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» Bilevel Image Denoising Using Gaussianity Tests
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CVPR
2007
IEEE
14 years 8 months ago
Learning Gaussian Conditional Random Fields for Low-Level Vision
Markov Random Field (MRF) models are a popular tool for vision and image processing. Gaussian MRF models are particularly convenient to work with because they can be implemented u...
Marshall F. Tappen, Ce Liu, Edward H. Adelson, Wil...
ICIAP
2009
ACM
14 years 7 months ago
Nonlocal Similarity Image Filtering
Abstract. We exploit the recurrence of structures at different locations, orientations and scales in an image to perform denoising. While previous methods based on "nonlocal f...
Yifei Lou, Paolo Favaro, Stefano Soatto, Andrea L....
IH
1999
Springer
13 years 11 months ago
A Stochastic Approach to Content Adaptive Digital Image Watermarking
This paper presents a new stochastic approach which can be applied with di erent watermark techniques. The approach is based on the computation of a Noise Visibility Function NVF...
Sviatoslav Voloshynovskiy, Alexander Herrigel, Naz...
MMM
2006
Springer
154views Multimedia» more  MMM 2006»
14 years 22 days ago
A robust object shape prediction algorithm in the presence of white Gaussian noise
This paper presents a shape prediction algorithm in a noisy video sequence based on pixel representation in the undecimated wavelet domain. In our algorithm for tracking of user-d...
Mohammad Khansari, Hamid R. Rabiee, M. Asadi, M. G...
ICCV
2007
IEEE
14 years 8 months ago
Feature Preserving Image Smoothing Using a Continuous Mixture of Tensors
Many computer vision and image processing tasks require the preservation of local discontinuities, terminations and bifurcations. Denoising with feature preservation is a challeng...
Özlem N. Subakan, Bing Jian, Baba C. Vemuri, ...