Details Recovery by Linear Prediction from an Auxiliary Band in Wavelet Domain for Hyperspectral Image Denoising

摘要：

　　This paper proposes a hyperspectral image denoising method based on details recovery from an auxiliary band.Based on the fact that the significant spectral correlation of hyperspectral image still exists in wavelet domain,the details of noisy band can be well recovered by prediction in the least square sense from the wavelet coefficients of an auxiliary band of less noise.The performance of the method is tested on both simulated data and the real life data.Experimental results show that the method surpasses other denoising methods in terms of SNR and visually.

关键词： hyperspectral image image denoising wavelets least square linear prediction

作者: Lei Sun Zong-liang Tong He-kai Lin

作者单位: College of Sciences,National University of Defense Technology,Changsha China

会议类型: 国际会议

会议名称: 2016IEEE第二届信息技术、网络、电子及自动化控制会议

会议地点: 重庆

会议语种:英文

页码: 433-437

在线出版日期: 2016-03-20（万方平台首次上网日期，不代表论文的发表时间）