Path traced, 16 samples using Probabilistic illumination-aware filtering
Noise removal for Monte Carlo global illumination rendering is a well known problem, and has seen significant attention from image-based filtering methods. However, many state of the art methods breakdown in the presence of high frequency features, complex lighting and materials. In this work we present a probabilistic image based noise removal and irradiance filtering framework that preserves this high frequency detail such as hard shadows and glossy reflections, and imposes no restrictions on the characteristics of the light transport or materials. We maintain per-pixel clusters of the path traced samples and, using statistics from these clusters, derive an illumination aware filtering scheme based on the discrete Poisson probability distribution. Furthermore, we filter the incident radiance of the samples, allowing us to preserve and filter across high frequency and complex textures without limiting the effectiveness of the filter.
Ian C. Doidge and Mark W. Jones.
CGI 2013, The Visual Computer 29(6-8),707-616, 2013. The final publication is available at www.springerlink.com.
This paper presents a novel approach to detecting and preserving fine illumination structure within photon maps. Data derived from each photon’s primal trajectory is encoded and used to build a high-dimensional kd-tree. Incorporation of these new parameters allows for precise differentiation between intersecting ray envelopes, thus minimizing detail degradation when combined with photon relaxation. We demonstrate how parameter-aware querying is beneficial in both detecting and removing noise. We also propose a more robust structure descriptor based on principal components analysis that better identifies anisotropic detail at the sub-kernel level.We illustrate the effectiveness of our approach in several example scenes and show significant improvements when rendering complex caustics compared to previous methods.
Ben Spencer and Mark W. Jones
Computer Graphics Forum, Volume 32, Issue 2pt1, pages 83–92, May 2013. [doi]
Best paper, Eurographics 2013.
We present an efficient ray-tracing algorithm which, for the first time, does not store any data structures when performing spatial subdivisions, and directly computes intersections inside the scene. This new algorithm is often faster than comparable ray-tracing methods at rendering dynamic scenes, and has a similar level of performance when compared to static ray-tracers. Memory management is made minimal and deterministic, which simplifies ray-tracing engineering, as spatial subdivision data structures are no longer considered in the graphics pipeline. This is possible with a modification of Whitted’s naive ray-tracing algorithm by using a divide-and-conquer approach, and by having a sufficient collection of rays in order to reduce the complexity of naive ray-tracing. In particular, the algorithm excels at spontaneously solving large Ray/Primitive intersection problems.
ACM Transactions on Graphics, Article 117, Vol. 30, No 5, October 2011.
A new rendering method that ray traces an entire row of the image at a time is introduced. This moves some of the ray tracing computations into a simplified 1D domain and reduces the memory requirements considerably. Visibility determination is performed efficiently using Hierarchical Occlusion Maps and provides faster renderings than packet ray tracing in general and OpenGL for large scenes. In addition, the algorithm shows near perfect scaling when multi-threaded and works very well with kd-trees and octrees, as implementations demonstrate. Finally, optimal rendering times are reached with trees that are an order of magnitude smaller than those required for regular ray tracing.
Ravi Prakash Kammaje and Benjamin Mora.
Proceedings of IEEE symposium on Interactive Ray-Tracing 2008, pp. 27-34.