Euler’s elastica and curvature based model for image restoration

Khan, Mushtaq Ahmad; Chen, Wen; Ullah, Asmat; Lin, Jing

doi:10.1371/journal.pone.0202464

Cited by 9 publications

(4 citation statements)

References 43 publications

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“…At the same time, the nontexture-based image restoration technology also includes a variational repair method based on the image geometry model [18]. This method seeks to describe the repair process of artisans and experts using mathematical language.In addition, this technology through establishing an image prior model,transforms the problem of image defect repair into a variational problem for function extremum, e.g.,the TV model [19], Mumford-Shah model [20], Eulerelastica model [21] and Mumford-Shah-Euler model [22].…”

Section: Related Workmentioning

confidence: 99%

Image Inpainting Technique Based on Smart Terminal: A Case Study in CPS Ancient Image Data

Zhou

Wan

2019

IEEE Access

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Cyber-physical system (CPS) can intelligently feel the interactive information between data and terminal. The combination of CPS data and intelligent terminal can make terminal devices communicate with each other, coordinate operation, and share information in a complex environment. At present, the demand for smart terminal technology in university libraries and national cultural museums is also increasing. However, the data for smart terminal display and development of shared services face the problem that the original data is difficult to collect and the incomplete images are difficult to repair. In order to display the ancient books in a smart terminal, we have established a model for image inpainting through deep learning. In this paper, we set up a smart terminal display solution to display the digital protection effect of incomplete character images. Then, we propose a model based on Conditional Generative Adversarial Network (CGAN) to solve the problem of repairing incomplete character images. We put this model into the computing module and deployed it to the cloud computing platform of the smart terminal. Moreover, we construct a handwritten Yi character image data set in the cloud. To verify the CGAN calculation model, we design and construct two quality detection tests. According to the experimental results, the image inpainting quality of the CGAN is better than the traditional image restoration technology. Based on the experimental analysis and evaluation criteria, we find that the CGAN calculation model is of great significance for ancient book inpainting.INDEX TERMS CPS data, smart terminal, character image, conditional generative adversarial network.

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Section: Related Workmentioning

confidence: 99%

Image Inpainting Technique Based on Smart Terminal: A Case Study in CPS Ancient Image Data

Zhou

Wan

2019

IEEE Access

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“…In any case, it activates the indication of uplifting impact and the creation of edge artifacts. An enhanced fourth-order PDE model based on [30], [31] has been developed to deal with this issue. Several fractional-order derivative-based models were presented in [32]- [34] for Gaussian noise and multiplicative noise removal as a trade-off within the first order total variation regularized models and high order derivative based models, and thus used for super-resolution and image restoration [9].…”

Section: Introductionmentioning

confidence: 99%

A Novel Fractional-Order Variational Approach for Image Restoration Based on Fuzzy Membership Degrees

Khan¹,

Ullah

Khan

et al. 2021

IEEE Access

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We propose a new fractional-order (space and time) total variation regularized model for multiplicative noise removal in this research article. We use the regularly varying fuzzy membership degrees to characterize the likelihood of a pixel related to edges, texture regions, and flat regions to improve model efficiency. This approach is capable of maintaining edges, textures, and other image information while significantly reducing the blocky effect. We opt for the option of local actions. In order to efficiently find the minimizer of the prescribed energy function, the semi-implicit gradient descent approach is used (which derives the corresponding fractional-order Euler-Lagrange equations). The existence and uniqueness of a solution to the suggested variational model are proved. Experimental results show the efficiency of the suggested model in visual enhancement, preserving details and reducing the blocky effect while extracting noise as well as an increase in the PSNR (dB), SSIM, relative error, and less CPU time(s) comparing to other schemes. INDEX TERMS Fractional-order total variation; time and space fractional derivative; Grünwald-Letniko derivative; Caputo derivative; multiplicative noise; fuzzy membership degrees.

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“…have been used by the researchers to solve the models and to remove the multiplicative noise from the images. For more information, see [10,11,[21][22][23][24][25][26][27][28].…”

Section: Introductionmentioning

confidence: 99%

Multiquadric Radial Basis Function Approximation Scheme for Solution of Total Variation BasedMultiplicative Noise Removal Model

Khan¹,

Altamimi²,

Khan³

et al. 2021

Computer Modeling in Engineering &Amp; Sciences

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This article introduces a fast meshless algorithm for the numerical solution nonlinear partial differential equations (PDE) by Radial Basis Functions (RBFs) approximation connected with the Total Variation (TV)-based minimization functional and to show its application to image denoising containing multiplicative noise. These capabilities used within the proposed algorithm have not only the quality of image denoising, edge preservation but also the property of minimization of staircase effect which results in blocky effects in the images. It is worth mentioning that the recommended method can be easily employed for nonlinear problems due to the lack of dependence on a mesh or integration procedure. The numerical investigations and corresponding examples prove the effectiveness of the recommended algorithm regarding the robustness and visual improvement as well as peak-signal-to-noise ratio (PSNR), signal-to-noise ratio (SNR), and structural similarity index (SSIM) corresponded to the current conventional TV-based schemes.

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Euler’s elastica and curvature based model for image restoration

Cited by 9 publications

References 43 publications

Image Inpainting Technique Based on Smart Terminal: A Case Study in CPS Ancient Image Data

Image Inpainting Technique Based on Smart Terminal: A Case Study in CPS Ancient Image Data

A Novel Fractional-Order Variational Approach for Image Restoration Based on Fuzzy Membership Degrees

Multiquadric Radial Basis Function Approximation Scheme for Solution of Total Variation BasedMultiplicative Noise Removal Model

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