Abstract
Photon mapping can simulate some special effects efficiently such as shadows and caustics. Photon mapping runs in two phases: the photon map generating phase and the radiance estimation phase. In this paper, we focus on the bandwidth selection process in the second phase, as it can affect the final quality significantly. Poor results with noise arise if few photons are collected, while bias appears if a large number of photons are collected. In order to solve this issue, we propose an adaptive radiance estimation solution to obtain trade-offs between noise and bias by changing the number of neighboring photons and the shape of the collected area according to the radiance gradient. Our approach can be applied in both the direct and the indirect illumination computation. Finally, experimental results show that our approach can produce smoother quality while keeping the high frequency features perfectly compared with the original photon mapping algorithm.
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References
Jensen H W. Global illumination using photon maps. In Rendering Techniques’96, Pueyo X, Schröder P (eds.), Springer Vienna, 1996, pp.21-30.
Jensen H W, Christensen N J. Photon maps in bidirectional Monte Carlo ray tracing of complex objects. Computers & Graphics, 1995, 19(2): 215–224.
Schjøth L, Sporring J, Olsen O F. Diffusion based photon mapping. Computer Graphics Forum, 2008, 27(8): 2114–2127.
Spencer B, Jones M W. Into the blue: Better caustics through photon relaxation. Computer Graphics Forum, 2009, 28(2): 319–328.
Spencer B, Jones M W. Photon parameterisation for robust relaxation constraints. Computer Graphics Forum, 2013, 32(2): 83–92.
Hachisuka T, Ogaki S, Jensen H W. Progressive photon mapping. ACM Transactions on Graphics (TOG), 2008, 27(5): 130:1–130:8.
Fu Z, Jensen H W. Noise reduction for progressive photon mapping. In Proc. ACM SIGGRAPH 2012 Talk, August 2012, Article No. 29.
Kaplanyan A S, Dachsbacher C. Adaptive progressive photon mapping. ACM Transactions on Graphics (TOG), 2013, 32(2): 16:1–16:13.
Myszkowski K. Lighting reconstruction using fast and adaptive density estimation techniques. In Proc. the Eurographics Workshop on Rendering Techniques, June 1997, pp.251-262.
Roland S. Bias compensation for photon maps. Computer Graphics Forum, 2003, 22(4): 729–742.
Walter B, Hubbard PM, Shirley P et al. Global illumination using local linear density estimation. ACM Transactions on Graphics (TOG), 1997, 16(3): 217–259.
Walter B. Density estimation techniques for global illumination [Ph.D. Thesis]. Cornell University, 1998.
Havran V, Bittner J, Herzog R et al. Ray maps for global illumination. In Proc. the 16th Eurographics Conference on Rendering Techniques, June 29-July 1, 2005, pp.43-54.
Kajiya J T. The rendering equation. ACM SIGGRAPH Computer Graphics, 1986, 20(4): 143–150.
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Kang, CM., Wang, L., Xu, YN. et al. Adaptive Photon Mapping Based on Gradient. J. Comput. Sci. Technol. 31, 217–224 (2016). https://doi.org/10.1007/s11390-016-1622-x
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DOI: https://doi.org/10.1007/s11390-016-1622-x