Image Stitching Using Structure Deformation

Abstract

The aim of this paper is to achieve seamless image stitching without producing visual artifact caused by severe intensity discrepancy and structure misalignment, given that the input images are roughly aligned or globally registered. Our new approach is based on structure deformation and propagation for achieving overall consistency in image structure and intensity.The new stitching algorithm, which has found applications in image compositing, image blending, and intensity correction,consists of the following main processes. Depending on the compatibility and distinctiveness of the 2-D features detected in the image plane, single or double optimal partitions are computed subject to the constraints of intensity coherence and structure continuity. Afterwards, specific 1-D features are detected along the computed optimal partitions, from which a set of sparse deformation vectors is derived to encode 1-D feature matching between the partitions. These sparse deformation cues are robustly propagated into the input images by solving the associated minimization problem in gradient domain, thus providing a uniform framework for the simultaneous alignment of image structure and intensity. We present results in general image compositing and blending, in order to show the effectiveness of our method in producing seamless stitching results from complex input images.

Index Terms

• Computing methodologies

  • Artificial intelligence

    • Computer vision

      • Computer vision problems

      • Computer vision tasks

        • Scene understanding

  • Computer graphics

    • Image manipulation

  • Machine learning