Open AccessNon‐local feature back‐projection for image super‐resolution
Author(s) -
Zhang Xin,
Liu Qian,
Li Xuemei,
Zhou Yuanfeng,
Zhang Caiming
Publication year - 2016
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2015.0467
Subject(s) - interpolation (computer graphics) , artificial intelligence , feature (linguistics) , computer vision , computer science , projection (relational algebra) , ringing artifacts , image resolution , image (mathematics) , feature detection (computer vision) , image processing , image restoration , iterative reconstruction , noise (video) , process (computing) , pattern recognition (psychology) , algorithm , philosophy , linguistics , operating system
Image super‐resolution (SR) for a single low‐resolution image is an important and challenging task in image processing. In this study, the authors propose a novel non‐local feature back‐projection method for image SR, which can effectively reduce jaggy and ringing artefacts common, in general, iterative back‐projection (IBP) method. In their method, the objective high‐resolution (HR) image is obtained by projecting reconstructed errors back to HR image iteratively. To optimise the initial HR image and constrain anisotropic errors propagation during IBP process, an efficient non‐local feature interpolation algorithm is designed. Specially, edge information is used as constraints to make the interpolation surface preserve better shape. Furthermore, as post‐processing, non‐local similarities are utilised to remove noise and irregularities induced by errors propagation. Experimental results show that their method achieves better performance than state‐of‐the‐art methods in terms of both quantitative metrics and visual qualities.