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» Image Processing: Principles and Applications
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CVPR
2007
IEEE
16 years 6 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...
ICIP
2006
IEEE
16 years 5 months ago
A Lifting-Based Wavelet Transform Supporting Non-Dyadic Spatial Scalability
In subband image and video compression, the issue of dyadic spatial scalability with a downsizing ratio of 2:1 has already been widely investigated. In some application scenarios,...
Ruiqin Xiong, Jizheng Xu, Feng Wu
ICIP
2006
IEEE
16 years 5 months ago
Two-Stage Optimal Component Analysis
Linear techniques are widely used to reduce the dimension of image representation spaces in applications such as image indexing and object recognition. Optimal Component Analysis ...
Yiming Wu, Xiuwen Liu, Washington Mio, Kyle A. Gal...
ICIP
2005
IEEE
16 years 5 months ago
Range-enhanced active foreground extraction
We describe a new technique that uses active scene illumination to perform foreground-background segmentation and recover partial HDR information. We explore the fact that relativ...
Asla Medeiros Sá, Marcelo Bernardes Vieira,...
ICIP
2003
IEEE
16 years 5 months ago
Evaluation strategies for automatic linguistic indexing of pictures
With the rapid technological advances in machine learning and data mining, it is now possible to train computers with hundreds of semantic concepts for the purpose of annotating i...
James Ze Wang, Jia Li, Sui Ching Lin