Super-Resolution of Magnetic Resonance Images via Convex Optimization with Local and Global Prior Regularization and Spectrum Fitting
المؤلفون المشاركون
Kawamura, Naoki
Yokota, Tatsuya
Hontani, Hidekata
المصدر
International Journal of Biomedical Imaging
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-17، 17ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-09-02
دولة النشر
مصر
عدد الصفحات
17
التخصصات الرئيسية
الملخص EN
Given a low-resolution image, there are many challenges to obtain a super-resolved, high-resolution image.
Many of those approaches try to simultaneously upsample and deblur an image in signal domain.
However, the nature of the super-resolution is to restore high-frequency components in frequency domain rather than upsampling in signal domain.
In that sense, there is a close relationship between super-resolution of an image and extrapolation of the spectrum.
In this study, we propose a novel framework for super-resolution, where the high-frequency components are theoretically restored with respect to the frequency fidelities.
This framework helps to introduce multiple simultaneous regularizers in both signal and frequency domains.
Furthermore, we propose a new super-resolution model where frequency fidelity, low-rank (LR) prior, low total variation (TV) prior, and boundary prior are considered at once.
The proposed method is formulated as a convex optimization problem which can be solved by the alternating direction method of multipliers.
The proposed method is the generalized form of the multiple super-resolution methods such as TV super-resolution, LR and TV super-resolution, and the Gerchberg method.
Experimental results show the utility of the proposed method comparing with some existing methods using both simulational and practical images.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Kawamura, Naoki& Yokota, Tatsuya& Hontani, Hidekata. 2018. Super-Resolution of Magnetic Resonance Images via Convex Optimization with Local and Global Prior Regularization and Spectrum Fitting. International Journal of Biomedical Imaging،Vol. 2018, no. 2018, pp.1-17.
https://search.emarefa.net/detail/BIM-1169521
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Kawamura, Naoki…[et al.]. Super-Resolution of Magnetic Resonance Images via Convex Optimization with Local and Global Prior Regularization and Spectrum Fitting. International Journal of Biomedical Imaging No. 2018 (2018), pp.1-17.
https://search.emarefa.net/detail/BIM-1169521
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Kawamura, Naoki& Yokota, Tatsuya& Hontani, Hidekata. Super-Resolution of Magnetic Resonance Images via Convex Optimization with Local and Global Prior Regularization and Spectrum Fitting. International Journal of Biomedical Imaging. 2018. Vol. 2018, no. 2018, pp.1-17.
https://search.emarefa.net/detail/BIM-1169521
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1169521
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر