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Yuna Jeong, Kangtae Kim and Sungkil Lee Real-Time Defocus Rendering With Level of Detail and Sub-Sample Blur Computer Graphics Forum 32

Article first published online: 25 MAR 2013 | DOI: 10.1111/cgf.12075

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This paper presents a GPU-based rendering algorithm for real-time defocus blur effects, which significantly improves the accumulation buffering. The algorithm combines three distinctive techniques: (1) adaptive discrete geometric level of detail (LOD), made popping-free by blending visibility samples across the two adjacent geometric levels; (2) adaptive visibility/shading sampling via sample reuse; (3) visibility supersampling via height-field ray casting. All the three techniques are seamlessly integrated to lower the rendering cost of smooth defocus blur with high visibility sampling rates, while maintaining most of the quality of brute-force accumulation buffering.

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