Overview of traditional denoising and deep learning-based denoising

Jian Wen; Jianfei Shao; Jianlong Shao; Hongfei Pu

doi:10.1117/12.2644503

10 November 2022 Overview of traditional denoising and deep learning-based denoising

Jian Wen, Jianfei Shao, Jianlong Shao, Hongfei Pu

Proceedings Volume 12301, 6th International Conference on Mechatronics and Intelligent Robotics (ICMIR2022); 123011Q (2022) https://doi.org/10.1117/12.2644503
Event: 6th International Conference on Mechatronics and Intelligent Robotics, 2022, Kunming, China

Abstract

Image denoising is a classical problem in the current field of computer vision. The goal of the task of image denoising is to use techniques to preserve as much clear detail of the original image as possible when the image has external noise. The essence of the image denoising process is to reduce the noise in the digital image and to recover and reconstruct the original clear image. The reason for image noise is that during image transmission and acquisition, the integrity of the image cannot be guaranteed due to environmental, acquisition equipment, human and other factors, so the image will inevitably be damaged by different degrees of noise. In medical, military, and optoelectronics fields, there is an extremely high demand for image realism, so the task of image denoising becomes very important. In this paper, we will discuss a history of image denoising techniques and analyze the denoising methods into traditional denoising and deep learning based denoising.

Citation Download Citation

Jian Wen, Jianfei Shao, Jianlong Shao, and Hongfei Pu "Overview of traditional denoising and deep learning-based denoising", Proc. SPIE 12301, 6th International Conference on Mechatronics and Intelligent Robotics (ICMIR2022), 123011Q (10 November 2022); https://doi.org/10.1117/12.2644503

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KEYWORDS

Denoising

Image filtering

Image denoising

Digital filtering

Image processing

Electronic filtering

Machine learning

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