http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-112734763-B

Outgoing Links

Predicate Object
classificationCPCAdditional http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-10024
classificationCPCInventive http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T5-002
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-10
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-22
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-90
classificationIPCInventive http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-90
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-10
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T5-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06V10-74
filingDate 2021-01-29-04:00^^<http://www.w3.org/2001/XMLSchema#date>
grantDate 2022-09-16-04:00^^<http://www.w3.org/2001/XMLSchema#date>
publicationDate 2022-09-16-04:00^^<http://www.w3.org/2001/XMLSchema#date>
publicationNumber CN-112734763-B
titleOfInvention Image decomposition method based on joint sparse coding of convolution and K-SVD dictionary
abstract The invention discloses an image decomposition method based on convolution and K-SVD dictionary joint sparse coding. First, an acquired color image is preprocessed to obtain an image to be decomposed; Superposition; build a priori constraints according to the prior characteristics of the two unknown components; finally solve the two unknown components through alternate optimization; judge whether a feasible solution is reached according to the convergence conditions. The invention can be used for image denoising. A set of convolution operators is obtained by learning according to different noise types, and the noise is approximated by updating the convolution kernel and the response coefficient. The method can be dynamically applied to various noise types, and overcomes the problem of constructing different Disadvantages of regularization constraints.
priorityDate 2021-01-29-04:00^^<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/gene/GID155012
http://rdf.ncbi.nlm.nih.gov/pubchem/protein/ACCP06909
http://rdf.ncbi.nlm.nih.gov/pubchem/compound/CID24404
http://rdf.ncbi.nlm.nih.gov/pubchem/gene/GID3075
http://rdf.ncbi.nlm.nih.gov/pubchem/gene/GID553297
http://rdf.ncbi.nlm.nih.gov/pubchem/gene/GID280816
http://rdf.ncbi.nlm.nih.gov/pubchem/protein/ACCP08603
http://rdf.ncbi.nlm.nih.gov/pubchem/substance/SID419559532
http://rdf.ncbi.nlm.nih.gov/pubchem/gene/GID12628
http://rdf.ncbi.nlm.nih.gov/pubchem/protein/ACCA0A0R4IPQ8

Total number of triples: 27.