DocumentCode
1324161
Title
Compressibility-Aware Media Retargeting With Structure Preserving
Author
Wang, Shu-Fan ; Lai, Shang-Hong
Author_Institution
Dept. of Comput. Sci., Nat. Tsing Hua Univ., Hsinchu, Taiwan
Volume
20
Issue
3
fYear
2011
fDate
3/1/2011 12:00:00 AM
Firstpage
855
Lastpage
865
Abstract
A number of algorithms have been proposed for intelligent image/video retargeting with image content retained as much as possible. However, they usually suffer from some artifacts in the results, such as ridge or structure twist. In this paper, we present a structure-preserving media retargeting technique that preserves the content and image structure as best as possible. Different from the previous pixel or grid based methods, we estimate the image content saliency from the structure of the content. A block structure energy is introduced with a top-down strategy to constrain the image structure inside to deform uniformly in either x or y direction. However, the flexibilities for retargeting are quite different for different images. To cope with this problem, we propose a compressibility assessment scheme for media retargeting by combining the entropies of image gradient magnitude and orientation distributions. Thus, the resized media is produced to preserve the image content and structure as best as possible. Our experiments demonstrate that the proposed method provides resized images/videos with better preservation of content and structure than those by the previous methods.
Keywords
content management; image retrieval; media streaming; block structure energy; compressibility assessment scheme; compressibility-aware media retargeting; grid based method; image content; image content saliency; image gradient magnitude; image structure; intelligent image-video retargeting; orientation distribution; structure preserving media retargeting technique; top-down strategy; Humans; Image coding; Image segmentation; Media; Optimization; Pixel; Shape; Compressibility estimation; media retargeting; structure-preserving;
fLanguage
English
Journal_Title
Image Processing, IEEE Transactions on
Publisher
ieee
ISSN
1057-7149
Type
jour
DOI
10.1109/TIP.2010.2076293
Filename
5571001
Link To Document