An Overview of Image Super-Resolution Reconstruction Algorithm

Super-resolution image reconstruction refers to the reconstruction of a clear (or multiple) high-resolution image from a low-resolution degraded image (or image sequence) of the same scene. This technology has become a research hotspot in the field of image processing. However, it is difficult to br...

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Bibliographic Details
Published in2018 11th International Symposium on Computational Intelligence and Design (ISCID) Vol. 2; pp. 16 - 18
Main Author Xiaoming Niu
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2018
Subjects
Image reconstruction
Interpolation
Markov random fields
overcomplete sparse representation
Reconstruction algorithms
Signal resolution
Spatial resolution
Super resolution
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Summary:Super-resolution image reconstruction refers to the reconstruction of a clear (or multiple) high-resolution image from a low-resolution degraded image (or image sequence) of the same scene. This technology has become a research hotspot in the field of image processing. However, it is difficult to break through the traditional method. In recent years, over-complete sparse representation has provided a new idea for the super-resolution reconstruction, and it has become a hot spot at present. Through analysing the algorithm of three aspects of super-resolution technology, this paper analyses its previous and latest research progress, and gives a outlook on the development of future super-resolution technology.
ISSN:2473-3547
DOI:10.1109/ISCID.2018.10105