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Image retargeting via Beltrami representation

Project Description:
Image retargeting aims to resize an image to one with prescribed aspect ratio. Simple scaling inevitably introduces unnatural geometric distortions on the important contents of the image. In this paper, we propose a simple and yet effective method to resize an image, which preserves the geometry of the important content, using quasiconformal theories. Our algorithm allows users to interactively identify content regions as well as line structures.  Image resizing can then be acheived by warping the image by an orientation-preserving homeomorphism with controlled distortion. The warping map is represented by its Beltrami representation, which captures the local geometric distortion of the map. By carefully setting the values of the Beltrami representation, we propose three methods to resize an image for different situations. Our method is simple and does not require solving any optimization problems throughtout the process. This results in a simple and efficient algorithm to solve the image retargeting problem. Experiment results demonstrate the efficacy of our proposed method.


  • C.P. Yung, C.P. Lau, L.M. Lui, Image retargeting via Beltrami representation, (2017)