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Salient edge and region aware image retargeting
Affiliation:1. Department of Applied Mathematics, Xidian University, Xian 710071, China;2. School of Science, Xian Technological University, Xian 710012, China;1. Department of Mathematics, Xidian University, Xi’an 710071, China;2. Institute of Graphics and Image Processing, Xianyang Normal University, Xianyang 712000, China;1. Department of Electronic and Electrical Engineering, University of Strathclyde, Technology and Innovation Centre, 99 George Street, Glasgow, G1 1RD, United Kingdom;2. Dept. Electronic and Electrical Engineering, University of Strathclyde, Royal College Building, 204 George Street, Glasgow G1 1XW, United Kingdom;1. Department of Applied Mathematics, Xidian University, Xi’an, China;2. School of Mathematics and Computer Science, Ningxia University, Yinchuan, China
Abstract:The purpose of image retargeting is to automatically adapt a given image to fit the size of various displays without introducing severe visual distortions. The seam carving method can effectively achieve this task and it needs to define image importance to detect the salient context of images. In this paper we present a new image importance map and a new seam criterion for image retargeting. We first decompose an image into a cartoon and a texture part. The higher order statistics (HOS) on the cartoon part provide reliable salient edges. We construct a salient object window and a distance dependent weight to modify the HOS. The weighted HOS effectively protects salient objects from distortion by seam carving. We also propose a new seam criterion which tends to spread seam uniformly in nonsallient regions and helps to preserve large scale geometric structures. We call our method salient edge and region aware image retargeting (SERAR). We evaluate our method visually, and compare the results with related methods. Our method performs well in retargeting images with cluttered backgrounds and in preserving large scale structures.
Keywords:Saliency detection  Seam carving  Image retargeting  Cartoon texture decomposition  Higher order statistics
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