http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-108664899-A
Outgoing Links
| Predicate | Object |
|---|---|
| assignee | http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_c96f881b0c20a2c7843712b2022bc1b8 |
| classificationCPCAdditional | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06V20-194 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06V10-58 |
| classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-214 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-2411 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06V10-60 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06V20-13 |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-62 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-46 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-00 |
| filingDate | 2018-04-19-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor | http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_c8f75e00901bb8b84fa5612736e29fff http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_c1abb91225635d6ab55881004bbfb043 |
| publicationDate | 2018-10-16-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | CN-108664899-A |
| titleOfInvention | Hyperspectral Image Mixed Pixel Decomposition Method Based on Model-Driven and RVM Regression |
| abstract | The invention discloses a hyperspectral image mixed pixel decomposition method based on model drive and RVM regression, which includes the following steps: S1, read the hyperspectral image, and use the endmember extraction algorithm to calculate the endmembers including all the bands of the hyperspectral image. Number of elements; S2, extract the spectral vectors of all endmembers in the hyperspectral image; S3, calculate the single scattering albedo of each endmember according to the Hapke model, and linearly mix the single scattering albedo of the endmembers , converted into the albedo of the mixed pixel, the beneficial effect of the present invention is: the nonlinear spectral mixed model is adopted, which can better explain the nonlinear characteristics of the mixed pixel. Compared with the traditional linear mixed pixel decomposition method, the method in this paper has higher accuracy, and the RVM regression model has a probability output, which has statistical significance for the calculation results of the abundance values of each component in the mixed pixel. |
| isCitedBy | http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-113516019-A http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-114002165-A http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-112699838-B http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-112699838-A http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-113516019-B http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-110705082-A |
| priorityDate | 2018-04-19-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type | http://data.epo.org/linked-data/def/patent/Publication |
Incoming Links
Total number of triples: 34.