SAR Image Change Detection Code with Difference Map and Ratio Map Fusion

This implementation provides SAR image change detection code based on the fusion of difference maps and ratio maps. The algorithm processes multi-temporal SAR images by generating both difference maps (capturing amplitude changes) and ratio maps (highlighting multiplicative changes), then fuses these complementary representations using optimized weighting schemes. The core functionality includes pre-processing steps like speckle filtering, co-registration of temporal images, and statistical analysis of change patterns. The code enables researchers to efficiently detect and analyze changes in SAR imagery, helping identify terrain modifications, environmental changes, or anthropogenic activities. Built on advanced change detection algorithms, it ensures high accuracy through adaptive thresholding techniques and robust decision fusion mechanisms. Users can customize parameters such as fusion weights, threshold levels, and filtering options to adapt to specific datasets and application requirements. The implementation includes comprehensive documentation with example datasets demonstrating urban change monitoring, deforestation detection, and flood mapping applications. The modular code structure allows easy integration of additional preprocessing modules or alternative fusion strategies. Whether for academic research or practical applications like disaster assessment and land use monitoring, this toolbox provides reliable change detection capabilities with detailed performance metrics and visualization outputs.