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Chapter 1 Continuous Level Anisotropic Diffusion 1.1 Introduction 1.2 Anisotropic diffusion and total variation 1.3 Continuous level anisotropic diffusion 1.3.1 Local adaptive anisotropic diffusion 1.3.2 Optimization of the threshold function 1.3.3 A nonlinear evolution system for noise removal 1.4 Numerical examples 1.5 Conclusions Chapter 2 Anisotropic Diffusion for Image Reconstruction 2.1 Introduction 2.2 Total variation minimization 2.3 Adaptive dynamic combined energy reconstruction model 2.3.1 Dynamic combined energy model 2.3.2 Conjugate gradient method for model solving 2.4 Numerical experiments 2.4.1 Limited-view reconstruction 2.4.2 Limited-view reconstruction from limited angel 2.5 Conclusion Chapter 3 Anisotropic Diffusion-Based Dynamic Combined Energy Model 3.1 Introduction 3.2 Anisotropic diffusion 3.3 Dynamic Combined Energy model 3.4 Examples 3.4.1 Synthetic data examples 3.4.2 Field data examples 3.5 Lonclusion Chapter 4 Anisotropic Diffusion Model Using Variational Mode Dr 4.1 Introduction 4.2 Methods 4.2.1 Variational Mode Decomposition 4.2.2 Dynamic Combined Energy model 4.2.3 Adaptive Hybrid Diffusion model 4.3 Synthetic and field data application 4.3.1 Synthetic data example 4.3.2 Field data examples 4.4 Conclusion Chapter 5 Anisotropic Diffusion Based Low Rank Tensor Decomposition ModeI 5.1 Introduction 5.2 The proposed method 5.2.1 Model overview 5.2.2 Patch grouping 5.2.3 CP decomposition 5.2.4 Patch aggregation 5.2.5 Model solution 5.2.6 The procedure of the TDTV method 5.3 Experimental results and discussion 5.3.1 Synthetic seismic data 5.3.2 Field seismic data 5.4 Conclusion RefeFences