A New Low-Rank Representation Based Hyperspectral Image Denoising Method for Mineral Mapping-Reference-Cited by-同舟云学术

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A New Low-Rank Representation Based Hyperspectral Image Denoising Method for Mineral Mapping

Published:2017-11-08 Issue:11 Volume:9 Page:1145
ISSN:2072-4292
Container-title:Remote Sensing
language:en
Short-container-title:Remote Sensing

Author:

Gao Lianru,Yao Dan,Li Qingting,Zhuang Lina,Zhang Bing,Bioucas-Dias José

Funder

National Natural Science Foundation of China

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

Link

http://www.mdpi.com/2072-4292/9/11/1145/pdf

Reference48 articles.

1. Color Display for Hyperspectral Imagery

2. A Convex Formulation for Hyperspectral Image Superresolution via Subspace-Based Regularization

3. Hyperspectral remote sensing for mineral exploration in Pulang, Yunnan Province, China

4. Expert system-based mineral mapping in northern death valley, California/Nevada, using the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS)

5. Comparison of airborne hyperspectral data and eo-1 hyperion for mineral mapping

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