Methods for multi-spectral image fusion: identifying stable and repeatable information across the visible and infrared spectra

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dc.contributor.advisorNicolls, Fredericken_ZA
dc.contributor.authorRetief, Francois Jacquesen_ZA
dc.date.accessioned2016-07-25T07:07:58Z
dc.date.available2016-07-25T07:07:58Z
dc.date.issued2016en_ZA
dc.description.abstractFusion of images captured from different viewpoints is a well-known challenge in computer vision with many established approaches and applications; however, if the observations are captured by sensors also separated by wavelength, this challenge is compounded significantly. This dissertation presents an investigation into the fusion of visible and thermal image information from two front-facing sensors mounted side-by-side. The primary focus of this work is the development of methods that enable us to map and overlay multi-spectral information; the goal is to establish a combined image in which each pixel contains both colour and thermal information. Pixel-level fusion of these distinct modalities is approached using computational stereo methods; the focus is on the viewpoint alignment and correspondence search/matching stages of processing. Frequency domain analysis is performed using a method called phase congruency. An extensive investigation of this method is carried out with two major objectives: to identify predictable relationships between the elements extracted from each modality, and to establish a stable representation of the common information captured by both sensors. Phase congruency is shown to be a stable edge detector and repeatable spatial similarity measure for multi-spectral information; this result forms the basis for the methods developed in the subsequent chapters of this work. The feasibility of automatic alignment with sparse feature-correspondence methods is investigated. It is found that conventional methods fail to match inter-spectrum correspondences, motivating the development of an edge orientation histogram (EOH) descriptor which incorporates elements of the phase congruency process. A cost function, which incorporates the outputs of the phase congruency process and the mutual information similarity measure, is developed for computational stereo correspondence matching. An evaluation of the proposed cost function shows it to be an effective similarity measure for multi-spectral information.en_ZA
dc.identifier.apacitationRetief, F. J. (2016). <i>Methods for multi-spectral image fusion: identifying stable and repeatable information across the visible and infrared spectra</i>. (Thesis). University of Cape Town ,Faculty of Engineering & the Built Environment ,Department of Electrical Engineering. Retrieved from http://hdl.handle.net/11427/20636en_ZA
dc.identifier.chicagocitationRetief, Francois Jacques. <i>"Methods for multi-spectral image fusion: identifying stable and repeatable information across the visible and infrared spectra."</i> Thesis., University of Cape Town ,Faculty of Engineering & the Built Environment ,Department of Electrical Engineering, 2016. http://hdl.handle.net/11427/20636en_ZA
dc.identifier.citationRetief, F. 2016. Methods for multi-spectral image fusion: identifying stable and repeatable information across the visible and infrared spectra. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Retief, Francois Jacques AB - Fusion of images captured from different viewpoints is a well-known challenge in computer vision with many established approaches and applications; however, if the observations are captured by sensors also separated by wavelength, this challenge is compounded significantly. This dissertation presents an investigation into the fusion of visible and thermal image information from two front-facing sensors mounted side-by-side. The primary focus of this work is the development of methods that enable us to map and overlay multi-spectral information; the goal is to establish a combined image in which each pixel contains both colour and thermal information. Pixel-level fusion of these distinct modalities is approached using computational stereo methods; the focus is on the viewpoint alignment and correspondence search/matching stages of processing. Frequency domain analysis is performed using a method called phase congruency. An extensive investigation of this method is carried out with two major objectives: to identify predictable relationships between the elements extracted from each modality, and to establish a stable representation of the common information captured by both sensors. Phase congruency is shown to be a stable edge detector and repeatable spatial similarity measure for multi-spectral information; this result forms the basis for the methods developed in the subsequent chapters of this work. The feasibility of automatic alignment with sparse feature-correspondence methods is investigated. It is found that conventional methods fail to match inter-spectrum correspondences, motivating the development of an edge orientation histogram (EOH) descriptor which incorporates elements of the phase congruency process. A cost function, which incorporates the outputs of the phase congruency process and the mutual information similarity measure, is developed for computational stereo correspondence matching. An evaluation of the proposed cost function shows it to be an effective similarity measure for multi-spectral information. DA - 2016 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2016 T1 - Methods for multi-spectral image fusion: identifying stable and repeatable information across the visible and infrared spectra TI - Methods for multi-spectral image fusion: identifying stable and repeatable information across the visible and infrared spectra UR - http://hdl.handle.net/11427/20636 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/20636
dc.identifier.vancouvercitationRetief FJ. Methods for multi-spectral image fusion: identifying stable and repeatable information across the visible and infrared spectra. [Thesis]. University of Cape Town ,Faculty of Engineering & the Built Environment ,Department of Electrical Engineering, 2016 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/20636en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentDepartment of Electrical Engineeringen_ZA
dc.publisher.facultyFaculty of Engineering and the Built Environment
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherElectrical Engineeringen_ZA
dc.titleMethods for multi-spectral image fusion: identifying stable and repeatable information across the visible and infrared spectraen_ZA
dc.typeMaster Thesis
dc.type.qualificationlevelMasters
dc.type.qualificationnameMSc (Eng)en_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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