
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.
The paper describe a new representation of these operations as an optimal graph labeling, where the shiftmap represents the selected label for each output pixel. Two terms are used in computing the optimal shiftmap: (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 shiftmap.
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 graphcuts are presented, and operations on 1M images can take only a few seconds.
