Abstract
This paper considers fast and robust mosaicking of UAV images under a circumstance that each UAV images have very narrow overlaps in-between. Image transformation for image mosaicking consists of two estimations: relative transformations and global transformations. For estimating relative transformations between adjacent images, projective transformation is widely considered. For estimating global transformations, panoramic constraint is widely used. While perspective transformation is a general transformation model in 2D-2D transformation, this may not be optimal with weak stereo geometry such as images with narrow overlaps. While panoramic constraint works for reliable conversion of global transformation for panoramic image generation, this constraint is not applicable to UAV images in linear motions. For these reasons, a robust approach is investigated to generate a high quality mosaicked image from narrowly overlapped UAV images. For relative transformations, several transformation models were considered to ensure robust estimation of relative transformation relationship. Among them were perspective transformation, affine transformation, coplanar relative orientation, and relative orientation with reduced adjustment parameters. Performance evaluation for each transformation model was carried out. The experiment results showed that affine transformation and adjusted coplanar relative orientation were superior to others in terms of stability and accuracy. For global transformation, we set initial approximation by converting each relative transformation to a common transformation with respect to a reference image. In future work, we will investigate constrained relative orientation for enhancing geometric accuracy of image mosaicking and bundle adjustments of each relative transformation model for optimal global transformation.
Highlights
Image mosaicking aims to generate a seamless composite image, which is geometrically and radiometrically consistent, from a set of overlapping images
We focus on the geometric correction part for the whole image mosaicking process
The experiment results showed that affine transformation and adjusted coplanar relative orientation were superior to homography and standard coplanar relative orientation and that this tendency was remarkably appeared with narrower overlaps between strip images
Summary
Image mosaicking aims to generate a seamless composite image, which is geometrically and radiometrically consistent, from a set of overlapping images. The most accurate result can be achieved by ortho-rectification scheme using 3D terrain model of a target area This scheme generally needs image matching process or precise 3D terrain dataset. Image-to-image based geometric correction that additional information for the target area is not required can be preferred for image mosaicking In this approach, quality of a mosaicked image widely depends on accuracy of the geometric relationships and transformations among overlapping images. While the panoramic constraint works for reliable conversion of global transformation for panoramic image generation (Brown and Lowe, 2007), this constraint is not applicable to UAV (unmanned aircraft vehicle) images in linear motions For these reasons, we investigate a robust approach to generate a high quality mosaicked image from narrowly overlapped UAV images. In order to identify optimal geometric correction method in the case of narrowly overlapping images, several transformation models are discussed and evaluated
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