A novel customized recompression framework for massive internet images

Authors:
Shouhong Ding;Feiyue Huang;Zhifeng Xie;Yongjian Wu;Lizhuang Ma
Affiliations:
Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China;Tencent Research, Shanghai, China;Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China;Tencent Research, Shanghai, China;Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China
Venue:
CVM'12 Proceedings of the First international conference on Computational Visual Media
Year:
2012

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Abstract

Recently, device storage capacity and transmission bandwidth requirements are facing a heavy burden on account of massive internet images. Generally, to improve user experience and save costs as much as possible, a lot of internet applications always focus on how to achieve the appropriate image recompression. In this paper, we propose a novel framework to efficiently customize image recompression according to a variety of applications. And our new framework has been successfully applied to many commercial applications, such as web portals, e-commerce, online game and so on.