http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-111641822-A
Outgoing Links
| Predicate | Object |
|---|---|
| assignee | http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_89d8e7355750aa815842a3fa5b382c19 |
| classificationCPCAdditional | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/H04N2013-0074 |
| classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-62 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/H04N13-106 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/H04N17-00 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-0002 |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/H04N17-00 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-00 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/H04N13-106 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-62 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-62 |
| filingDate | 2020-05-06-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor | http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_5413bc3c088a89c4ab0775343889ff4a http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_4fa8cef2988f66370091068da4208677 |
| publicationDate | 2020-09-08-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | CN-111641822-A |
| titleOfInvention | A Repositioning Stereo Image Quality Evaluation Method |
| abstract | The invention discloses a method for evaluating the quality of a repositioned stereoscopic image, which considers the effects of geometric distortion, information loss and visual comfort on the repositioning of the stereoscopic image, and calculates that the aspect ratios of the original stereoscopic image and the repositioned stereoscopic image are similar. properties, grid similarity, forward information loss, backward information loss, information retention features, visual comfort, get the feature vector of the repositioned stereo image, and then use support vector regression in the training phase to train the feature vector in the training set , construct a support vector regression training model; use the support vector regression training model in the test phase to predict the objective quality evaluation prediction value of the repositioned stereo image corresponding to the feature vector in the test set, because the obtained feature vector has strong stability and It can better reflect the geometric distortion, information loss and visual comfort of the repositioned stereo image, thus effectively improving the correlation between the objective evaluation results and the subjective perception of the human eye. |
| isCitedBy | http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-112419234-A http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-113920115-A http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-112770105-A http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-113920115-B http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-112770105-B http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-112419234-B |
| priorityDate | 2020-05-06-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type | http://data.epo.org/linked-data/def/patent/Publication |
Incoming Links
| Predicate | Subject |
|---|---|
| isDiscussedBy | http://rdf.ncbi.nlm.nih.gov/pubchem/substance/SID419535645 http://rdf.ncbi.nlm.nih.gov/pubchem/compound/CID43672 |
Total number of triples: 30.