Remote Sensing Image Classification Tool

This tool is designed for remote sensing image classification applications. It accepts multiple remote sensing images as input and employs the K-means clustering algorithm to segment different terrain features through clustering analysis. The implementation achieves excellent classification and segmentation results, making it particularly useful for students and researchers working on image segmentation projects. The code is developed in MATLAB and features well-structured, readable implementation with comprehensive comments. Key aspects include: - Preprocessing of multi-band remote sensing data - Efficient K-means clustering implementation with customizable cluster numbers - Post-processing techniques for refined segmentation results - Visualization functions for result comparison and analysis We encourage users to download and utilize this tool for collaborative learning and professional development. The clear code organization facilitates easy understanding of the clustering methodology and allows for further customization.