Abstract
This paper presents an efficient image stitching algorithm with better image quality and less processing time for online stitching of a continuous image sequence. Stitching many frames with similar scenes is time-consuming and easily generates inconsistency in the overlap region between frames. Instead of stitching every captured frame, only the dominant frames with significant visual content dissimilar to that in the previously stitched result are worthy of being stitched and can contribute much new information. Although the nondominant frames are not included in the mosaicked image, their homography matrix with respect to the mosaicked image will be roughly evaluated to localize the camera view on the mosaicked image as the region of stitching interest. A particle filter with partitioned sampling is utilized to categorize the stitching label and estimate the homography matrix. Moreover, to substantially increase the quality of offline image mosaicking, a seam planning algorithm is designed to eliminate the unclear ghost effect in the overlap region between dominant frames. The aim is to maximally preserve the visual content while eliminating inconsistencies in the overlap region. The proposed stitching algorithm has been verified in several online and offline experiments to present the efficiency of the overall system.
Published Version
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