NDLI: Multiframe super-resolution based on a high-order spatially weighted regularisation

Content Provider	IET Digital Library
Author	Laghrib, Amine Alahyane, Mohamed Ghazdali, Abdelghani Hakim, Abdelilah Raghay, Said
Abstract	Here, the authors propose a spatially weighted super-resolution (SR) algorithm, which takes into consideration the distribution of every information that characterise different image areas. The authors investigate to use a combined spatially weighted regularisation of the bilateral total variation and a second-order term increasing then the robustness of the proposed SR approach with respect to blur and noise degradations. In addition, the authors propose an iterative Bregman iteration algorithm to resolve the obtained optimisation SR problem. As a result, this regularisation is more efficient and easier to implement; moreover, it preserves well the smooth regions of the image and also sharp edges. Using different simulated and real tests, the authors prove the efficiency of the proposed algorithm compared to some SR methods.
Starting Page	928
Ending Page	940
Page Count	13
ISSN	17519659
Volume Number	12
e-ISSN	17519667
Issue Number	Issue 6, Jun (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/12/6
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2017.1046
Journal	IET Image Processing
Publisher Date	2018-01-08
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Bilateral Total Variation Blur Degradations Computer Vision And Image Processing Technique High-order Spatially Weighted Regularisation Image Resolution Interpolation And Function Approximation Iterative Bregman Iteration Algorithm Iterative Method Multiframe Super-resolution Noise Degradations Numerical Analysis Optical, Image And Video Signal Processing Optimisation Optimisation SR Problem Optimisation Technique Second-order Term Sharp Edge Smooth Image Region SR Algorithm
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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