A Variational Bayesian Superresolution Approach Using Adaptive Image Prior Model
المؤلفون المشاركون
Zhao, Shengrong
Jin, Renchao
Xu, Xiangyang
Song, Enmin
Hung, Chih-Cheng
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2015، العدد 2015 (31 ديسمبر/كانون الأول 2015)، ص ص. 1-13، 13ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2015-10-05
دولة النشر
مصر
عدد الصفحات
13
التخصصات الرئيسية
الملخص EN
The objective of superresolution is to reconstruct a high-resolution image by using the information of a set of low-resolution images.
Recently, the variational Bayesian superresolution approach has been widely used.
However, these methods cannot preserve edges well while removing noises.
For this reason, we propose a new image prior model and establish a Bayesian superresolution reconstruction algorithm.
In the proposed prior model, the degree of interaction between pixels is adjusted adaptively by an adaptive norm, which is derived based on the local image features.
Moreover, in this paper, a monotonically decreasing function is used to calculate and update the single parameter, which is used to control the severity of penalizing image gradients in the proposed prior model.
Thus, the proposed prior model is adaptive to the local image features thoroughly.
With the proposed prior model, the edge details are preserved and noises are reduced simultaneously.
A variational Bayesian inference is employed in this paper, and the formulas for calculating all the variables including the HR image, motion parameters, and hyperparameters are derived.
These variables are refined progressively in an iterative manner.
Experimental results show that the proposed SR approach is very efficient when compared to existing approaches.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Zhao, Shengrong& Jin, Renchao& Xu, Xiangyang& Song, Enmin& Hung, Chih-Cheng. 2015. A Variational Bayesian Superresolution Approach Using Adaptive Image Prior Model. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-13.
https://search.emarefa.net/detail/BIM-1073905
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Zhao, Shengrong…[et al.]. A Variational Bayesian Superresolution Approach Using Adaptive Image Prior Model. Mathematical Problems in Engineering No. 2015 (2015), pp.1-13.
https://search.emarefa.net/detail/BIM-1073905
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Zhao, Shengrong& Jin, Renchao& Xu, Xiangyang& Song, Enmin& Hung, Chih-Cheng. A Variational Bayesian Superresolution Approach Using Adaptive Image Prior Model. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-13.
https://search.emarefa.net/detail/BIM-1073905
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1073905
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