Review of research applications of wavelet transform in the field of image processing

Yuhang Feng; Jianfei Shao; Jianlong Shao

doi:10.1117/12.2644506

10 November 2022 Review of research applications of wavelet transform in the field of image processing

Yuhang Feng, Jianfei Shao, Jianlong Shao

Proceedings Volume 12301, 6th International Conference on Mechatronics and Intelligent Robotics (ICMIR2022); 123011R (2022) https://doi.org/10.1117/12.2644506
Event: 6th International Conference on Mechatronics and Intelligent Robotics, 2022, Kunming, China

Abstract

With the arrival of the information age, we can see images in every corner of our life, and images convey a lot of information to us. But not all images are clearly visible. And the image obtained after image transmission is often more blurred than the original image or the lack of information in the image. Therefore, the image we see may have been more or less disturbed, resulting in some damage to the image. This interference is mostly composed of noise, Such as AWGN and Poisson noise and so on. Aiming at the influence of noise on the image and preserving the integrity of image information to the greatest extent after eliminating noise, wavelet threshold denoising is one of the most important methods of image denoising. It is a relatively simple and less computational wavelet denoising algorithm. This paper summarizes the related research of wavelet transform in the field of image denoising. Firstly, the general principle of wavelet threshold denoising is explained. Furthermore, three different wavelet threshold image denoising methods are described. The characteristics and problems of three kinds of wavelet threshold denoising are summarized. Finally, the prospect of wavelet transform is also given.

Citation Download Citation

Yuhang Feng, Jianfei Shao, and Jianlong Shao "Review of research applications of wavelet transform in the field of image processing", Proc. SPIE 12301, 6th International Conference on Mechatronics and Intelligent Robotics (ICMIR2022), 123011R (10 November 2022); https://doi.org/10.1117/12.2644506

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