Criminisi Algorithm for Color Image Inpainting

The Criminisi algorithm is a sophisticated method designed for color image inpainting. This implementation provides ready-to-run code with detailed technical documentation. The algorithm operates by leveraging both local image information and global constraints to intelligently fill missing pixels, making it particularly effective for complex color image restoration tasks. Key technical aspects include: - Priority-based patch filling mechanism that calculates confidence and data terms for optimal reconstruction - Multi-channel processing for RGB color space preservation during inpainting - Edge-aware propagation that maintains structural continuity and texture synthesis Practical applications encompass: - Noise removal and artifact elimination - Damaged region reconstruction in digital restoration - Missing detail recovery in photographic enhancement The implementation features: - Modular code structure with separate functions for priority calculation, patch selection, and texture synthesis - Parameter optimization for balancing computational efficiency and reconstruction quality - Compatibility with standard image formats through MATLAB's image processing toolbox Whether for academic research exploring computer vision techniques or practical applications in digital image restoration, this Criminisi algorithm implementation serves as a robust and reliable tool for achieving high-quality color image reconstruction. The provided code includes comprehensive comments and example usage scenarios to facilitate immediate implementation and customization.