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 k...
We consider the problem of optimizing the parameters of an arbitrary denoising algorithm by minimizing Stein’s Unbiased Risk Estimate (SURE) which provides a means of assessing ...
The problem of noise in Monte-Carlo rendering arising from estimator variance is well-known and well-studied. In this work, we concentrate on identifying individual light paths as...
Christopher DeCoro, Tim Weyrich, Szymon Rusinkiewi...
This paper introduces a novel stochastic approach to image denoising using an adaptive Monte Carlo scheme. Random samples are generated from the image field using a spatially-adap...
Alexander Wong, Akshaya Kumar Mishra, Paul W. Fieg...
— In a nanoscale technology, memory bits are highly susceptible to process variation induced read/write failures. To address the above problem, in this paper a new memory cell is...
Jawar Singh, Jimson Mathew, Saraju P. Mohanty, Dhi...