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Proceedings Paper

Old film image enhancements based on sub-pixel convolutional network algorithm
Author(s): Qianqian Zhang; Youdong Ding; Bing Yu; Min Xu; Chang Li
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Paper 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.

Paper Details

Date Published: 6 May 2019
PDF: 6 pages
Proc. SPIE 11069, Tenth International Conference on Graphics and Image Processing (ICGIP 2018), 110693K (6 May 2019); doi: 10.1117/12.2524338
Show Author Affiliations
Qianqian Zhang, Shanghai Univ. (China)
Youdong Ding, Shanghai Univ. (China)
Bing Yu, Shanghai Univ. (China)
Min Xu, Shanghai Univ. (China)
Chang Li, Shanghai Univ. (China)

Published in SPIE Proceedings Vol. 11069:
Tenth International Conference on Graphics and Image Processing (ICGIP 2018)
Chunming Li; Hui Yu; Zhigeng Pan; Yifei Pu, Editor(s)

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