Seam-Driven Image Stitching

نویسندگان

  • Junhong Gao
  • Yu Li
  • Tat-Jun Chin
  • Michael S. Brown
چکیده

Image stitching computes geometric transforms to align images based on the best fit of feature correspondences between overlapping images. Seam-cutting is used afterwards to to hide misalignment artifacts. Interestingly it is often the seam-cutting step that is the most crucial for obtaining a perceptually seamless result. This motivates us to propose a seam-driven image stitching strategy where instead of estimating a geometric transform based on the best fit of feature correspondences, we evaluate the goodness of a transform based on the resulting visual quality of the seam-cut. We show that this new image stitching strategy can often produce better perceptual results than existing methods especially for challenging scenes.

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تاریخ انتشار 2013