design and development of a new hybrid area and feature-based image matching method for relative orientation in close range photogrammetry

by far, many stereo-matching techniques have been successfully proposed and applied in digital aerial photogrammetry. however, due to some problems such as large parallaxes, occlusions, geometric deformations, and repetitive patterns in convergent close range images, these methods may not be applicable to the same level of success as that of aerial imagery. in order to overcome these shortcomings, in this paper a new hybrid area and feature-based image matching method is proposed. this technique, puts the emphasis on spectral information of color images without the need for prior knowledge about imaging conditions such as overlap and order of images. this method was implemented and tested on real close range images having different convergence angles. the results showed that it succeeds in convergent images with angles about 40-60 degrees giving an accuracy of 2 pixels.