Partial Differential Equations-Based Iterative Denoising Algorithm for Movie Images
Film video noise can usually be defined as the error information visible on the video image, caused by the digital signal system. This distortion is inevitably present in the video obtained by various camera equipment. Noise reduction techniques are important preprocessing processes in many video pr...
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Wiley
2021-01-01
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| Series: | Advances in Mathematical Physics |
| Online Access: | http://dx.doi.org/10.1155/2021/8176746 |
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| author | Pingli Sun Chenxia Wang Min Li Lanqi Liu |
| author_facet | Pingli Sun Chenxia Wang Min Li Lanqi Liu |
| author_sort | Pingli Sun |
| collection | DOAJ |
| description | Film video noise can usually be defined as the error information visible on the video image, caused by the digital signal system. This distortion is inevitably present in the video obtained by various camera equipment. Noise reduction techniques are important preprocessing processes in many video processing applications, and its main goal is to reduce the noise contained in a video image while preserving as much of its edge and texture information as possible. In this paper, we describe in detail the principles of the space-time noise reduction filter, propose a 3D-filter algorithm for Gaussian noise, an improved 3D-filter algorithm based on the 3D-BDP (bloom-deep-split) filter for mixed noise, and a filter algorithm for luminance and color noise in low-brightness scenes. By dissecting the partial differential equation (PDE) denoising process, we establish a new iterative denoising algorithm. The partial differential equation method can be considered as the iterative denoising of the filter, and the first stage of the new algorithm uses wavelet-domain adaptive Wiener filter as the filtering base and achieves good results by adjusting the parameters. The proposed model in this paper is compared with the existing denoising model, and the analysis results show that the model proposed in this section can effectively remove multiplicative noise. The experimental report shows that the parameters set by the algorithm have some stability and can achieve good processing results for multiple images, which is an advantage over the partial differential equation method for denoising. The second stage of the algorithm uses the appropriate partial differential equation method to remove the pseudo-Gibbs in the first stage, which further improves the performance of the algorithm. After the image containing Gaussian noise is processed by the new algorithm, the pseudo-Gibbs effect, which often occurs in wavelet denoising, is eliminated, and the step effect, which occurs in partial differential equation denoising, is avoided; the details are better preserved, and the peak signal-to-noise ratio is improved, and a large number of experiments show that it is an effective denoising method. |
| format | Article |
| id | doaj-art-3feb21be79b64fbba0a79eaef384531d |
| institution | DOAJ |
| issn | 1687-9120 1687-9139 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Mathematical Physics |
| spelling | doaj-art-3feb21be79b64fbba0a79eaef384531d2025-08-20T02:39:12ZengWileyAdvances in Mathematical Physics1687-91201687-91392021-01-01202110.1155/2021/81767468176746Partial Differential Equations-Based Iterative Denoising Algorithm for Movie ImagesPingli Sun0Chenxia Wang1Min Li2Lanqi Liu3Department of Education and Teaching, Zhengzhou Preschool Education College, Zhengzhou, Henan 450000, ChinaDepartment of Education and Teaching, Zhengzhou Preschool Education College, Zhengzhou, Henan 450000, ChinaDepartment of Science Teaching, Zhengzhou Preschool Education College, Zhengzhou, Henan 450000, ChinaSchool of Law, Henan University of Economics and Law, Zhengzhou, Henan 450000, ChinaFilm video noise can usually be defined as the error information visible on the video image, caused by the digital signal system. This distortion is inevitably present in the video obtained by various camera equipment. Noise reduction techniques are important preprocessing processes in many video processing applications, and its main goal is to reduce the noise contained in a video image while preserving as much of its edge and texture information as possible. In this paper, we describe in detail the principles of the space-time noise reduction filter, propose a 3D-filter algorithm for Gaussian noise, an improved 3D-filter algorithm based on the 3D-BDP (bloom-deep-split) filter for mixed noise, and a filter algorithm for luminance and color noise in low-brightness scenes. By dissecting the partial differential equation (PDE) denoising process, we establish a new iterative denoising algorithm. The partial differential equation method can be considered as the iterative denoising of the filter, and the first stage of the new algorithm uses wavelet-domain adaptive Wiener filter as the filtering base and achieves good results by adjusting the parameters. The proposed model in this paper is compared with the existing denoising model, and the analysis results show that the model proposed in this section can effectively remove multiplicative noise. The experimental report shows that the parameters set by the algorithm have some stability and can achieve good processing results for multiple images, which is an advantage over the partial differential equation method for denoising. The second stage of the algorithm uses the appropriate partial differential equation method to remove the pseudo-Gibbs in the first stage, which further improves the performance of the algorithm. After the image containing Gaussian noise is processed by the new algorithm, the pseudo-Gibbs effect, which often occurs in wavelet denoising, is eliminated, and the step effect, which occurs in partial differential equation denoising, is avoided; the details are better preserved, and the peak signal-to-noise ratio is improved, and a large number of experiments show that it is an effective denoising method.http://dx.doi.org/10.1155/2021/8176746 |
| spellingShingle | Pingli Sun Chenxia Wang Min Li Lanqi Liu Partial Differential Equations-Based Iterative Denoising Algorithm for Movie Images Advances in Mathematical Physics |
| title | Partial Differential Equations-Based Iterative Denoising Algorithm for Movie Images |
| title_full | Partial Differential Equations-Based Iterative Denoising Algorithm for Movie Images |
| title_fullStr | Partial Differential Equations-Based Iterative Denoising Algorithm for Movie Images |
| title_full_unstemmed | Partial Differential Equations-Based Iterative Denoising Algorithm for Movie Images |
| title_short | Partial Differential Equations-Based Iterative Denoising Algorithm for Movie Images |
| title_sort | partial differential equations based iterative denoising algorithm for movie images |
| url | http://dx.doi.org/10.1155/2021/8176746 |
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