Target and Background Separation in Hyperspectral Imagery for Automatic Target Detection
- Resource Type
- Conference
- Authors
- Bitar, Ahmad W.; Cheong, Loong-Fah; Ovarlez, Jean-Philippe
- Source
- 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Acoustics, Speech and Signal Processing (ICASSP), 2018 IEEE International Conference on. :1598-1602 Apr, 2018
- Subject
- Signal Processing and Analysis
Sparse matrices
Dictionaries
Hyperspectral imaging
Object detection
Detectors
Shape
Minimization
Hyperspectral target detection
target separation’ low rank background HSI
sparse target HSI
- Language
- ISSN
- 2379-190X
In this paper, we propose a method for separating known targets of interests from the background in hyperspectral imagery. More precisely, we regard the given hyperspectral image (HSI) as being made up of the sum of low-rank background HSI and a sparse target HSI that contains the known targets based on a pre-learned target dictionary specified by the user. Based on the proposed method, two strategies are outlined and evaluated independently to realize the target detection on both synthetic and real experiments.