2002 · 50 citations · 20 references
EngineeringComputer ScienceComputer VisionDigital ImagingMachine Vision3D ReconstructionCamera GeometryCoordinate TransformationsImage RegistrationMulti-view GeometryScene ReconstructionCamera CalibrationCoordinate Frame TransformationsDistortion CompensationImage AlignmentImage Distortion CorrectionLens DistortionTransformationsTransformations In Coordinate Plane
Multiple images of a scene are related by 2D/3D view transformations and linear/nonlinear camera transformations, and when lens distortion is present none can be assumed ideal. The authors present an algorithm for true multi‑image alignment that computes an image in the ideal coordinate system while solving for the transformations relating each data image to that system, enabling alignment and mosaicing with parametric transformations even when no reference image is distortion‑free. The method models each image as intensity measurements in its own coordinate system, related to an ideal coordinate system via interior camera and exterior view transformations, and jointly estimates these transformations to produce a distortion‑free composite. The algorithm achieves key advantages—no need for a distortion‑free reference image, robust registration across extended scenes with non‑overlapping frames, and unified handling of linear and nonlinear transformations—and its application corrects lens distortion and produces video mosaics.
Multiple images of a scene are related through 2D/3D view transformations and linear and nonlinear camera transformations. We present an algorithm for true multi-image alignment that does not rely on the measurements of a reference image being distortion free. The algorithm is developed to specifically align and mosaic images using parametric transformations in the presence of lens distortion. When lens distortion is present, none of the images can be assumed to be ideal. In our formulation, all the images are modeled as intensity measurements represented in their respective coordinate systems, each of which is related to an ideal coordinate system through an interior camera transformation and an exterior view transformation. The goal of the accompanying algorithm is to compute an image in the ideal coordinate system while solving for the transformations that relate the ideal system with each of the data images. Key advantages of the technique presented in this paper are: (i) no reliance on one distortion free image, (ii) ability to register images and compute coordinate transformations even when the multiple images are of an extended scene with no overlap between the first and last frame of the sequence, and (iii) ability to handle linear and nonlinear transformations within the same framework. Results of applying the algorithm are presented for the correction of lens distortion, and creation of video mosaics.
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