IJMTES – ENERGY AWARE IMAGE RETARGETING USING DISCRETE IMAGE

Journal Title : International Journal of Modern Trends in Engineering and Science

Paper Title : ENERGY AWARE IMAGE RETARGETING USING DISCRETE IMAGE

Author’s Name : Ambili Jose | Mrs N Santhana Krishna
unnamed

Volume 04 Issue 06 2017

ISSN no:  2348-3121

Page no: 89-91

Abstract – The image reduction techniques ensure that they enlarge the dimension in each direction. The image enlarging is balancing under the pixels. The pixel is operated on the artificial means by pixel. The horizontal and vertical directions are exceeded on the multi size pictures. The designer dimension is exceeded on the size image, and client application. The removal and insertion processes are leaving under the entropy eye- gaze movement, and more. The image resizing and scanning technique are primitive under the graphic geometric transformation. The scanning graphic dimensional are rated under conversion. The conversion of discrete signal is under the sampling rate. The graphic image is scalded under the no loss of the image quality. The local sampling rate is optimized under the signal processing.

Keywords – Image Resize, Seam Carving, Quality Measure

References

  1. A.Rav-Acha, Y. Pritch, and S. Peleg, “Making a long video short: Dynamic video synopsis,” in Proc. IEEE Conf. Computer Vision Pattern Recognition, June 2006, pp. 435–441.
  2. A.Rav-Acha, Y. Pritch, D. Lischinski, and S. Peleg, “Dynamosaicing: Mosaicing of dynamic scenes,” IEEE Trans. Pattern Anal. Machine Intell, vol. 29, no. 10, pp. 1789–1801, 2007.
  3. B.Chen and P. Sen, “Video carving,” in EUROGRAPHICS’08, 2008.
  4. Elgammal, R. Duraiswami, D. Harwood, and L. Davis, “Background and foreground modeling using nonparametric kernel density for visual surveillance,” Proc. IEEE, vol. 90, pp. 1151–1163, 2002.
  5. H.-W. Kang, Y. Matsuhita, X. Tang, and X.-Q. Chen, “Space-time video montage,” in Proc. IEEE Conf. Computer Vision Pattern Recognition, June 2006, pp. 1331–1338.
  6. J. Konrad, “Videopsy: Dissecting visual data in space-time,” IEEE Comm. Mag., vol. 45, no. 1, pp. 34–42, Jan. 2007.
  7. J.McHugh, J. Konrad, V. Saligrama, and P.-M. Jordon, “Foreground adaptive background subtraction,” IEEE Signal Process. Lett., Sept. 2008 (submitted).
  8. J. Nam and A. Tewfik, “Video abstract of video,” in IEEE Workshop on Multimedia Signal Proc., 1999, pp. 117–122.
  9. J. Oh, Q. Wen, J. Lee, and S. Hwang, “Video abstraction,” in Video Data Mangement and Information Retrieval, S. Deb, Ed. Idea Group Inc. and IRM Press, 2004, ch. 3, pp. 321–346.
  10. M. Irani, P. Anandan, J. Bergen, R. Kumar, and S. Hsu, “Efficient representations of video sequences and their applications,” Signal Process., Image Commun., vol. 8, no. 4, pp. 327–351, May 1996.
  11. M. Rubinstein, A. Shamir, and S. Avidan. Improved seam carving for video retargetting. ACM Trans. Graph., vol. 27, no. 3, 2008.
  12. M. Yeung and B.-L. Yeo, “Video visualization for compact presentation and fast browsing of pictorial content,” IEEE Trans. Circuits Syst. Video Technol., vol. 7, no. 5, pp. 771–785, Oct. 1997.
  13. N. Petrovic, N. Jojic, and T. Huang, “Adaptive video fast forward,” Multimedia Tools Appl., vol. 26, no. 3, pp. 327–344, Aug. 2005.
  14. O. Tuzel, F. Porikli, and P. Meer, “Pedestrian detection via classification on Riemannian manifolds,” IEEE Trans. Pattern Anal. Machine Intell., vol. 30, no. 10, pp. 1713–1727, Oct. 2008.
  15. S. Avidan and A. Shamir. Seam carving for content-aware image resizing. ACM Trans. Graph. 26, 3 (Jul. 2007), 10.