Geometric Precision Correction Tool for Remote Sensing Imagery

This MATLAB-implemented program performs geometric precision correction on remote sensing imagery through polynomial transformation models. The core functionality includes three correction modes: 1) First-order polynomial correction (affine transformation) for basic rotation, translation, and scaling operations 2) Second-order polynomial correction incorporating curvature adjustments for moderate terrain distortions 3) Third-order polynomial correction handling complex nonlinear distortions in rugged terrain The implementation utilizes control point matching and least-squares estimation to compute transformation parameters. Additional image processing algorithms are integrated for pre-/post-processing tasks, including: - Defect restoration through interpolation algorithms - Noise removal using spatial and frequency domain filters - Image enhancement via histogram equalization and contrast stretching Key functions include GCP (Ground Control Point) management, transformation matrix computation, and resampling with bilinear/cubic convolution methods. This toolkit enables improved accuracy in remote sensing data analysis, supporting scientific research and practical applications with reliable geometric correction results.