• DocumentCode
    1581862
  • Title

    Improved retargeting algorithm based on optimized scale-and-stretch

  • Author

    Zijuan Zhang ; Baosheng Kang

  • Author_Institution
    Sch. of Inf. Sci. & Technol., Northwest Univ., Xi´an, China
  • fYear
    2013
  • Firstpage
    181
  • Lastpage
    182
  • Abstract
    Effective resizing of images should not only use geometric constraints, but consider the image content as well. According to the fact that it is not necessary that the image content in the middle is more important than on the border, the image resizing technology in view of content is becoming new hotspot in image retargeting domain. At first, this technology treat the area that attract the eyes as important region, but the area that not attract the people as unimportant district, then to the greatest extent maintain the important area but changing unimportant area in order to fit target image size. This technology is known as content-aware image resizing. Among all the algorithms relating to content-aware image retargeting, the status of SNS method is beyond all doubt, its inauguration and innovation is better than other methods. This text analyses the classical SNS algorithm and presents a improved algorithm basing on scale-and-stretch, in our experiment it is easy to see that our new method enhances the performance and makes better effect.
  • Keywords
    gradient methods; image processing; optimisation; SNS; content aware image resizing; content aware image retargeting; geometric constraints; image content; image resizing technology; retargeting algorithm; scale and stretch; target image size; Algorithm design and analysis; Computers; Educational institutions; Electronic mail; Information science; Visualization; Energy; Image resizing; Image retargeting; SNS;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Global High Tech Congress on Electronics (GHTCE), 2013 IEEE
  • Conference_Location
    Shenzhen
  • Type

    conf

  • DOI
    10.1109/GHTCE.2013.6767268
  • Filename
    6767268