Image Mosaic Technology with Algorithm Implementation Approaches

As mentioned in the text, image mosaic technology involves matching and aligning a sequence of overlapping images, followed by resampling and synthesis to produce a new, complete, high-resolution image that encompasses a wide-angle scene containing information from all input image sequences. This technology holds significant application value across various fields including photogrammetry, computer vision, remote sensing image processing, medical image analysis, and computer graphics. Typically, the image mosaic process can be divided into three main stages: image acquisition, image registration, and image synthesis/compositing. Among these, image registration forms the foundational step of the entire mosaic pipeline. This paper examines two different image registration algorithms: feature-based registration (commonly implemented using detectors like SIFT or SURF for feature extraction and matching) and transform-domain-based registration (which operates in frequency domains using techniques like Phase Correlation or Wavelet transforms for alignment estimation).