Significance-Preserving-Guided Content-Aware Image Retargeting

NCUIR > Engineering College > Departmant of Mechanical Engineering > journal & Dissertation > Item 987654321/109049

Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/109049

Title:	Significance-Preserving-Guided Content-Aware Image Retargeting
Authors:	林智揚;Sung, Yu-Hsien;Tseng, Wen-Yu;Lin, Pao-Hung;Kang, Li-Wei;Lin, Chih-Yang;Yeh, Chia-Hung
Contributors:	工學院機械工程學系
Keywords:	Artificial intelligence;Popular Research Topic;Saliency Detection;Scalable Video Code;Uniform Scaling;Visual Attention Model
Date:	2013-06-28
Issue Date:	2026-04-23 15:27:33 (UTC+8)
Publisher:	Springer Verlag;Germany: Springer Berlin / Heidelberg
Abstract:	摘要： With the rapid development of multimedia and network technologies, sharing image contents through heterogeneous devices of different capabilities has been popular. A variety of displays provide different display capabilities ranging from high-resolution computer/TV monitors to low-resolution mobile devices, where images are usually required to be changed in size or aspect ratio to adapt to different screens. Based on the fact that straightforward image resizing operators (e.g., uniform scaling) cannot usually produce satisfactory results, content-aware image retargeting, which aims to arbitrarily change image size while preserving visually prominent features, has been a popular research topic. In this paper, we present a robust and computationally-efficient content-aware image retargeting framework based on seam carving subject to gradient energy and saliency-preserving constraint. In the proposed method, the significance map derived from adaptively integrating both the gradient and saliency maps of an image is used to accurately identify the most important area(s) to be preserved while retargeting this image. The proposed significance map can well compensate the drawbacks induced by only either gradient-based or saliency-based map is used. As a result, an image can be flexibly adapted to arbitrary sizes. Experimental results demonstrate the efficacy of the proposed algorithm. 出版者： Germany: Springer Berlin / Heidelberg 出版日期： 2013 出處： Advances in Intelligent Systems and Applications - Volume 2, 2013, p.339-348 版權： Springer-Verlag Berlin Heidelberg 2013 識別號： ISSN: 2190-3018 識別號： ISBN: 9783642354724 識別號： ISBN: 3642354726 識別號： EISSN: 2190-3026 識別號： EISBN: 9783642354731 識別號： EISBN: 3642354734 識別號： DOI: 10.1007/978-3-642-35473-1_34 識別號： OCLC: 823728185 識別號： LCCallNum: Q342
Appears in Collections:	[Departmant of Mechanical Engineering ] journal & Dissertation

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