Predictive Compression of Hyperspectral Images

This resource provides a complete MATLAB implementation for predictive compression of hyperspectral images, featuring detailed explanations and step-by-step procedures. The content explores the fundamental principles and methodologies of predictive compression for hyperspectral imagery, demonstrating practical implementation using MATLAB. The implementation includes key functions for spectral prediction, residual coding, and compression optimization algorithms. Through this material, you will gain a deeper understanding of hyperspectral image predictive compression techniques and learn to perform more accurate and efficient processing in practical applications. We examine various technical approaches and algorithms, including differential pulse code modulation (DPCM) and transform-based methods, to address diverse requirements and application scenarios. The MATLAB code features spectral band prediction models, error minimization techniques, and compression ratio optimization functions. Whether you are a beginner or an experienced professional, this comprehensive guide will enhance your understanding and application of predictive compression for hyperspectral images through practical code examples and algorithmic explanations.