Objective Edge Similarity Metric for denoising applications in MR images

• Autorzy: Shanmugam Ashok , Rukmani Devi S.

Identyfikatory

DOI

10.1016/j.bbe.2020.01.012

• Języki publikacji: EN

Abstrakty

EN

Edge Similarity Metrics (ESMs) are necessary to objectively quantify the inadvertent blur at the edge pixels which occurs during denoising. They are helpful for evaluating edge-preserving capability of nonlinear filters. Most of the ESMs in literature, consider similarity of either strength of the edges or their direction individually. They lag in terms of concordance with subjective edge similarity ratings. An Objective Edge Similarity Metric (OESM) which considers all three attributes of edges; strength, direction and width together, is proposed in this paper. Pearson's Correlation shown by Gradient Magnitude Similarity Deviation (GMSD), Gradient Similarity Measure (GSM), Edge Strength Similarity Index Metric (ESSIM) and OESM with Subjective Edge Similarity Score (SESS) are ˗0.9669 ± 0.0028, 0.9566 ± 0.0053, 0.9507 ± 0.0057 and 0.9848 ± 0.0038, respectively. OESM is able to measure the degree of edge similarity between images more efficiently than GMSD, GSM and ESSIM. It reflects the perceptual edge similarity between images more accurately than GMSD, GSM and ESSIM.

Słowa kluczowe

EN

denoising; edge preserving filter; edge similarity; quality metrics

PL

odszumianie; wygładzanie krawędzi; metryka jakości

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2020
• Tom: Vol. 40, no. 1
• Strony: 574--582
• Opis fizyczny: Bibliogr. 21 poz., rys., tab., wykr.

Twórcy

autor

Shanmugam Ashok

• Department of Electronics and Communication Engineering, Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College, Chennai 600062, India

autor

Rukmani Devi S.

• Department of Electronics and Communication Engineering, R.M.D Engineering College, Kavaraipettai, Tamil Nadu, India

Bibliografia

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Uwagi

PL

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).