Raster Image and Its Deformed Counterpart with Geometric Correction

When working with a given raster image and its corresponding deformed version, the initial step requires calculating the displacement vectors at each grid intersection point. Subsequently, we can develop a geometric correction program utilizing a control grid approach. This program typically employs interpolation algorithms (such as bilinear or bicubic interpolation) to remap pixel positions from the deformed image to the corrected coordinates. The implementation would involve key functions for: 1) Grid point detection using corner detection algorithms like Harris corner detector, 2) Displacement vector calculation through point matching techniques, 3) Transformation matrix computation using least-squares estimation, and 4) Image resampling with anti-aliasing filters. This correction process adjusts the image's shape, size, and spatial alignment to better conform to expected specifications, making it particularly valuable for photogrammetry and remote sensing applications.