A novel Monte Carlo noise reduction operator

Author

Xu, Ruifeng ; Pattanaik, Sumanta N.

Author_Institution

Central Florida Univ., Orlando, FL, USA

Volume

25

Issue

2

fYear

2005

Firstpage

31

Lastpage

35

Abstract

Monte Carlo noise appears as outliers and as interpixel incoherence in a typical image rendered at low sampling density. Unfortunately, none of the previous approaches can reduce both types of noise in a unified way. In this article, we propose such a unified Monte Carlo noise reduction approach using bilateral filtering. We extended the standard bilateral filtering method and built a new local adaptive noise reduction kernel. The new operator suppresses the outliers and interpixel incoherence in a noniterative way.

Keywords

Monte Carlo methods; edge detection; image denoising; image resolution; interference suppression; smoothing methods; Monte Carlo noise reduction operator; bilateral filtering; image rendering; interpixel incoherence; outlier detection; smoothing methods; Adaptive filters; Anisotropic magnetoresistance; Equations; Filtering; Image sampling; Kernel; Lighting; Monte Carlo methods; Noise reduction; Rendering (computer graphics); Monte Carlo method; bilateral filtering; global illumination; image processing; noise reduction; Algorithms; Artificial Intelligence; Computer Graphics; Image Enhancement; Image Interpretation, Computer-Assisted; Information Storage and Retrieval; Light; Models, Biological; Models, Statistical; Monte Carlo Method; Numerical Analysis, Computer-Assisted; Photometry; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Stochastic Processes; User-Computer Interface;

fLanguage

English

Journal_Title

Computer Graphics and Applications, IEEE

Publisher

ieee

ISSN

0272-1716

Type

jour

DOI

10.1109/MCG.2005.31

Filename

1405951