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dc.contributor.advisorBarshan, Billur
dc.contributor.authorDobrucalı, Oğuzcan
dc.date.accessioned2016-01-08T18:21:00Z
dc.date.available2016-01-08T18:21:00Z
dc.date.issued2010
dc.identifier.urihttp://hdl.handle.net/11693/15581
dc.descriptionAnkara : The Department of Electrical and Electronics Engineering and the Institute of Engineering and Sciences of Bilkent University, 2010.en_US
dc.descriptionThesis (Master's) -- Bilkent University, 2010.en_US
dc.descriptionIncludes bibliographical references leaves 68-75.en_US
dc.description.abstract3-D models of environments can be very useful and are commonly employed in areas such as robotics, art and architecture, environmental planning and documentation. A 3-D model is typically comprised of a large number of measurements. When 3-D models of environments need to be transmitted or stored, they should be compressed efficiently to use the capacity of the communication channel or the storage medium effectively. In this thesis, we propose a novel compression technique based on compressive sampling, applied to sparse representations of 3-D laser range measurements. The main issue here is finding highly sparse representations of the range measurements, since they do not have such representations in common domains, such as the frequency domain. To solve this problem, we develop a new algorithm to generate sparse innovations between consecutive range measurements acquired while the sensor moves. We compare the sparsity of our innovations with others generated by estimation and filtering. Furthermore, we compare the compression performance of our lossy compression method with widely used lossless and lossy compression techniques. The proposed method offers small compression ratio and provides a reasonable compromise between reconstruction error and processing time.en_US
dc.description.statementofresponsibilityDobrucalı, Oğuzcanen_US
dc.format.extentxiv, 75 leaves, illustrationsen_US
dc.language.isoEnglishen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subject3-D laser scanen_US
dc.subject3-D modelingen_US
dc.subject3-D mappingen_US
dc.subjectcompressive sensingen_US
dc.subjectcompressive samplingen_US
dc.subjectsensor data compressionen_US
dc.subjectSICK LMS laser range finderen_US
dc.subject.lccTA1632 .D63 2010en_US
dc.subject.lcshImage compression.en_US
dc.subject.lcshRemote sensing.en_US
dc.subject.lcshData compression (Computer science)en_US
dc.subject.lcshThree-dimensional imaging--Mathematical models.en_US
dc.subject.lcshLasers.en_US
dc.titleA novel compression algorithm based on sparse sampling of 3-D laser range scansen_US
dc.typeThesisen_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.publisherBilkent Universityen_US
dc.description.degreeM.S.en_US


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