Adaptive shrinkage on dual-tree complex wavelet transform for denoising real-time MR images

• Autorzy: Venuji Renuka Simi , Reddy Edla Damodar

Identyfikatory

DOI

10.1016/j.bbe.2018.11.003

• Języki publikacji: EN

Abstrakty

EN

Performance of denoising filters which are based on the principle of wavelet thresholding greatly depends upon selection of the threshold value. An objective method is proposed in this paper for computing the optimum value of threshold in DTCWT based denoising. At optimum threshold, annoying intensity transitions of pixels in the homogeneous regions of the images, contributed by noise get completely suppressed and the true edges remain unaffected. For finding optimum value of threshold a newly derived quality metric termed as Optimum Denoising Index (ODI), which quantifies both the edge-preservation and smoothing of homogeneous regions is used. The ODI values corresponding to mean, median, Gaussian, Wiener, Bilateral, Kuwahara filters and wavelet thresholding are 0.1192±0.0118, 0.2196±0.0125, 0.1283±0.0118, 0.2106±0.0145, 0.1590±0.0331, 0.2200±0.0101 and 0.2516±0.0094, respectively. The wavelet thresholding has better edge-preservation and denoising capacity than the said denoising schemes. The ODI is highly correlated with its existing alternatives like Peak Signal to Noise Ratio (PSNR) and Structured Similarity Index Metric (SSIM) with values 0.9165 0.0536 and 0.9050 0.0452 respectively. This shows ODI is a good alternative to PSNR and SSIM.

Słowa kluczowe

EN

Dual Tree Complex Wavelet Transform; edge preservation index; edge preserved smoothing; magnetic resonance imaging; optimum denoising index; wavelet thresholding

PL

złożona transformacja falkowa; wygładzanie krawędzi; rezonans magnetyczny; próg falkowy

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2019
• Tom: Vol. 39, no. 1
• Strony: 133--147
• Opis fizyczny: Bibliogr. 23 poz., rys., tab., wykr.

Twórcy

autor

Venuji Renuka Simi

• Department of Computer Science and Engineering, National Institute of Technology, Goa,, India

autor

Reddy Edla Damodar

• Department of Computer Science and Engineering, National Institute of Technology, Goa, India

Bibliografia

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• [19] Joseph J, Sivaraman J, Periyasamy R, Simi VR. An objective method to identify optimum clip-limit and histogram specification of contrast limited adaptive histogram equalization for MR images. Biocybern Biomed Eng 2017;37 (3):489–97.
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Uwagi

PL

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).