Adaptive Generalized Morphological Filter

This documentation provides comprehensive insights into the adaptive generalized morphological filter's implementation. The filter's core principle involves dynamically adjusting structural elements based on signal characteristics to optimize noise suppression while preserving key features. The implementation includes fundamental morphological operations: erosion (shrinking object boundaries), dilation (expanding boundaries), opening (erosion followed by dilation for noise removal), and closing (dilation followed by erosion for gap filling). The SNR calculation module evaluates filtering performance through peak signal-to-noise ratio metrics. For practical understanding, the code structure organizes these operations into modular functions with configurable parameters for structural element size and shape adaptation. Demonstration cases showcase applications in signal processing and image enhancement scenarios, such as ECG baseline wander removal or industrial image defect detection. Users can modify the adaptive threshold mechanism in the morphology.m function to customize element selection logic based on local signal statistics.