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A method for predicting DCT-based denoising efficiency for grayscale images corrupted by AWGN and additive spatially correlated noise

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


Original languageEnglish
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
ISBN (Print)9781628414899
Publication statusPublished - 2015
Publication typeA4 Article in a conference publication
EventIS&T/SPIE Electronic Imaging / Image Processing: Algorithms and Systems -
Duration: 1 Jan 1900 → …


ConferenceIS&T/SPIE Electronic Imaging / Image Processing: Algorithms and Systems
Period1/01/00 → …


Results of denoising based on discrete cosine transform for a wide class of images corrupted by additive noise are obtained. Three types of noise are analyzed: additive white Gaussian noise and additive spatially correlated Gaussian noise with middle and high correlation levels. TID2013 image database and some additional images are taken as test images. Conventional DCT filter and BM3D are used as denoising techniques. Denoising efficiency is described by PSNR and PSNR-HVS-M metrics. Within hard-thresholding denoising mechanism, DCT-spectrum coefficient statistics are used to characterize images and, subsequently, denoising efficiency for them. Results of denoising efficiency are fitted for such statistics and efficient approximations are obtained. It is shown that the obtained approximations provide high accuracy of prediction of denoising efficiency.


  • DCT and BM3D filter, Denoising, Fitting, Grayscale images, Prediction

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