Image inpainting with SVM-based scratch identification and fast Fourier convolution

Luotao Zhang; Xuesong Su; Wenguang Zheng; Jingzhi Gao; Xin Ruan

doi:10.1117/12.2681066

23 May 2023 Image inpainting with SVM-based scratch identification and fast Fourier convolution

Luotao Zhang, Xuesong Su, Wenguang Zheng, Jingzhi Gao, Xin Ruan

Proceedings Volume 12645, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023); 1264525 (2023) https://doi.org/10.1117/12.2681066
Event: International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023), 2023, Hangzhou, China

Abstract

Old photographs often suffer from a variety of imperfections, such as scratches, stains, and fading. Various techniques have been proposed for image restoration, including image inpainting, denoising, deblurring, and super-resolution. In this paper, we propose a novel approach to restoring such images by leveraging deep learning techniques. Specifically, to accurately identify scratches in images, we train a classification network on a large dataset of paired old and repaired photos. Additionally, we employ a Fourier convolution-based neural network to repair the damaged areas of the images. Our results show that our approach outperforms existing methods in terms of both objective metrics and visual quality. We believe that our work has the potential to preserve valuable memories and historical artifacts for future generations.

Citation Download Citation

Luotao Zhang, Xuesong Su, Wenguang Zheng, Jingzhi Gao, and Xin Ruan "Image inpainting with SVM-based scratch identification and fast Fourier convolution", Proc. SPIE 12645, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023), 1264525 (23 May 2023); https://doi.org/10.1117/12.2681066

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KEYWORDS

Feature extraction

Image restoration

Education and training

Convolution

Deep learning

Machine learning

Image quality

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