Distortion optimization based image completion from a large displacement view

We present a new image completion method based on an additional large displacement view (LDV) of the same scene for faithfully repairing large missing regions on the target image in an automatic way. A coarse-to-fine distortion correction algorithm is proposed to minimize the perspective distortion in the corresponding parts for the common scene regions on the LDV image. First, under the assumption of a planar scene, the LDV image is warped according to a homography to generate the initial correction result. Second, the residual distortions in the common known scene regions are revealed by means of a mismatch detection mechanism and relaxed by energy optimization of overlap correspondences, with the expectations of color constancy and displacement field smoothness. The fundamental matrix for the two views is then computed based on the reliable correspondence set. Third, under the constraints of epipolar geometry, displacement field smoothness and color consistency of the neighboring pixels, the missing pixels are orderly restored according to a specially defined repairing priority function. We finally eliminate the ghost effect between the repaired region and its surroundings by Poisson image blending. Experimental results demonstrate that our method outperforms recent state-of-the-art image completion methods for repairing large missing area with complex structure information.