Research on image super-resolution reconstruction algorithms based on deep learning

Zhihui Zheng

doi:10.1117/12.3033706

13 June 2024 Research on image super-resolution reconstruction algorithms based on deep learning

Zhihui Zheng

Proceedings Volume 13180, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024); 131800L (2024) https://doi.org/10.1117/12.3033706
Event: International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024), 2024, Guangzhou, China

Abstract

Image super-resolution reconstruction (ISRR) can reconstruct a high-resolution image from low-resolution images, and ISRR algorithms based deep learning (DL) networks appear to be one of the most promising directions. Motivated by recent studies, this paper summarizes the ISRR algorithms based on DL, with a focus on convolutional neural network algorithms, deep residual network algorithms and other typical algorithms. Based on the above analysis, a very deep super-resolution (VDSR) algorithm is proposed, and experimental verification on the DIV2K dataset is conducted as well. Furthermore, the important highlights and prospects of DL-based ISRR algorithm innovation are introduced.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Zhihui Zheng "Research on image super-resolution reconstruction algorithms based on deep learning", Proc. SPIE 13180, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024), 131800L (13 June 2024); https://doi.org/10.1117/12.3033706

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KEYWORDS

Reconstruction algorithms

Super resolution

Evolutionary algorithms

Image restoration

Lawrencium

Algorithm development

Deep learning

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