Classic Two-Dimensional Empirical Mode Decomposition Algorithm

This represents a classic and widely-used implementation of two-dimensional empirical mode decomposition (2D EMD), specifically designed for feature extraction and decomposition from images. The algorithm employs an iterative sifting process that decomposes images into intrinsic mode functions (IMFs) with well-defined instantaneous frequency characteristics. This approach enables deeper understanding of image structures and properties while providing advanced methodologies for image analysis and processing. Through this implementation, researchers can explore hidden patterns and information within images, significantly enhancing image comprehension and interpretation capabilities. The code incorporates key functions for boundary handling, extremum identification, and envelope interpolation using techniques like radial basis functions or thin-plate splines. This robust implementation finds extensive applications in image processing, computer vision, and pattern recognition domains, serving as a powerful tool for both research and practical applications.