Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.777989
Title: Estimation of the plenoptic function from a swiped image
Author: Lawson, Michael Yee-Ming Chong
ISNI:       0000 0004 7963 753X
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2019
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Abstract:
The image blurring that results from moving a camera whilst the shutter is open is normally regarded as undesirable. However, the blurring of the images contains hidden information which can be extracted to give information about the captured scene. Information encapsulated within this blur allows the light rays present within the scene to be recovered. Given the correct recovery of the light rays that form a blurred image, a sharp image of the scene can be generated for an arbitrary camera location. Therefore, rather than resharpening an image with motion blur, the goal of the work contained within this thesis is to recover the light rays within the scene Recovery of the light rays within the scene is achieved by using a layer based model to represent objects within the scene as planes at discrete depths, and by using an extension to the level set method, to segment the blurred image into planes at different depths. Knowledge of the layer boundaries is then used to recover the surfaces of the layers, and hence a model of the scene in three dimensions. The algorithm described in this thesis has been successfully tested on real and synthetic images constructed from fronto-parallel planes, with the scene being recovered accurately from all positions within the original path of the camera.
Supervisor: Brookes, Mike ; Dragotti, Pier Luigi Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.777989  DOI:
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