A Novel Monte Carlo Noise Reduction Operator

A novel Monte Carlo noise reduction operator is proposed in this paper. We apply and extend the standard bilateral filtering method and build a new local adaptive noise reduction kernel. It first computes an initial estimate for the value of each pixel, and then applies bilateral filtering using this initial estimate in its range filter kernel. It is simple both in formulation and implementation. The new operator is robust and fast in the sense that it can suppress the outliers, as well as the inter-pixel incoherence in a non-iterative way. It can be easily integrated into existing rendering systems as a post-processing step. The results of our approach are compared with those of other methods. A GPU implementation of our algorithm runs in 500ms for a 512

• Type: Journal
• Year: 2005
• Where: CGA
• Authors: Ruifeng Xu, Sumanta N. Pattanaik
• Keywords: Bilateral Filtering, CGA 2005, Computational Geometry, Initial Estimate, Noise Reduction