Image super-resolution reconstruction based on dual-branch and residual network

Xuyang Zhu; Mengle Zuo; Shaohua Li; Junyang Yu

doi:10.1117/12.2640945

2 December 2022 Image super-resolution reconstruction based on dual-branch and residual network

Xuyang Zhu, Mengle Zuo, Shaohua Li, Junyang Yu

Proceedings Volume 12288, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2022); 1228808 (2022) https://doi.org/10.1117/12.2640945
Event: International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2022), 2022, Zhuhai, China

Abstract

In recent years, computer vision is more and more widely used in the field of intelligent control, and super-resolution reconstruction technology solves the problem of making the image clear. In order to solve the problem of insufficient image feature extraction and low information dissemination efficiency in the FSRCNN algorithm, this paper puts forward a dual-branch and residual network for image super-resolution reconstruction. The model designs a dual-branch feature extraction channel, expands the feature extraction channels, and improves the high-frequency information extraction ability of the input image; adopts an improved residual block to reduce the loss of information transmission. As shown in the experimental results, the peak signal-to-noise ratio (PSNR) of the Set5 dataset is 0.14dB and 0.52dB higher than that of the FSRCNN algorithm under the 2 and 3 scale factors, and the Set14 dataset is 0.13dB and 0.41dB higher respectively.

Citation Download Citation

Xuyang Zhu, Mengle Zuo, Shaohua Li, and Junyang Yu "Image super-resolution reconstruction based on dual-branch and residual network", Proc. SPIE 12288, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2022), 1228808 (2 December 2022); https://doi.org/10.1117/12.2640945

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KEYWORDS

Feature extraction

Reconstruction algorithms

Super resolution

Convolution

Image transmission

Image enhancement

Image processing

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