的发表时间）