A Novel Nonlinear Second Order Hyperbolic Partial Differential Equation-Based Image Restoration Algorithm With Directional Diffusion

Li, Shuaijie; Zhi, Zhanjiang

doi:10.1109/access.2020.3010031

Cited by 2 publications

(3 citation statements)

References 25 publications

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“…e results are shown in Figure 5. Grayscale value of the test set True value Method of [9] e proposed method It can be found that the proposed method has high consistency with the real value. In order to quantitatively evaluate the difference between the two methods, the concept of similarity rate is introduced here, which can be summarized as the ratio of similar samples to the total number of samples.…”

Section: Algorithm and Experimental Results Analysismentioning

confidence: 98%

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Computer-Aided Mural Digital Restoration under Generalized Regression Neural Network

Liu

2022

Mathematical Problems in Engineering

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Aiming at the digital protection of classical murals and according to the method of generalized regression neural network (GRNN), a digital restoration is proposed in the paper. Firstly, the existing defect photos are processed preliminarily, including the elimination of noise, the extraction of boundary pixels of the region to be repaired, and the establishment of several small block regions centered on these pixels. Then, similar known pixel regions are found as sample pixel blocks, which are used as input samples of GRNN. Finally, the GRNN is adopted to obtain the approximate estimation function, and the adaptive smoothing parameters are introduced to obtain the pixel information of the area to be repaired. Through model prediction, by acquiring the pixel information of the area to be repaired, the damaged area of the original image can be repaired. The method proposed is compared with the traditional repair methods, the results show that the method is close to the texture structure image restoration method in peak signal-to-noise ratio, and the restoration results are in line with the expectation.

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Section: Algorithm and Experimental Results Analysismentioning

confidence: 98%

“…Detailed restoration is performed on di erent image layers. Among the nontexture-based restoration methods, the more classical ones are the nonlinear partial di erential equation method [8,9] and the total variational restoration method [10,11].…”

Section: Introductionmentioning

confidence: 99%

Computer-Aided Mural Digital Restoration under Generalized Regression Neural Network

Liu

2022

Mathematical Problems in Engineering

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“…Therefore, tourist street view image information is the main source of all kinds of information that humans come into contact with. During the acquisition or transmission of tourist street view images, due to imaging principles, sensor defects, and changes in the surrounding environment, the signal may be unstable, and noises of different intensities may be generated, resulting in degradation of the tourist street view image quality [1]. Noise can be understood as interference signals that affect the acquisition or analysis of tourist street scene images from the signal source received by people or sensors.…”

Section: Introductionmentioning

confidence: 99%

Denoising of Tourist Street Scene Image Based on ROF Model of Second-Order Partial Differential Equation

Yang

2021

Advances in Mathematical Physics

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The noise pollution in tourist street view images is caused by various reasons. A major challenge that researchers have been facing is to find a way to effectively remove noise. Although in the past few decades people have proposed many methods of denoising tourist street scene images, the research on denoising technology of tourist street scene images is still not outdated. There is no doubt that it has become a basic and important research topic in the field of digital image processing. The evolutionary diffusion method based on partial differential equations is helpful to improve the quality of noisy tourist street scene images. This method can process tourist street scene images according to people’s expected diffusion behavior. The adaptive total variation model proposed in this paper is improved on the basis of the total variation model and the Gaussian thermal diffusion model. We analyze the classic variational PDE-based denoising model and get a unified variational PDE energy functional model. We also give a detailed analysis of the diffusion performance of the total variational model and then propose an adaptive total variational diffusion model. By improving the diffusion coefficient and introducing a curvature operator that can distinguish details such as edges, it can effectively denoise the tourist street scene image, and it also has a good effect on avoiding the step effect. Through the improvement of the ROF model, the loyalty term and regular term of the model are parameterized, the adaptive total variation denoising model of this paper is established, and a detailed analysis is carried out. The experimental results show that compared with some traditional denoising models, the model in this paper can effectively suppress the step effect in the denoising process, while protecting the texture details of the edge area of the tourist street scene image. In addition, the model in this paper is superior to traditional denoising models in terms of denoising performance and texture structure protection.

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A Novel Nonlinear Second Order Hyperbolic Partial Differential Equation-Based Image Restoration Algorithm With Directional Diffusion

Cited by 2 publications

References 25 publications

Computer-Aided Mural Digital Restoration under Generalized Regression Neural Network

Computer-Aided Mural Digital Restoration under Generalized Regression Neural Network

Denoising of Tourist Street Scene Image Based on ROF Model of Second-Order Partial Differential Equation

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