A5100769930- Image and Signal Denoising Methods
- Advanced Image Processing Techniques
- Advanced Image Fusion Techniques
- Advanced Vision and Imaging
- Imbalanced Data Classification Techniques
- Sparse and Compressive Sensing Techniques
- Image Processing Techniques and Applications
- Cybercrime and Law Enforcement Studies
- Corruption and Economic Development
- Numerical methods in inverse problems
- Medical Image Segmentation Techniques
State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering
2016-2018
Hohai University
2015-2018
This paper proposes a new variational model for joint multiplicative denoising and deblurring. It combines total generalized variation filter (which has been proved to be able reduce the blocky-effects by being aware of high-order smoothness) shearlet transform (that effectively preserves anisotropic image features such as sharp edges, curves so on). The takes advantage both regularizers since it is minimize staircase effects while preserving textures other fine details. existence uniqueness...
Minimization functionals related to Euler’s elastica energy has a broad range of applications in computer vision and image processing. This paper proposes novel curvature-based variational model for restoration corrupted with multiplicative noise. It combines curvature Weberized total variation (TV) regularization gets TV-based minimization functional. The combined approach this can preserve edges while reducing the blocky effect smooth regions. implicit gradient descent scheme is applied...
The total variation (TV) denoising method is a PDE-based technique that preserves the edges well but has undesirable staircase effect in some cases, namely, translation of smooth regions (ramps) into piecewise constant (stairs). This paper introduces novel mesh-free approach using TV (ROF model) regularization and radial basis function (RBF) for numerical approximation TV-based model to remove additive noise from measurements. structured on local collocation multiquadric function. These...
This paper introduces a fractional order total variation (FOTV) based model with three different weights in the derivative definition for multiplicative noise removal purpose. The fractional-order Euler Lagrange equation which is highly non-linear partial differential (PDE) obtained by minimization of energy functional image restoration. Two numerical schemes namely an iterative scheme on dual theory and majorization-- algorithm (MMA) are used. To improve restoration results, we opt adaptive...
Multiplicative noise based on Total Variation (TV) regularization has been widely researched in many image processing applications, such as Synthetic Aperture Radar (SAR) images, Ultrasound imaging, single particle emission-computed tomography etc. In problems, the is multiplied to original rather than added image. Usually logarithmic amplification used transfer multiplicative classical additive problem. Then this problem solved by ROF model. paper we develop a new model for with modified...