http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-106683102-B
Outgoing Links
| Predicate | Object |
|---|---|
| classificationCPCAdditional | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-10044 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-30181 |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-11 |
| filingDate | 2016-12-30-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| grantDate | 2019-07-23-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationDate | 2019-07-23-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | CN-106683102-B |
| titleOfInvention | SAR Image Segmentation Method Based on Ridgelet Filter and Convolutional Structure Learning Model |
| abstract | The invention discloses a SAR image segmentation method based on a ridge wave filter and a convolution structure model. It mainly solves the problem of inaccurate segmentation of SAR images in the prior art. The implementation steps are: (1) sketching the SAR image to obtain a sketch map; (2) dividing the pixel subspace of the SAR image according to the area map of the SAR image; (3) constructing a ridge wave filter set; (4) constructing a volume (5) SAR image segmentation method based on ridge wave filter and convolutional structure model is used to segment the pixel subspace of mixed aggregate structures; (6) independent target segmentation based on the gathering feature of sketch lines; (7) ) Segmentation of line objects based on visual semantic rules; (8) Segmentation of pixel subspaces in homogeneous regions using a priori model based on polynomial logistic regression; (9) Merging segmentation results. The invention obtains a good segmentation effect of SAR images and can be used for semantic segmentation of SAR images. |
| priorityDate | 2016-12-30-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type | http://data.epo.org/linked-data/def/patent/Publication |
Incoming Links
Total number of triples: 15.