{"data":{"id":"10.6084/m9.figshare.3412381.v2","type":"dois","attributes":{"doi":"10.6084/m9.figshare.3412381.v2","prefix":"10.6084","suffix":"m9.figshare.3412381.v2","identifiers":[],"alternateIdentifiers":[],"creators":[{"name":"Jiangfeng","affiliation":[],"nameIdentifiers":[]}],"titles":[{"title":"Pan-sharpening with Structural Consistency and L1/2 Gradient Prior"}],"publisher":"Figshare","container":{},"publicationYear":2016,"subjects":[{"subject":"90609 Signal Processing","subjectScheme":"FOR"},{"subject":"FOS: Electrical engineering, electronic engineering, information engineering","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Electrical engineering, electronic engineering, information engineering","subjectScheme":"Fields of Science and Technology (FOS)"}],"contributors":[],"dates":[{"date":"2016-06-03","dateType":"Created"},{"date":"2016-06-03","dateType":"Updated"},{"date":"2016","dateType":"Issued"}],"language":null,"types":{"ris":"GEN","bibtex":"misc","citeproc":"article","schemaOrg":"Collection","resourceType":"Fileset","resourceTypeGeneral":"Collection"},"relatedIdentifiers":[{"relationType":"IsPreviousVersionOf","relatedIdentifier":"10.6084/m9.figshare.3412381","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":["17973517 Bytes"],"formats":[],"version":null,"rightsList":[{"rights":"CC-BY","rightsUri":"http://creativecommons.org/licenses/by/3.0/us"}],"descriptions":[{"description":"In this letter, a variational method is proposed for pan-sharpening by fusing a \nlow resolution multispectral (LRMS) image with a high resolution panchromatic \n(PAN) image to generate a high resolution multispectral (HRMS) image. Most \nmethods focus on spatial intensity preservation while the proposed method tends \nto preserve the consistency of the spatial structure information. In addition, \nan L\u003csub\u003e1\u003c/sub\u003e-aL\u003csub\u003e2\u003c/sub\u003e metric is used to estimate L\u003csub\u003e1/2\u003c/sub\u003e \ngradient prior. The alternating direction method of multipliers (ADMM) and the \ndifference of convex algorithm (DCA) are used to guarantee the convergence of \nthe algorithm. A large number of experiments show that the proposed method has \nobvious advantages compared with other advanced methods both subjectively and \nobjectively.","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"xml":"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","url":"https://figshare.com/articles/Pan-sharpening_with_Structural_Consistency_and_L1_2_Gradient_Prior/3412381/2","contentUrl":null,"metadataVersion":8,"schemaVersion":"http://datacite.org/schema/kernel-4","source":"api","isActive":true,"state":"findable","reason":null,"viewCount":0,"viewsOverTime":[],"downloadCount":0,"downloadsOverTime":[],"referenceCount":0,"citationCount":0,"citationsOverTime":[],"partCount":0,"partOfCount":0,"versionCount":0,"versionOfCount":0,"created":"2016-06-03T12:11:00.000Z","registered":"2016-06-03T12:11:01.000Z","published":"2016","updated":"2024-12-14T12:31:53.000Z"},"relationships":{"client":{"data":{"id":"figshare.ars","type":"clients"}},"provider":{"data":{"id":"otjm","type":"providers"}},"media":{"data":{"id":"10.6084/m9.figshare.3412381.v2","type":"media"}},"references":{"data":[]},"citations":{"data":[]},"parts":{"data":[]},"partOf":{"data":[]},"versions":{"data":[]},"versionOf":{"data":[]}}}}