NDLI: Sparse representation based multi-frame image super-resolution reconstruction using adaptive weighted features

Content Provider	IET Digital Library
Author	Nandi, Debashis Karmakar, Jayashree Kumar, Amish Mandal, Mrinal Kanti
Abstract	This study presents a novel sparse-representation based multi-frame super-resolution (SR) technique to reconstruct a high-resolution (HR) frame from multiple noisy low-resolution (LR) frames by using registration in sub-pixel accuracy and adaptive weighted feature operators. First, the registration of multiple frames in sub-pixel level and the mapping of pixels from LR frames to HR grid puts more information into the reconstructed image with respect to the conventional sparse representation based single image SR technique. This improves the overall resolution of the output image. Second, the introduction of adaptive weighted feature operators in the reconstruction process has significantly improved the robustness of the algorithm to noisy input frames. Hence, from the outputs, it can be seen that the proposed method outperforms the recent techniques in terms of noise robustness even in the higher noise level in the input image. The performance of the proposed algorithm is evaluated and quantified through a set of well-defined quality metrics and compared with some recently developed techniques. The results of the proposed technique confirm the claims of the authors.
Starting Page	663
Ending Page	672
Page Count	10
ISSN	17519659
Volume Number	13
e-ISSN	17519667
Issue Number	Issue 4, Mar (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/13/4
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2018.5139
Journal	IET Image Processing
Publisher Date	2019-01-16
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Adaptive Weighted Feature Operators Adaptive Weighted Features Computer Vision And Image Processing Technique Feature Extraction High-resolution Frame Image Reconstruction Image Registration Image Representation Image Resolution Low-resolution Frames LR Frames Multiframe Image Super-resolution Reconstruction Noisy Input Frames Optical, Image And Video Signal Processing Reconstructed Image Single Image SR Technique Sparse Representation Sub-pixel Accuracy Sub-pixel Level
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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