Paper
6 May 2019 Old film image enhancements based on sub-pixel convolutional network algorithm
Qianqian Zhang, Youdong Ding, Bing Yu, Min Xu, Chang Li
Author Affiliations +
Proceedings Volume 11069, Tenth International Conference on Graphics and Image Processing (ICGIP 2018); 110693K (2019) https://doi.org/10.1117/12.2524338
Event: Tenth International Conference on Graphic and Image Processing (ICGIP 2018), 2018, Chengdu, China
Abstract
Due to the underdeveloped scanning technology, some old movie films are scanned in digital format with lower resolution, which does not meet the viewing needs of contemporary viewers. Therefore, it is necessary to superresolution processing them to improve the image quality. However, some old movies will appear blurred after scanning. In this case, the existing algorithm super-resolution reconstruction results are often not ideal. This paper adds image deblurring pre-processing before the super-resolution processing. First, the old movie is deblurred according to the deblurring generation training model against the network, and then the image is super-resolution processed by the sub-pixel convolution network. The method aims to improve the problem that the repair effect caused by the image blur caused by the old film in the super-resolution reconstruction is not ideal.
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Qianqian Zhang, Youdong Ding, Bing Yu, Min Xu, and Chang Li "Old film image enhancements based on sub-pixel convolutional network algorithm", Proc. SPIE 11069, Tenth International Conference on Graphics and Image Processing (ICGIP 2018), 110693K (6 May 2019); https://doi.org/10.1117/12.2524338
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
Super resolution

Image processing

Lawrencium

Convolution

Data modeling

Image resolution

Fuzzy logic

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