Hyperspectral Anomaly Detection With Attribute and Edge-Preserving Filters
By Xudong Kang, Xiangping Zhang, Shutao Li, Kenli Li, Jun Yu Li, Jon Atli Benediktsson. IEEE Transactions on Geoscience and Remote Sensing, 2017
358 citations recorded by the source corpus.
Subfields: Analytical Chemistry, Atmospheric Science, Media Technology
View Paper: https://www.semanticscholar.org/paper/2ed2d561cb38822eb622fb24db1b834537698260
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Analytical Chemistry
- Shutao Li
- Xudong Kang
- Antonio J. Plaza
- Jon Atli Benediktsson
- Xuanlin Xiang
- Lina Zhuang
- Jocelyn Chanussot
- Pedram Ghamisi
In Atmospheric Science
- Shutao Li
- Xudong Kang
- Jon Atli Benediktsson
- Antonio J. Plaza
- Xuanlin Xiang
- Lianru Gao
- Lina Zhuang
- Jun Yu Li
In Media Technology
- Shutao Li
- Xudong Kang
- Jon Atli Benediktsson
- Antonio J. Plaza
- Xuanlin Xiang
- Leyuan Fang
- Lianru Gao
- Lina Zhuang
Citations in the corpus
- BockNet: Blind-Block Reconstruction Network With a Guard Window for Hyperspectral Anomaly Detection (2023, methodology): “A. Datasets 1) Airport Dataset: It was collected by airborne visible infrared imaging spectrometer (AVIRIS) covering Gulfport city [71], and the anomalous objects in this HSI are three aircraft with different sizes and shapes.”
- PCA-Based Edge-Preserving Features for Hyperspectral Image Classification (2017, methodology): “Due to this advantage, hyperspectral remote sensing has been successfully used in many applications, such as target detection [1], [2], spectral unmixing [3], and scene”