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Cell-average multiresolution based on local polynomial regression. Application to image processing
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DOI：10.1016/j.amc.2014.07.079.png)
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Abstract
En 中文
In Harten (1996) [32] presented a general framework about multiresolution representation based on four principal operators: decimation and prediction, discretization and reconstruction. The discretization operator indicates the nature of the data. In this work the pixels of a digital image are obtained as the average of a function in some defined cells, A family of Harten cell-average multiresolution schemes based on local polynomial regression is presented. The stability is ensured by the linearity of the operators obtained and the order is calculated. Some numerical experiments are performed testing the accuracy of the prediction operators in comparison with the classical linear and nonlinear methods. (C) 2014 Elsevier Inc. All rights reserved.
Keywords:
Generalized wavelets
Kernel methods
Statistical multiresolution
Image processing
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