Partial Differential Equation Methods for Image Processing with MATLAB Implementation

This book provides comprehensive MATLAB source code for implementing partial differential equation (PDE) methods in image processing. The codebase serves as both an educational tool for understanding algorithm implementation and a research foundation for advanced image analysis. The repository includes implementations of key PDE-based operations such as edge detection using gradient-based methods, image enhancement through diffusion processes, and image segmentation via active contour models. Each function contains detailed comments explaining the mathematical foundations, including discretization schemes for PDEs and numerical implementation details. The code demonstrates practical applications of variational methods, level set formulations, and anisotropic diffusion filters with parameter tuning examples. Whether you're beginning your journey in image processing or are an experienced researcher, these well-documented MATLAB implementations offer valuable resources for developing and optimizing PDE-based image processing pipelines, complete with sample datasets and performance benchmarking examples.