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SCALESPACE
1999
Springer
15 years 3 months ago
A Geometric Functional for Derivatives Approximation
We develop on estimation method, for the derivative field of an image based on Bayesian approach which is formulated in a geometric way. The Maximum probability configuration of ...
Nir A. Sochen, Robert M. Haralick, Yehoshua Y. Zee...
NIPS
2008
15 years 17 days ago
Learning with Consistency between Inductive Functions and Kernels
Regularized Least Squares (RLS) algorithms have the ability to avoid over-fitting problems and to express solutions as kernel expansions. However, we observe that the current RLS ...
Haixuan Yang, Irwin King, Michael R. Lyu
ICIP
2010
IEEE
14 years 9 months ago
Tensor-based image diffusions derived from generalizations of the Total Variation and Beltrami Functionals
We introduce a novel functional for vector-valued images that generalizes several variational methods, such as the Total Variation and Beltrami Functionals. This functional is bas...
Anastasios Roussos, Petros Maragos
ISNN
2007
Springer
15 years 5 months ago
Neural-Based Separating Method for Nonlinear Mixtures
A neural-based method for source separation in nonlinear mixture is proposed in this paper. A cost function, which consists of the mutual information and partial moments of the out...
Ying Tan
IVC
2008
83views more  IVC 2008»
14 years 11 months ago
A minimum description length objective function for groupwise non-rigid image registration
Groupwise non-rigid registration aims to find a dense correspondence across a set of images, so that analogous structures in the images are aligned. For purely automatic inter-sub...
Stephen Marsland, Carole J. Twining, Christopher J...