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A Metric for Perceptual Distancebetween Bidirectional ReflectanceDistribution Functions
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology.
2018 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Bidirectional reflectance distribution functions (BRDFs) are used in the renderingequation to simulate light reflections in physically realistic way. A reflectance metric defines distances between all possible pairs of BRDFs.  Deriving a perceptually based reflectance metric which accurately predicts how humans perceive differences in the reflective properties of surfaces has been explicitly state as an open research for over a decade. This work builds upon previous insights on the problem and combines them with new idea, defining the new Projective Area Weighted CIELAB (PAWCIELAB) metric. To evaluate the performance of the PAWCIELAB metric, it was experimentally tested against an existing state-of-the-art metric, and the results indicate that the PAWCIELAB metric is the better reflectance metric with respect to human perception. The PAWCIELAB metric is useful in any application involving humans and light reflections, for example: 3D graphics applications and quality assurance of reflectance properties in a product. There is also room for improvement and extensions of the PAWCIELAB metric, which is described in the future work section at the end of this report.

Place, publisher, year, edition, pages
2018. , p. 57
Series
UPTEC IT, ISSN 1401-5749 ; 18008
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:uu:diva-355666OAI: oai:DiVA.org:uu-355666DiVA, id: diva2:1230258
Educational program
Master of Science Programme in Information Technology Engineering
Supervisors
Examiners
Available from: 2018-07-03 Created: 2018-07-03 Last updated: 2018-07-03Bibliographically approved

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CiteExportLink to record
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