Multiframe Superresolution Reconstruction Based on Self-Learning Method
Joint Authors
Mu, Shao-Shuo
Zhang, Ye
Jia, Ping
Yang, Xun
Qiu, Xiao-Feng
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-08-27
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
One category of the superresolution algorithms widely used in practical applications is dictionary-based superresolution algorithms, which constructs a single high-resolution (HR) and high-clarity image from multiple low-resolution (LR) images.
Despite the fact that general dictionary-based superresolution algorithms obtain redundant dictionaries from numerous HR-LR images, HR image distortion is unavoidable.
To solve this problem, this paper proposes a multiframe superresolution reconstruction based on self-learning methods.
First, multiple images from the same scene are selected to be both input and training images, and larger-scale images, which are also involved in the training set, are constructed from the learning dictionary.
Then, different larger-scale images are constructed via repetition of the first step and the initial HR sets whose scale closely approximates that of the target HR image are finally obtained.
Lastly, initial HR images are fused into one target HR image under the NLM idea, while the IBP idea is adopted to meet the global constraint.
The simulation results demonstrate that the proposed algorithm produces more accurate reconstructions than those produced by other general superresolution algorithms, while, in real scene experiments, the proposed algorithm can run well and create clearer HR images from input images captured by cameras.
American Psychological Association (APA)
Mu, Shao-Shuo& Zhang, Ye& Jia, Ping& Yang, Xun& Qiu, Xiao-Feng. 2015. Multiframe Superresolution Reconstruction Based on Self-Learning Method. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-12.
https://search.emarefa.net/detail/BIM-1073146
Modern Language Association (MLA)
Mu, Shao-Shuo…[et al.]. Multiframe Superresolution Reconstruction Based on Self-Learning Method. Mathematical Problems in Engineering No. 2015 (2015), pp.1-12.
https://search.emarefa.net/detail/BIM-1073146
American Medical Association (AMA)
Mu, Shao-Shuo& Zhang, Ye& Jia, Ping& Yang, Xun& Qiu, Xiao-Feng. Multiframe Superresolution Reconstruction Based on Self-Learning Method. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-12.
https://search.emarefa.net/detail/BIM-1073146
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1073146