Cell-average multiresolution based on local polynomial regression. Application to image processing

作者:

Highlights:

摘要

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.

论文关键词:Generalized wavelets,Kernel methods,Statistical multiresolution,Image processing

论文评审过程:Available online 7 August 2014.

论文官网地址:https://doi.org/10.1016/j.amc.2014.07.079