Adaptive Feature Point Image Registration Algorithm with Added Spatial Constraint Model

Abstract

Image data with different spectral features contain different attribute information of a target, which is naturally complementary and can provide more comprehensive and detailed features after registration and fusion. Image registration methods based on point features have the advantages of high speed and precision, and have been widely used in visible light image registration. For registration of multiscale images and those with different spectral characteristics, the precision of these methods is affected by such factors as complex gradient variation. To this end, we add a spatial constraint model to point feature image registration, and improve the method from the aspects of feature point selection, registration, and image conversion parameter calculation. The method is applied to different types of image registration programs, and the results show that it can effectively improve the registration accuracy of multiscale images with different spectral characteristics.