Accurate depth-of-field rendering using adaptive bilateral depth filtering

Authors:
Shang Wu;Kai Yu;Bin Sheng;Feiyue Huang;Feng Gao;Lizhuang Ma
Affiliations:
Department of Computer Science and Engineering, Shanghai Jiao Tong University, China;Department of Computer Science and Engineering, Shanghai Jiao Tong University, China;Department of Computer Science and Engineering, Shanghai Jiao Tong University, China,State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, China;Tencent Research, Shanghai, China;Tencent Research, Shanghai, China;Department of Computer Science and Engineering, Shanghai Jiao Tong University, China
Venue:
CVM'12 Proceedings of the First international conference on Computational Visual Media
Year:
2012

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Abstract

Real-time depth of field (DoF) rendering is crucial to realistic image synthesis and VR applications. This paper presents a new method to simulate the depth-of-field effects with bilateral depth filtering. Unlike the traditional rendering methods that handle the depth-of-field with Gaussian filtering, we develop a new DoF filter, called adaptive bilateral depth filter, to adaptively postfilter the pixels according to their depth variance. Depth information is used to focus on the objects with edge-preserving property. Our approach can eliminate the artifacts of intensity leakage, which can generate adaptive high-quality DoF rendering effects dynamically, and can be fully implemented in GPU parallelization.