Name
Title | ||
|---|---|---|
A Sparse Representation-Based Binary Hypothesis Model for Target Detection in Hyperspectral Images |
Abstract | ||
|---|---|---|
In this paper, a new sparse representation-based binary hypothesis (SRBBH) model for hyperspectral target detection is proposed. The proposed approach relies on the binary hypothesis model of an unknown sample induced by sparse representation. The sample can be sparsely represented by the training samples from the background-only dictionary under the null hypothesis and the training samples from the target and background dictionary under the alternative hypothesis. The sparse vectors in the model can be recovered by a greedy algorithm, and the same sparsity levels are employed for both hypotheses. Thus, the recovery process leads to a competition between the background-only subspace and the target and background subspace, which are directly represented by the different hypotheses. The detection decision can be made by comparing the reconstruction residuals under the different hypotheses. Extensive experiments were carried out on hyperspectral images, which reveal that the SRBBH model shows an outstanding detection performance. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/TGRS.2014.2337883 | IEEE T. Geoscience and Remote Sensing |
Keywords | Field | DocType |
sparse vectors,background only dictionary,remote sensing,training samples,target-background subspace,srbbh model,detection decision,background only subspace,sparse representation based binary hypothesis model,greedy algorithm,alternative hypothesis,greedy algorithms,target detection,object detection,null hypothesis,hyperspectral imaging,target-background dictionary,hyperspectral images,binary hypothesis,hyperspectral target detection,sparse representation,hyperspectral imagery,vectors,detectors,niobium,dictionaries | Computer vision,Alternative hypothesis,Subspace topology,Pattern recognition,Null hypothesis,Sparse approximation,Greedy algorithm,Hyperspectral imaging,Artificial intelligence,Mathematics,Binary number | Journal |
Volume | Issue | ISSN |
53 | 3 | 0196-2892 |
Citations | PageRank | References |
43 | 1.18 | 22 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuxiang Zhang | 1 | 167 | 15.28 |
| Bo Du | 2 | 1662 | 130.01 |
| Liangpei Zhang | 3 | 5448 | 307.02 |