Published 12 issues per year
ISSN Print: 0040-2508
ISSN Online: 1943-6009
Indexed in
ON REQUIREMENTS TO ACCURACY OF NOISE VARIANCE ESTIMATION IN PREDICTION OF DCT-BASED FILTER EFFICIENCY
ABSTRACT
Several approaches to prediction of denoising efficiency for the DCT-based filters with application to single and multichannel images corrupted by different types of noise have been proposed recently. For all of them, it has been assumed that the noise characteristics are a priori and accurately known. In this paper, we analyze the influence of errors in estimated noise variance on prediction accuracy. It is shown that this influence depends upon input parameter used in prediction. Based on the analysis, requirements to accuracy of the noise variance estimation are provided.
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Rubel , Lukin , Rubel , Egiazarian , NN-Based Prediction of Sentinel-1 SAR Image Filtering Efficiency, Geosciences, 9, 7, 2019. Crossref
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Rubel Oleksii, Rubel Andrii, Lukin Vladimir, Egiazarian Karen, Blind DCT-based prediction of image denoising efficiency using neural networks, 2018 7th European Workshop on Visual Information Processing (EUVIP), 2018. Crossref