Experimental Tutorial for the Book "Image Processing Based on Partial Differential Equations"

This material contains experimental tutorials for the book "Image Processing Based on Partial Differential Equations." The book introduces the principles and applications of PDE-based image processing methods. The tutorial focuses on implementing various PDE approaches to solve image processing problems such as image denoising (using diffusion equations), image enhancement (via shock filters), and image segmentation (with active contour models). Readers will gain hands-on experience through practical experiments and code implementation, learning to work with key PDE formulations and numerical schemes (like finite difference methods) in MATLAB or Python environments. The book provides numerous examples and case studies demonstrating algorithm implementation details, including parameter tuning and convergence analysis. Each section includes working code snippets showing how to discretize PDEs, handle boundary conditions, and visualize results. This resource serves as a valuable reference for learning and researching PDE-based image processing techniques, with practical guidance on translating mathematical models into executable code.