A Joint Sparsity Approach to Soil Detection Using Expanded Bands of WV-2 Images

Minh Dao; Kwan Chiman; Bernabe Sergio; Plaza Antonio J.; Koperski Krzysztof

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A Joint Sparsity Approach to Soil Detection Using Expanded Bands of WV-2 Images

机译：WV-2图像扩展带的联合稀疏性土壤检测方法

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Soil can be used as a damage indicator of landslides and flooding, which expose soil from vegetation canopy. It can also be used as an indirect indicator of illegal tunnel digging activity. This letter presents a sparsity-based approach to soil detection using multispectral satellite images, where both original and synthetic bands have been used. Spatial and spectral information has then been jointly used in soil detection. Extensive experiments clearly demonstrated the feasibility of our approach.

机译：土壤可以用作滑坡和洪水的破坏指标，它们使土壤从植被冠层中暴露出来。它也可以用作非法挖掘隧道活动的间接指示。这封信提出了一种基于稀疏性的土壤探测方法，该方法使用多光谱卫星图像进行了原始和合成波段的检测。然后将空间和光谱信息联合用于土壤检测。大量的实验清楚地证明了我们方法的可行性。

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来源
《IEEE Geoscience and Remote Sensing Letters》 |2019年第12期|1869-1873|共5页
作者
Minh Dao; Kwan Chiman; Bernabe Sergio; Plaza Antonio J.; Koperski Krzysztof;
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作者单位

Appl Res LIC Rockville MD 20850 USA;

Univ Complutense Madrid Dept Comp Sci Madrid 28040 Spain;

Univ Extremadura Dept Technol Comp & Commun Hyperspectral Comp Lab Caceres 10003 Spain;

Digital Globe Inc Westminster CO 80234 USA;

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正文语种 eng
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关键词
Extended multiattribute profile (EMAP); flooding; joint sparsity-based model; landslide; multispectral (MS) satellite images; soil detection; synthetic spectral bands;

机译：扩展的多属性配置文件（EMAP）;洪水;基于联合稀疏性的模型;滑坡;多光谱（MS）卫星图像;土壤检测;合成光谱带;

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1. A joint band prioritization and band-decorrelation approach to band selection for hyperspectral image classification [J] . Chein-I Chang, Qian Du IEEE Transactions on Geoscience and Remote Sensing . 1999,第6期

机译：用于高光谱图像分类的波段优先联合和波段解相关方法
2. Joint Sparse Tensor Representation for the Target Detection of Polarized Hyperspectral Images [J] . Junping Zhang, Jian Tan, Ye Zhang IEEE Geoscience and Remote Sensing Letters . 2017,第12期

机译：联合稀疏张量表示法用于偏振高光谱图像的目标检测
3. Multiple change detection for multispectral remote sensing images via joint sparse representation [J] . Huihui Song, Guojie Wang, Kaihua Zhang Optical engineering . 2014,第12期

机译：通过联合稀疏表示的多光谱遥感图像的多变化检测
4. Detection of Dual-Band Infrared Small Target based on Joint Dynamic Sparse Representation [C] . Zhou Jinwei, Li Jicheng, Shi Zhiguang, Conference on Applied Optics and Photonics China . 2015

机译：基于联合动态稀疏表示的双波段红外小目标检测
5. Joint symbol detection and synchronization design for ultra high speed wireless data networks in the terahertz band [D] . Gupta, Ajeya 2015

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6. Compressed Sensing/Sparse-Recovery Approach for Improved Range Resolution in Narrow-Band Radar [O] . Sandra Costanzo 2016

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7. A SPARSITY-DRIVEN JOINT IMAGE REGISTRATION AND CHANGE DETECTION TECHNIQUE FOR SAR IMAGERY [O] . Lam H. Nguyen, Trac D. Tran 2012

机译：SAR影像的稀疏驱动联合图像配准和变化检测技术

A Joint Sparsity Approach to Soil Detection Using Expanded Bands of WV-2 Images

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