| Predicate |
Object |
| assignee |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_e61dd9097ef0c42d9e8c1fd4e1d1ec3c |
| classificationCPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-24
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-253
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-254 |
| classificationIPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-62 |
| filingDate |
2019-04-19-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_8e3672d7acfc60b5b50248090f9c6c09
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_30377f0d3d47370ea54ffa0b27c7279b
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_49f4d3b014f6fb3dccfb8992c5faed68 |
| publicationDate |
2019-08-06-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber |
CN-110097101-A |
| titleOfInvention |
A remote sensing image fusion and coastal zone classification method based on improved reliability factor |
| abstract |
The invention discloses a remote sensing image fusion and coastal zone classification method based on an improved reliability factor, which mainly includes: reading and registering a SAR image and an optical image; selecting an FLF line detection algorithm to extract the coastline; dividing the classification area into uniform areas and uneven area; perform image fusion and extract grayscale co-occurrence matrix texture and select training data; calculate the conditional probability of the category to which the current pixel belongs and the potential energy of each pixel belonging to each category, and assign the category label with the smallest potential energy to the current pixel As the classification result; 20% of the data is extracted from each category of the classification result as a training set until the potential energy of each pixel belonging to each category no longer changes, then the final classification result is output. The invention provides different reliability factors for different sensor data according to different ground object areas, thereby realizing the accurate classification of the coastal zone. |
| isCitedBy |
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-113538536-A
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-113538536-B
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-113112533-A
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-116129145-A
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-116129145-B
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-110705578-A
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-113112533-B
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-112016441-B
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-112364289-A
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-112016441-A
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-111079847-B
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-111079847-A
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-111339959-A |
| priorityDate |
2019-04-19-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type |
http://data.epo.org/linked-data/def/patent/Publication |