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How many pieces can a long picture spell at most?
Technical classification of image mosaic technology
Image mosaic technology mainly includes two key links: image registration and image fusion. For the image fusion part, the algorithm is mature as a whole, because it takes less time, and the existing main methods have little difference in effect.
Image registration is the core part of the whole image mosaic technology, which is directly related to the success rate and running speed of the image mosaic algorithm, so the research on registration algorithm has been a research hotspot for many years.
At present, image registration algorithms can be basically divided into two categories: frequency domain-based methods (phase correlation method) and time domain-based methods.
Phase correlation method was first proposed by Kuglin and Hines in 1975, and it was proved that the stitching accuracy can reach 1 pixel in the case of pure two-dimensional translation, which is mostly used for the registration of aerial photos and satellite remote sensing images.
This method transforms the spliced images into frequency domain through fast Fourier transform, and then directly calculates the translation vector between the two images through the cross-power spectrum of the two images, thus realizing image registration. Because of its simplicity and accuracy, it later became one of the most promising image registration algorithms.
However, the phase correlation method generally requires a large overlap rate (usually the overlap rate between registered images is 50%). If the overlap rate is very small, it will easily lead to the wrong estimation of the translation vector, so it is difficult to achieve image registration.
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