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» A Stochastic Grammar of Images
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GRAPHICSINTERFACE
2003
13 years 9 months ago
Entropy-based Adaptive Sampling
Ray tracing techniques need supersampling to reduce aliasing and/or noise in the final image. Since not all the pixels in the image require the same number of rays, supersampling...
Jaume Rigau, Miquel Feixas, Mateu Sbert
TOG
2012
178views Communications» more  TOG 2012»
11 years 10 months ago
Reconstructing the indirect light field for global illumination
Stochastic techniques for rendering indirect illumination suffer from noise due to the variance in the integrand. In this paper, we describe a general reconstruction technique tha...
Jaakko Lehtinen, Timo Aila, Samuli Laine, Fr&eacut...
ICPR
2008
IEEE
14 years 8 months ago
An adaptive Monte Carlo approach to nonlinear image denoising
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...
ICPR
2004
IEEE
14 years 8 months ago
Image and Feature Co-Clustering
The visual appearance of an image is closely associated with its low-level features. Identifying the set of features that best characterizes the image is useful for tasks such as ...
Guoping Qiu
MICCAI
2006
Springer
14 years 8 months ago
Limits on Estimating the Width of Thin Tubular Structures in 3D Images
This work studies limits on estimating the width of thin tubular structures in 3D images. Based on nonlinear estimation theory we analyze the minimal stochastic error of estimating...
Karl Rohr, Stefan Wörz