Low noise super-resolution reconstruction algorithm based on network integration

Yanyao Guo; Qilin Bi; Tianmao Lai; Youjie Lv; Boren Chen; Huiling Tang; Shuqi Deng; Chuxin Huang

doi:10.1117/12.3038562

23 August 2024 Low noise super-resolution reconstruction algorithm based on network integration

Yanyao Guo, Qilin Bi, Tianmao Lai, Youjie Lv, Boren Chen, Huiling Tang, Shuqi Deng, Chuxin Huang

Author Affiliations +

Proceedings Volume 13250, Fourth International Conference on Image Processing and Intelligent Control (IPIC 2024); 132501N (2024) https://doi.org/10.1117/12.3038562
Event: 4th International Conference on Image Processing and Intelligent Control (IPIC 2024), 2024, Kuala Lumpur, Malaysia

Abstract

Due to the challenges associated with traditional methods in reconstructing complex water images, such as low resolution, absence of key information, and significant noise, this paper presents a network integration-based algorithm for low noise super-resolution reconstruction. In order to make the reconstructed image texture clear, the implicit neural expression of the image is applied in the traditional SRGAN algorithm. We also utilize the concept of network integration to effectively capture both the surface-level and in-depth information from the image. Experimental results indicate that the algorithm we propose outperforms the current mainstream algorithms in terms of both subjective visual effects and objective quality evaluation indicators for reconstructed images.

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

Citation Download Citation

Yanyao Guo, Qilin Bi, Tianmao Lai, Youjie Lv, Boren Chen, Huiling Tang, Shuqi Deng, and Chuxin Huang "Low noise super-resolution reconstruction algorithm based on network integration", Proc. SPIE 13250, Fourth International Conference on Image Processing and Intelligent Control (IPIC 2024), 132501N (23 August 2024); https://doi.org/10.1117/12.3038562

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