Equivalent Number of Looks for Evaluating Filtering Performance in Remote Sensing Images

The Equivalent Number of Looks (ENL) represents the filtering effectiveness in remote sensing images after noise reduction processing. By computing ENL, we can quantitatively evaluate the performance of filtering algorithms. This program facilitates ENL calculation through statistical analysis of homogeneous regions in filtered images, typically using variance-based measurements in uniform areas to gauge noise reduction levels. Filtering is a fundamental image processing technique that enhances image clarity and visibility by eliminating noise and interference. ENL serves as a critical evaluation metric that balances smoothness against detail preservation in filtered imagery. The calculation typically involves selecting uniform regions and applying the formula ENL = (mean² / variance) to measure signal-to-noise ratio improvement. Consequently, ENL computation enables objective assessment of filtering algorithm performance, supporting algorithm optimization and comparative analysis. This program is designed to streamline ENL calculation through automated region selection and statistical computation, allowing users to efficiently evaluate and compare different filtering approaches for remote sensing applications.