A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image selective smoothing and edge detection by nonlinear diffusion
SIAM Journal on Numerical Analysis
Removing Noise and Preserving Details with Relaxed Median Filters
Journal of Mathematical Imaging and Vision
Image restoration combining a total variational filter and a fourth-order filter
Journal of Visual Communication and Image Representation
An Improved Hybrid Model for Molecular Image Denoising
Journal of Mathematical Imaging and Vision
Feature Extraction & Image Processing, Second Edition
Feature Extraction & Image Processing, Second Edition
Behavioral analysis of anisotropic diffusion in image processing
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Fourth-order partial differential equations for noise removal
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
An Anisotropic Fourth-Order Partial Differential Equation for Noise Removal
SSVM '09 Proceedings of the Second International Conference on Scale Space and Variational Methods in Computer Vision
An Anisotropic Fourth-Order Diffusion Filter for Image Noise Removal
International Journal of Computer Vision
Two Enhanced Fourth Order Diffusion Models for Image Denoising
Journal of Mathematical Imaging and Vision
Fourth-order variational model with local-constraints for denoising images with textures
International Journal of Computational Vision and Robotics
Shock coupled fourth-order diffusion for image enhancement
Computers and Electrical Engineering
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Denoising methods based on using fourth-order partial deferential equations (PDEs) are providing a good combination of the noise smoothing and the edge preservation without creating blocky effects on the smooth regions of the image. However, finding an optimal choice of model parameters for numerical solver of these techniques is a challenging problem and generally, these model parameters are image-content dependent. In this paper, a hybrid fourth-order PDE-based filter is proposed so that it does not need a manual adjustment of the model parameters. It is shown that by setting the numerical solver of proposed filter for operation at a minor time step-size derived under a data-independent stability condition, the filter can still provide a significantly fast convergence rate. Therefore, the model parameters are reduced to one parameter estimated by using a well-studied mechanism applying in the second-order nonlinear diffusion denoising techniques. Simulation results show that the proposed method can provide a denoised image with higher quality in comparison with that of the existing methods.