Scalable image representation using improved retargeting pyramid

Abstract

The retargeting pyramid (RP) method is a good alternative to the well-known Laplacian pyramid (LP) approach for multiscale image decomposition. RP can be obtained by replacing the low-pass filtering and downsampling processes in LP with content-aware image resizing (a.k.a. retargeting), which is a technique being developed in computer vision research. In this paper, we improve RP so that it obtains good scalable image representation. The improved RP is then integrated with a well-known multiscale-multidirection (MSMD) transform, contourlet transform, to construct a saliency-oriented MSMD image representation. In the experiment, our decomposition outperforms the conventional pyramid structures.