Geometric rearrangement of images includes operations
such as image retargeting, inpainting, or object rearrangement.
Each such operation can be characterized by a shiftmap:
the relative shift of every pixel in the output image
from its source in an input image.
We describe a new representation of these operations as
an optimal graph labeling, where the shift-map represents
the selected label for each output pixel. Two terms are used
in computing the optimal shift-map: (i) A data term which
indicates constraints such as the change in image size, object
rearrangement, a possible saliency map, etc. (ii) A
smoothness term, minimizing the new discontinuities in the
output image caused by discontinuities in the shift-map.
This graph labeling problem can be solved using graph
cuts. Since the optimization is global and discrete, it outperforms
state of the art methods in most cases. Efficient
hierarchical solutions for graph-cuts are presented, and operations
on 1M images can...