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» Estimating demosaicing algorithms using image noise variance
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ICIP
2009
IEEE
16 years 22 days ago
Bayesian Blind Deconvolution From Differently Exposed Image Pairs
Photographs acquired under low-light conditions require long exposure times and therefore exhibit significant blurring due to the shaking of the camera. Using shorter exposure tim...
ISBI
2009
IEEE
15 years 6 months ago
Fast Haar-Wavelet Denoising of Multidimensional Fluorescence Microscopy Data
We propose a novel denoising algorithm to reduce the Poisson noise that is typically dominant in fluorescence microscopy data. To process large datasets at a low computational co...
Florian Luisier, Cédric Vonesch, Thierry Bl...
CVPR
2009
IEEE
15 years 3 months ago
High-quality curvelet-based motion deblurring from an image pair
One promising approach to remove motion deblurring is to recover one clear image using an image pair. Existing dual-image methods require an accurate image alignment between the i...
Jian-Feng Cai, Hui Ji, Chaoqiang Liu, Zuowei Shen
ECCV
2008
Springer
16 years 1 months ago
Robust 3D Pose Estimation and Efficient 2D Region-Based Segmentation from a 3D Shape Prior
In this work, we present an approach to jointly segment a rigid object in a 2D image and estimate its 3D pose, using the knowledge of a 3D model. We naturally couple the two proces...
Samuel Dambreville, Romeil Sandhu, Anthony J. Yezz...
CVPR
2000
IEEE
16 years 1 months ago
Learning in Gibbsian Fields: How Accurate and How Fast Can It Be?
?Gibbsian fields or Markov random fields are widely used in Bayesian image analysis, but learning Gibbs models is computationally expensive. The computational complexity is pronoun...
Song Chun Zhu, Xiuwen Liu