@inproceedings{f7e36907d35b44fcbd4d4c0298b42363,
title = "Effective hyperspectral image block compressed sensing using thress-dimensional wavelet transform",
abstract = "In this paper, an effective block compressed sensing algorithm based on improved noise variance estimation method is proposed for hyperspectral images. The reconstruction process adopts the iterative projected Landweber and soft-thresholding bivariate shrinkage image denoising based on three-dimensional wavelet transform. The improved noise variance estimation method can more effectively remove noise and achieve better image reconstruction quality. Experimental results demonstrate that the proposed algorithm significantly outperform several state-of-the-art compressed sensing algorithms.",
keywords = "bivariate shrinkage, compressed sensing, hyperspectral image, projected Landweber, three-dimensional wavelet transform",
author = "Ying Hou and Yanning Zhang",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; Joint 2014 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2014 and the 35th Canadian Symposium on Remote Sensing, CSRS 2014 ; Conference date: 13-07-2014 Through 18-07-2014",
year = "2014",
month = nov,
day = "4",
doi = "10.1109/IGARSS.2014.6947101",
language = "英语",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2973--2976",
booktitle = "International Geoscience and Remote Sensing Symposium (IGARSS)",
}