Predictive Coding for Images

This implementation performs predictive coding on images using Differential Pulse Code Modulation (DPCM), focusing on creating a clear and maintainable codebase. Predictive coding reduces storage requirements and transmission bandwidth by leveraging redundancy inherent in images. The DPCM scheme specifically utilizes local pixel correlations through differential encoding, achieving efficient image compression while maintaining computational simplicity. The core algorithm operates by calculating differences between actual pixel values and their predictions (typically based on neighboring pixels), then encoding these residuals. Key implementation aspects include: - Prediction model: Using left or upper neighboring pixels for current pixel prediction - Difference calculation: Subtracting predicted values from actual pixel intensities - Quantization (optional): Reducing precision of difference values for higher compression - Entropy encoding: Efficiently storing the difference values This approach significantly reduces computational complexity and memory requirements compared to traditional encoding methods. The code structure emphasizes readability with modular components for prediction, difference calculation, and encoding stages, making it ideal for educational purposes and practical applications where code maintainability is prioritized.