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On prediction of DCT-based denoising efficiency under spatially correlated noise conditions

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Details

Original languageEnglish
Title of host publication2016 13th International Conference on Modern Problems of Radio Engineering, Telecommunications and Computer Science (TCSET)
PublisherIEEE
Pages750-754
Number of pages5
ISBN (Print)9786176078067
DOIs
Publication statusPublished - 12 Apr 2016
Publication typeA4 Article in a conference publication
EventInternational Conference on Modern Problems of Radio Engineering, Telecommunications and Computer Science -
Duration: 1 Jan 2000 → …

Conference

ConferenceInternational Conference on Modern Problems of Radio Engineering, Telecommunications and Computer Science
Period1/01/00 → …

Abstract

In this paper, results of image denoising efficiency prediction for filter based on discrete cosine transform (DCT) for the case of spatially correlated additive Gaussian Noise (SCGN) are given. The considered noise model is analyzed for different degrees of spatial correlation that produce varying non-homogeneous spectrum of the noise. PSNR metric is exploited to assess denoising efficiency. It is shown in this paper, that a prediction of denoising efficiency has high accuracy for data distorted by noise with different degrees of spatial correlation, and require low computational resources.