Match Selection in Batch Mosaicing Using Mutual Information
Large area photo-mosaics are widely used in many different applications such as optical mapping, panorama creation and autonomous vehicle navigation. When the trajectory of the camera provides an overlap between non-consecutive images (closed-loop trajectory), it is essential to detect such events in order to get globally coherent mosaics. Recent advances in image matching methods allow for registering pairs of images in the absence of prior information on orientation, scale or overlap between images. Owing to this, recent batch mosaicing algorithms attempt to detect non-consecutive overlapping images using exhaustive matching of image pairs. This paper proposes the use of Observation Mutual Information as a criterion to evaluate the benefit of potential matches between pairs of images. This allows for ranking and ordering a list of potential matches in order to make the loop-closing process more efficient. In this paper, the Observation Mutual Information criterion is compared against other strategies and results are presented using underwater imagery.
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