Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/1410
DC FieldValueLanguage
dc.contributor.authorXu, Dongjiang-
dc.contributor.authorKasparis, Takis-
dc.contributor.otherΚασπαρής, Τάκης-
dc.date.accessioned2010-02-18T07:00:09Zen
dc.date.accessioned2013-05-17T05:23:02Z-
dc.date.accessioned2015-12-02T10:12:32Z-
dc.date.available2010-02-18T07:00:09Zen
dc.date.available2013-05-17T05:23:02Z-
dc.date.available2015-12-02T10:12:32Z-
dc.date.issued2007-05-01-
dc.identifier.citationInternational Journal of Pattern Recognition and Artificial Intelligence (IJPRAI), 2007, vol.21, no.3, pp. 573-590en_US
dc.identifier.issn17936381-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/1410-
dc.description.abstractThis paper proposes a hybrid approach to image registration for inferring the affine transformation that best matches a pair of partially overlapping aerial images. The image registration is formulated as a two-stage hybrid approach combining both phase correlation method (PCME) and optical flow equation (OFE) based estimation algorithm in a coarse-to-fine manner. With PCME applied at the highest level of decomposition, the initial affine parameter model could be first estimated. Subsequently, the OFE-based estimation algorithm is incorporated into the proposed hybrid approach using a multi-resolution mechanism. PCME is characterized by its insensitivity to large geometric transform between images, which can effectively guide the OFE-based registration. For image pairs under salient brightness variations, we propose a nonlinear image representation that emphasizes common intensity information, suppresses the non-common information between an image pair, and is suitable for the proposed coarse-to-fine hierarchical iterative processing. Experimental results demonstrate the accuracy and efficiency of our proposed approach using different types of aerial images.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.relation.ispartofInternational Journal of Pattern Recognition and Artificial Intelligence (IJPRAI)en_US
dc.rights© World Scientificen_US
dc.subjectImage registrationen_US
dc.subjectOptical flowen_US
dc.subjectPhase correlationen_US
dc.subjectGaussian/Laplacian pyramiden_US
dc.titleA hybrid and hierarchical approach to aerial image registrationen_US
dc.typeArticleen_US
dc.affiliationUniversity of Central Floridaen
dc.collaborationUniversity of Central Floridaen_US
dc.subject.categoryElectrical Engineering - Electronic Engineering - Information Engineeringen_US
dc.journalsSubscriptionen_US
dc.countryUnited Statesen_US
dc.subject.fieldEngineering and Technologyen_US
dc.publicationPeer Revieweden_US
dc.identifier.doi10.1142/S0218001407005508en_US
dc.dept.handle123456789/54en
dc.relation.issue3en_US
dc.relation.volume21en_US
cut.common.academicyear2006-2007en_US
dc.identifier.spage573en_US
dc.identifier.epage590en_US
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.fulltextNo Fulltext-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.openairetypearticle-
crisitem.journal.journalissn1793-6381-
crisitem.journal.publisherWorld Scientific-
crisitem.author.deptDepartment of Electrical Engineering, Computer Engineering and Informatics-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.orcid0000-0003-3486-538x-
crisitem.author.parentorgFaculty of Engineering and Technology-
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