Ordinal Measures for Image Correspondence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Mosaicing with Super-Resolution Zoom
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
An Intensity-augmented Ordinal Measure for Visual Correspondence
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
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Pattern matching and image patches correspondence have been described in several papers. However, in most cases the results are obtained using images with high level of detail, in other words, images with useful edge information. This paper describes a method to find correspondences between images with very poor edge information -for instance a painting with a cloudless sky- and its application to reflectographic images mosaicing. Unlike other pattern matching techniques, the proposed method solves the issue of low levels of detail or lack of good information, both needed for the determination of the correspondences used by common likeness measure (cross-norm correlation), features correspondence (Harris, SUSAN) and object recognition methods. Thus, intensity-augmented ordinal measure method is used: a window-based noise-robust method to calculate matching points. This method is improved with our Point Structure Selection (PSS) procedure to select good correspondences and reject false positives.