NDLI: Plenoptic sampling

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Plenoptic sampling

Content Provider	ACM Digital Library
Author	Chai, Jin-Xiang Chan, Shing-Chow Tong, Xin Shum, Heung-Yeung
Abstract	This paper studies the problem of plenoptic sampling in image-based rendering (IBR). From a spectral analysis of light field signals and using the sampling theorem, we mathematically derive the analytical functions to determine the minimum sampling rate for light field rendering. The spectral support of a light field signal is bounded by the minimum and maximum depths only, no matter how complicated the spectral support might be because of depth variations in the scene. The minimum sampling rate for light field rendering is obtained by compacting the replicas of the spectral support of the sampled light field within the smallest interval. Given the minimum and maximum depths, a reconstruction filter with an optimal and constant depth can be designed to achieve anti-aliased light field rendering.Plenoptic sampling goes beyond the minimum number of images needed for anti-aliased light field rendering. More significantly, it utilizes the scene depth information to determine the minimum sampling curve in the joint image and geometry space. The minimum sampling curve quantitatively describes the relationship among three key elements in IBR systems: scene complexity (geometrical and textural information), the number of image samples, and the output resolution. Therefore, plenoptic sampling bridges the gap between image-based rendering and traditional geometry-based rendering. Experimental results demonstrate the effectiveness of our approach.
Starting Page	307
Ending Page	318
Page Count	12
File Format	PDF
ISBN	1581132085
DOI	10.1145/344779.344932
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2000-07-01
Access Restriction	Subscribed
Subject Keyword	Plenoptic functions Image-based rendering Sampling Spectral analysis
Content Type	Text
Resource Type	Article

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