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Comparative analysis of function approximation methods in image processing tasks

V.V. Sergeev1, V.N. Kopenkov2, A.V. Chernov2
1Image Processing Systems Institute of RAS 

2Samara State Aerospace University 

 PDF, 114 kB

Pages: 119-122.

The paper considers various nonlinear methods of multivariate regression approximation (neural networks, linear parameter functions, hierarchical approximation) as applied to image filtering problems based on a priori information in the form of a pair of images (“ideal” + “distorted”). The considered approximation methods are compared in terms of efficiency.

image processing, nonlinear method, neural network, linear parameter function, hierarchical approximation.

Sergeev VV, Kopenkov VN, Chernov AV. Comparative analysis of function approximation methods in image processing tasks. Computer Optics 2004; 26: 119-122.


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