Image Compressibility Assessment and the Application of Structure-Preservng Image Retargeting

Shu-Fan WangShang-Hong Lai

Project summary

A number of algorithms have been proposed for intelligent image/video retargeting with important content retained as much as possible. In some cases, we can notice that they suffer from artifacts in the resized results, such as ridge or structure twist. In this project, we suggest that the compressibility of an image should be estimated properly first by analyzing the image structure to determine the optimal scaling factors for the resizing algorithm. To cope with this problem, we propose a compressibility assessment scheme by combining the entropies of image gradient magnitude and orientation distributions. In order to further improve the result, we also present a structure-preserving media retargeting technique that preserves the content and image structure as best as possible. Since we focus on protecting the content structure, a block structure energy is introduced with a top-down strategy to constrain the image structure inside to scale uniformly in either x or y direction. Our experiments demonstrate that the proposed compressibility assessment scheme provides better preservation of content and structure in the resized images/videos than those by the previous methods.

compressibility experiments

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Last updated on November, 23, 2010.