Computational single-image high dynamic range imaging
department or school: Science, Faculty of
department or school: Computer Science, Department of
data provider: DSpace
degree campus: UBCV
creator: Rouf, Mushfiqur
issued: 2018-06-25T21:31:55Z
issued: 2018
related degree: Doctor of Philosophy - PhD
degree grantor: University of British Columbia
description: This thesis proposes solutions for increasing the dynamic range (DR)—the number of intensity levels—of a single image captured by a camera with a standard dynamic range (SDR). The DR in a natural scene is usually too high for SDR cameras to capture, even with optimum exposure settings. The intensity values of bright objects (highlights) that are above the maximum exposure capacity get clipped due to sensor over-exposure, while objects that are too dark (shades) appear dark and noisy in the image. Capturing a high number of intensity levels would solve this problem, but this is costly, as it requires the use of a camera with a high dynamic range (HDR). Reconstructing an HDR image from a single SDR image is difficult, if not impossible, to achieve for all imaging situations. For some situations, however, it is possible to restore the scene details, using computational imaging techniques. We investigate three such cases, which also occur commonly in imaging. These cases pose relaxed and well-posed versions of the general single-image high dynamic range imaging (HDRI) problem. The first case occurs when the scene has highlights that occupy a small number of pixels in the image; for example, night scenes. We propose the use of a cross-screen filter, installed at the lens aperture, to spread a small part of the light from the highlights across the rest of the image. In post-processing, we detect the spread-out brightness and use this information to reconstruct the clipped highlights. Second, we investigate the cases when highlights occupy a large part of the scene. The first method is not applicable here. Instead, we propose to apply a spatial filter at the sensor that locally varies the DR of the sensor. In post-processing, we reconstruct an HDR image. The third case occurs when the clipped parts of the image are not white but have a color. In such cases, we restore the missing image details in the clipped color channels by analyzing the scene information available in ot…
aggregated CHO: https://circle.library.ubc.ca/rest/handle/2429/66350
note: COMPUTATIONAL SINGLE-IMAGEHIGH DYNAMIC RANGE IMAGINGbyMushfiqur RoufB.Sc., Bangladesh University of Engineering and Technology, 2005M.Sc., Bangladesh University of Engineering and Technology, 2007M.Sc., University of British Columbia, 2009A THESIS SUBMITTED IN PARTIAL FULFILLMENT OFTHE REQUIREMENTS FOR THE DEGREE OFDOCTOR OF PHILOSOPHYinThe Faculty of Graduate and Postdoctoral Studies(Computer Science)THE UNIVERSITY OF BRITISH COLUMBIA(Vancouver)June 2018c©Mushfiqur Rouf 2018The following individuals certify that they have read, and recommend to the Facultyof Graduate and Postdoctoral Studies for acceptance, the dissertation entitled:Computational single-image high dynamic range imagingsubmitted by Mushfiqur Rouf in partial fulfillment of the requirements forthe degree of Doctor of Philosophyin Computer ScienceExamining Committee:Rabab K. Ward, Electrical and Computer EngineeringCo-supervisorJames Little, Computer ScienceCo-supervisorSupervisory Committee MemberWilliam Evans, Computer ScienceUniversity ExaminerRoger Tam, RadiologyUniversity ExaminerAdditional Supervisory Committee Members:Jane Wang, Electrical and Computer EngineeringSupervisory Committee MemberSupervisory Committee MemberiiAbstractThis thesis proposes solutions for increasing the dynamic range (DR)—the numberof intensity levels—of a single image captured by a camera with a standard dynamicrange (SDR). The DR in a natural scene is usually too high for SDR camerasto capture, even with optimum exposure settings. The intensity values of brightobjects (highlights) that are above the maximum exposure capacity get clippeddue to sensor over-exposure, while objects that are too dark (shades) appear darkand noisy in the image. Capturing a high number of intensity levels would solvethis problem, but this is costly, as it requires the use of a camera with a highdynamic range (HDR). Reconstructing an HDR image from a single SDR imageis difficult, if not impossible, to achieve for all imaging situations. For som…
has type: Thesis/Dissertation
date issued: 2018-09
is shown at: 10.14288/1.0368721
language: eng
degree discipline: Computer Science
provider: Vancouver : University of British Columbia Library
publisher: University of British Columbia
rights: Attribution-NonCommercial-NoDerivatives 4.0 International
rights URI: http://creativecommons.org/licenses/by-nc-nd/4.0/
scholar level: Graduate
type: Text
identifier URI: http://hdl.handle.net/2429/66350