http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-115131258-A

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classificationCPCAdditional http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-20221
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http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T3-40
filingDate 2022-06-21-04:00^^<http://www.w3.org/2001/XMLSchema#date>
inventor http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_42495d18fa3825d3311b5199b4360827
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_b555c83212487dcca0ba91cd01ffbf7e
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publicationDate 2022-09-30-04:00^^<http://www.w3.org/2001/XMLSchema#date>
publicationNumber CN-115131258-A
titleOfInvention A hyperspectral, multispectral and panchromatic image fusion method based on sparse tensor priors
abstract In view of the application requirements of fusing a hyperspectral image with a multispectral image and a panchromatic image to obtain a fused hyperspectral image, the present invention proposes a hyperspectral, multispectral and panchromatic image fusion method based on sparse tensor prior. The fusion method can fully exploit the relationship between spatial, spectral and non-local similar blocks in the fused hyperspectral image by establishing a sparse tensor prior. The model proposed by the present invention includes data fidelity terms and sparse tensor prior terms, and is solved by an alternating direction multiplier method, thereby obtaining a fused hyperspectral image that is qualitatively and quantitatively superior to the contrast method. Compared with other fusion algorithms, the fusion result of the present invention has higher definition, and each index is also closest to the ideal value, and is superior to the comparison method in both qualitative and quantitative aspects.
isCitedBy http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-115880199-A
priorityDate 2022-06-21-04:00^^<http://www.w3.org/2001/XMLSchema#date>
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Total number of triples: 21.