A Combined PDE and Texture Synthesis Approach to Inpainting 1st edition by Harald Grossauer ISBN 3540219835 9783540219835

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Product details:

ISBN 10:       3540219835
ISBN 13: 978-3540219835
Author:         Harald Grossauer
 

A Combined PDE and Texture Synthesis Approach to Inpainting 1st  Table of contents:

• Introduction

  • 1.1 Background and Motivation
  • 1.2 Overview of Image Inpainting
  • 1.3 Challenges in Inpainting Missing Regions
  • 1.4 Goals of Combining PDE and Texture Synthesis
  • 1.5 Structure of the Paper

• Related Work

  • 2.1 Traditional PDE-Based Inpainting Approaches
  • 2.2 Texture Synthesis Techniques for Image Completion
  • 2.3 Hybrid Approaches to Inpainting
  • 2.4 Comparisons of PDE and Texture-Based Methods
  • 2.5 Limitations of Existing Inpainting Methods

• Fundamentals of PDE-Based Inpainting

  • 3.1 Introduction to Partial Differential Equations (PDEs)
  • 3.2 PDEs for Image Reconstruction and Diffusion
  • 3.3 The Role of PDEs in Edge Preservation and Smoothness
  • 3.4 Examples of PDE Models for Inpainting
  • 3.5 Numerical Methods for Solving PDEs in Inpainting

• Texture Synthesis for Inpainting

  • 4.1 Introduction to Texture Synthesis
  • 4.2 Methods for Seamless Texture Filling
  • 4.3 Statistical Models of Texture and Their Applications
  • 4.4 Challenges in Texture Synthesis for Inpainting
  • 4.5 Texture Synthesis Algorithms for Realistic Patch Completion

• Combining PDE and Texture Synthesis for Inpainting

  • 5.1 Motivation for Hybrid Approaches
  • 5.2 Integrating PDE-Based Diffusion with Texture Synthesis
  • 5.3 Algorithm Design: PDE for Global Structure, Texture Synthesis for Detail
  • 5.4 Hybrid Method for Inpainting Missing Regions
  • 5.5 Balancing Global Consistency and Local Realism in Inpainting

• Algorithm Implementation

  • 6.1 Preprocessing and Initialization
  • 6.2 Step-by-Step Inpainting Process Using PDEs and Texture Synthesis
  • 6.3 Computational Complexity and Efficiency Considerations
  • 6.4 Handling Boundary Conditions and Seamless Transitions
  • 6.5 Practical Implementation Details

• Experimental Setup and Evaluation

  • 7.1 Datasets and Test Images
  • 7.2 Evaluation Metrics: Structural Similarity, Visual Quality, and Computational Efficiency
  • 7.3 Benchmarking the Combined Approach with Other Inpainting Techniques
  • 7.4 Results from Numerical Simulations and Image Inpainting Experiments
  • 7.5 Comparative Analysis: PDE + Texture vs. Standalone PDE and Texture Approaches

• Results and Discussion

  • 8.1 Visual Results: Comparison with State-of-the-Art Inpainting Methods
  • 8.2 Impact of PDE Diffusion on Image Smoothness and Edge Preservation
  • 8.3 Contribution of Texture Synthesis to Realism and Detail Recovery
  • 8.4 Discussion on Performance in Different Inpainting Scenarios
  • 8.5 Analysis of Inpainting Quality in Terms of Missing Region Size and Complexity

• Applications

  • 9.1 Image Restoration and Recovery
  • 9.2 Artistic Image Editing and Digital Content Creation
  • 9.3 Medical Imaging and Diagnostics
  • 9.4 Object Removal and Scene Reconstruction
  • 9.5 Applications in Film and Visual Effects Industry

• Challenges and Future Directions

  • 10.1 Improving Seamless Integration of PDE and Texture Synthesis
  • 10.2 Addressing Large Missing Regions and Complex Textures
  • 10.3 Real-Time Inpainting Algorithms for Video Processing
  • 10.4 Machine Learning Approaches for Enhanced Inpainting
  • 10.5 Future Research Directions in Hybrid Inpainting Techniques

• Conclusion

  • 11.1 Summary of Contributions and Key Findings
  • 11.2 Practical Implications of the Combined PDE and Texture Approach
  • 11.3 Closing Remarks and Future Work

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