Fast image retargeting via axis-aligned importance scaling

In this paper, we propose an image retargeting method that resizes an image by the axis-aligned importance scaling. The proposed method operates on the axis-aligned deformation space, where the mesh structure is parameterized in the 1D vector, i.e., quads on the same column (or row) share the single parameter. The unknown variables are thus dependent on the grid resolution only, allowing a fast and simple implementation on a moderate CPU. The optimal parameters are inferred in an iterative manner: these parameters are updated by scaling initial ones according to the deformation error. It is measured at each iteration by aggregating the transition cost for the deformed quad. Experimental results show that the proposed method preserves visually salient features without foldover artifacts better than competing methods. In addition, the optimal parameters can be calculated within 0.02 ms on a single-core CPU.