Image Processing Based on Partial Differential Equations

The experimental code provided in the book "Image Processing Based on Partial Differential Equations" is exceptionally comprehensive, featuring numerous interesting and practical examples. These implementations go beyond simple demonstrations by providing detailed explanations and step-by-step procedures that help readers better understand and apply image processing techniques. The codebase includes implementations of various fundamental PDE algorithms such as diffusion filters for noise reduction, edge detection operators like gradient-based methods, and advanced techniques including active contour models for image segmentation. Each implementation demonstrates key mathematical concepts through practical MATLAB or Python examples, often utilizing finite difference methods to solve the underlying partial differential equations. The book systematically covers essential image processing domains - from basic filtering operations and edge detection to sophisticated image segmentation and feature extraction methods. Both beginners and experienced image processing specialists can gain substantial theoretical knowledge and hands-on programming experience through the well-documented code examples and algorithmic explanations provided throughout the text.