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Evaluating Different Spatial Anti Aliasing Techniques
KTH, School of Computer Science and Communication (CSC).
2017 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAlternative title
Utvärdering av olika Spatial Anti Aliasing tekniker (Swedish)
Abstract [sv]

 Aliasing är en bieffekt som förekommer när man mäter olika signaler. Inom datorgrafik förekommer det när objekt blir renderade på skärmen och man kan då upptäcka tydliga ojämna och hackiga kanter. Denna uppsats siktar på att hitta en kompromiss mellan prestanda och kvalitet när man använder olika anti aliasing tekniker inom en realtids 3D miljö. För att uppnå detta har flera olika anti aliasing tekniker testats på en mängd olika 3D miljöer samt har en undersökning gjorts angående människors preferenser inom bild kvalitet när dom är blint presenterade olika val. Uppsatsen lyckades och efter en grundlig analys av dom insamlade resultaten kan dra slutsatsen att MSAAx4 eller FXAA är det bästa valet när man använder en dator med begränsade resurer.

Abstract [en]

Aliasing, a commonly found phenomenon in sound engineering, is an effect that causes different signals to become indistinguishable when sampled. In computer graphics, it occurs when a picture is processed through the rendering pipeline and finally reconstructed. The reconstruction, performed by a display for example - will differ from the originally intended image as aliasing artifacts can be seen. ‘Jagged’ is an informal name for the artifacts in raster images that appear from aliasing. Aliasing is not to be confused with compression artifacts as these occur due to lossy compression. Spatial anti aliasing, the primary focus of this thesis, is a collection of techniques used to minimizing the alias distortion artifacts when representing a high-resolution image on a lower resolution screen. In computer graphics, anti aliasing is generally used to improve the appearance of polygon edges so that they do not appear jagged and instead are smoothed out on the screen.

Place, publisher, year, edition, pages
2017. , p. 30
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:kth:diva-208411OAI: oai:DiVA.org:kth-208411DiVA, id: diva2:1106244
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Available from: 2017-06-19 Created: 2017-06-07 Last updated: 2018-01-13Bibliographically approved

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