TY - GEN
T1 - A novel customized recompression framework for massive internet images
AU - Ding, Shouhong
AU - Huang, Feiyue
AU - Xie, Zhifeng
AU - Wu, Yongjian
AU - Ma, Lizhuang
PY - 2012
Y1 - 2012
N2 - 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.
AB - 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.
KW - Image Quality Assessment
KW - Image Recompression
KW - Massive Internet Images
UR - https://www.scopus.com/pages/publications/84868327665
U2 - 10.1007/978-3-642-34263-9_2
DO - 10.1007/978-3-642-34263-9_2
M3 - 会议稿件
AN - SCOPUS:84868327665
SN - 9783642342622
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 9
EP - 16
BT - Computational Visual Media - First International Conference, CVM 2012, Proceedings
T2 - 1st International Conference on Computational Visual Media, CVM 2012
Y2 - 8 November 2012 through 10 November 2012
ER -