Analysis of Two Representative Algorithms of Depth Estimation from Light Field Images

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dc.contributor.author Yutao, Chen
dc.date.accessioned 2017-08-28T07:32:25Z
dc.date.available 2017-08-28T07:32:25Z
dc.date.copyright 2017 en_US
dc.date.issued 2017-08-28
dc.identifier.uri http://hdl.handle.net/1828/8466
dc.description.abstract Lightfield (LF) cameras offer many more of advanced features than conventional cameras. One type of LF camera, the lenslet LF camera is portable and has become available to consumers in recent years. Images from LF cameras can be used to generate depth maps which is an essential tool in several areas of image processing and can be used in the generation of various visual effects. LF images generated by lenslet LF cameras have different properties that images generated from an array of conventional cameras and thus require different depth estimation approaches. To study and compare the differences of depth estimation from LF images, this project describes two existing algorithms for depth estimation. The first algorithm, from Korea Advanced Institute of Science and Technology, estimates the depth labels based on stereo matching theory, where each label is corresponding to a specific depth. The second algorithm, developed by University of California and Adobe Systems Company, takes full advantage of the LF camera structure to estimate depths from so-called refocus cue and correspondence cue, and combines the depth maps from both cues in a Markov Random Field (MRF) to obtain a quality depth map. Since these two methods apply different concepts and contain some widely used techniques for depth estimations, it is worthy to analyze and compare their advantages and disadvantages. In this report, the two methods were implemented using public domain software, the first method being called the DEL method and the second being called the DER method. Comparisons with respect to computational speed and visual quality of the depth information show that the DEL method tend to be more stable and gives better results than the DER method for the experiments carried out in this report. en_US
dc.language.iso en en_US
dc.rights Available to the World Wide Web en_US
dc.subject Depth Estimation en_US
dc.subject Light Field en_US
dc.subject Light Field Image en_US
dc.title Analysis of Two Representative Algorithms of Depth Estimation from Light Field Images en_US
dc.type project en_US
dc.contributor.supervisor Panajotis, Agathoklis
dc.contributor.supervisor Kin, Li
dc.degree.department Department of Electrical and Computer Engineering en_US
dc.degree.level Master of Engineering M.Eng. en_US
dc.description.scholarlevel Graduate en_US

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