| Predicate |
Object |
| assignee |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_ca46be4e68fa1f5a8b2ef4ab654c490a |
| classificationCPCAdditional |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-10036
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/Y02A40-10
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-20084
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-20081
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-30168 |
| classificationCPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06V10-764
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-0002
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06V10-7715
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06V10-82
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06V10-762
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T3-0012
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06V20-194
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-08 |
| classificationIPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06V20-10
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06V10-77
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06V10-762
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-04
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06V10-764
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06V10-82
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-08
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T3-00 |
| filingDate |
2022-08-17-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_77f135b0488070fd89e77f90d64872cc
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_df27bf5168f7db9b4b2c9820fd235235
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_98340ebc4453dc3f8931e159447a6c9f
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_661a2c8f2683d77982334df37ec5f215
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_4e789fdb81d8273c510a7abd6e1f4230
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_280850a2fa22a277b5ac0a457a3e9890
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_532d49a09e874398938f0ab0d887a164
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_8954a798bff33682924ce5e9378ffb76 |
| publicationDate |
2022-10-25-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber |
CN-115239694-A |
| titleOfInvention |
A Hyperspectral Anomaly Detection Method Fusion Robust Dictionary and Double Cooperative Constrained Regular Terms |
| abstract |
The present invention proposes a hyperspectral anomaly detection method fused with a robust dictionary and a double cooperative constraint regular term, which is used to solve the problems of poor robustness in dictionary construction and insufficient information utilization resulting in poor detection results. Including: 1) use the density estimation model and the local abnormal factor to obtain the density map, and perform pixel-by-pixel multiplication and pixel-by-pixel addition operations to obtain the background suppression map and abnormal enhancement map; 2) the background suppression map and abnormal enhancement map Perform binarization to obtain its index map, and construct a potential anomaly dictionary and a background dictionary; 3) Construct a low-rank and sparse representation model based on double-co-constrained regular terms and optimize the solution to obtain the initial detection result; 4) Use the background suppression map The initial detection result is nonlinearly transformed with the anomaly enhancement map to obtain the final detection result. The invention enhances the robustness of the dictionary, and fully considers the global and local characteristics, thereby effectively improving the hyperspectral anomaly detection effect. |
| priorityDate |
2022-08-17-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type |
http://data.epo.org/linked-data/def/patent/Publication |