Subpixel Image Registration Based on Cross-Correlation Algorithm

This program implements subpixel-level image registration through cross-correlation techniques, a registration method known for its low error and high accuracy. The algorithm operates by first detecting feature points within images and then computing cross-correlation to determine transformation relationships between images. Through subpixel interpolation techniques such as parabolic fitting or Gaussian interpolation around correlation peaks, the method achieves registration precision beyond single-pixel resolution. The implementation typically involves calculating normalized cross-correlation coefficients, identifying peak positions with pixel-level accuracy, and then applying subpixel refinement algorithms. This enhanced registration approach yields more precise alignment results, significantly improving registration accuracy. Such registration methods are widely applied in computer vision, remote sensing image processing, and related fields, holding substantial practical value for applications requiring high-precision image alignment.