An Intensity-augmented Ordinal Measure for Visual Correspondence

Determining the correspondence of image patches is one of the most important problems in Computer Vision. When the intensity space is variant due to several factors such as the camera gain or gamma correction, one needs methods that are robust to such transformations. While the most common assumption is that of a linear transformation, a more general assumption is that the change is monotonic. Therefore, methods have been developed previously that work on the rankings between different pixels as opposed to the intensities themselves. In this paper, we develop a new matching method that improves upon existing methods by using a combination of intensity and rank information. The method considers the difference in the intensities of the changed pixels in order to achieve greater robustness to Gaussian noise. Furthermore, only uncorrelated order changes are considered, which makes the method robust to changes in a single or a few pixels. These properties make the algorithm quite robust to different types of noise and other artifacts such as camera shake or image compression. Experiments illustrate the potential of the approach in several different applications such as change detection and feature matching.