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Depth of Field Rendering from Sparsely Sampled Pinhole Images
KTH, School of Electrical Engineering and Computer Science (EECS).
2020 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAlternative title
Skärpedjupsrendering från glesa nålhålsbilder (Swedish)
Abstract [en]

Optical lenses cause foreground and background objects to appear blurred, causing an effect called depth of field. Each point in the scene is projected onto the imaging plane as a semitransparent circle of confusion (CoC) with diameter depending on the distance between the point and the lens. In images rendered with a pinhole camera, the entire scene is in focus, but depth of field may be added synthetically for photorealism, aesthetics, or attention guiding purposes. However, most algorithms for depth of field rendering are either computationally expensive or produce noticeable artifacts. This report evaluates two different algorithms for depth of field rendering. Both algorithms are independent of the rendering technique. The first renders only a single pinhole image and uses a light-field based method for image synthesis. The second renders up to 12 pinhole images and uses CoC gathering to create defocus blur. Ideas from both methods are combined in a novel algorithm which uses sparse samples to approximate the light field. Our method produces a closer physical approximation than the other algorithms and avoids common artifacts. However, it may produce ghosting artifacts at low computation times. We evaluate the methods by comparing rendered images to an assumed ground truth generated with the accumulation buffer method. Physical accuracy is measured through structural similarity (SSIM) while artifacts are evaluated through visual inspection. Computation times are measured in the Inviwo software.

Abstract [sv]

Optiska linser får objekt i för- och bakgrunden att bli oskarpa i bilder. Varje punkt i scenen projiceras på bildplanet som en semitransparent oskärpecirkel (CoC) vars diameter beror på avståndet mellan punkten och linsen. I bilder renderade med nålhålskamera är hela scenen skarp men skärpedjup kan läggas till syntetiskt för fotorealism, estetik, eller i uppmärksamhetsledande syfte. Dock är många algoritmer för skärpedjupsrendering antingen resurskrävande eller präglade av artefakter. I denna rapport utvärderas två algoritmer för skärpedjupsrendering. Båda metoderna kan användas oberoende av renderingsteknik. Den första renderar endast en nålhålsbild och använder en ljusfältsbaserad metod för skärpedjupsrendering. Den andra renderar upp till 12 nålhålsbilder och använder CoC-samling för att skapa oskärpa. Idéer från båda algoritmerna kombineras i en ny metod som använder glesa nålhålsbilder för att approximera ljusfältet. Vår metod producerar bättre fysiska approximationer än de andra algoritmerna och undviker vanliga artefakter. Dock kan den orsaka spökbilder vid korta beräkningstider. Vi utvärderar metoderna genom att jämföra dem mot bilder genererade med accumulation buffer-tekniken som antas efterlikna den fysiska sanningen. Fysisk exakthet mäts med structural similarity (SSIM) och artefakter utvärderas visuellt. Beräkningstider mäts i programmet Inviwo

Place, publisher, year, edition, pages
2020. , p. 68
Series
TRITA-EECS-EX ; 2020:552
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:kth:diva-281771OAI: oai:DiVA.org:kth-281771DiVA, id: diva2:1469911
Subject / course
Computer Science
Educational program
Master of Science - Computer Science
Supervisors
Examiners
Available from: 2020-09-24 Created: 2020-09-23 Last updated: 2022-06-25Bibliographically approved

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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
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  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
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  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
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  • asciidoc
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