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Patch-Wise Adaptive Weights Smoothing in R
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DOI：10.18637/jss.v095.i06.png)
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Abstract
En 中文
Image reconstruction from noisy data has a long history of methodological development and is based on a variety of ideas. In this paper we introduce a new method called patch-wise adaptive smoothing, that extends the propagation-separation approach by using comparisons of local patches of image intensities to define local adaptive weighting schemes for an improved balance of reduced variability and bias in the reconstruction result. We present the implementation of the new method in an R package aws and demonstrate its properties on a number of examples in comparison with other state-of-the art image reconstruction methods.
Keywords:
image denoising
patch-wise structural adaptive smoothing
total variation
non-local means
R
Journal
IF:
8.1
Papers:
622
Citations:
4.6W