Paper
7 September 2010 A survey of image retargeting techniques
Daniel Vaquero, Matthew Turk, Kari Pulli, Marius Tico, Natasha Gelfand
Author Affiliations +
Abstract
Advances in imaging technology have made the capture and display of digital images ubiquitous. A variety of displays are used to view them, ranging from high-resolution computer monitors to low-resolution mobile devices, and images often have to undergo changes in size and aspect ratio to adapt to different screens. Also, displaying and printing documents with embedded images frequently entail resizing of the images to comply with the overall layout. Straightforward image resizing operators, such as scaling, often do not produce satisfactory results, since they are oblivious to image content. In this work, we review and categorize algorithms for contentaware image retargeting, i.e., resizing an image while taking its content into consideration to preserve important regions and minimize distortions. This is a challenging problem, as it requires preserving the relevant information while maintaining an aesthetically pleasing image for the user. The techniques typically start by computing an importance map which represents the relevance of every pixel, and then apply an operator that resizes the image while taking into account the importance map and additional constraints. We intend this review to be useful to researchers and practitioners interested in image retargeting.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Daniel Vaquero, Matthew Turk, Kari Pulli, Marius Tico, and Natasha Gelfand "A survey of image retargeting techniques", Proc. SPIE 7798, Applications of Digital Image Processing XXXIII, 779814 (7 September 2010); https://doi.org/10.1117/12.862419
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CITATIONS
Cited by 102 scholarly publications and 6 patents.
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KEYWORDS
Image segmentation

Visualization

Facial recognition systems

Video

Sensors

Image visualization

Computer programming

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