Image Stitching with Efficient Brightness Fusion and Automatic Content Awareness

Yu Tang, Jungpil Shin

Abstract

Image Stitching, also be called photo stitching, is the process of combining multiple photographic images with overlapping fields of view to produce a segmented panorama or high-resolution image. Image stitching is challenging in two fields. First, the sequenced photos taken from various angles will have different brightness. This will certainly lead to a un-nature stitched result with no harmony of brightness. Second, ghosting artifact due to the moving objects is also a common problem and the elimination of it is not an easy task. This paper presents several novel techniques that make the process of addressing the two difficulties significantly less labor-intensive while also efficient. For the brightness problem, each input image is blended by several images with different brightness. For the ghosting problem, we propose an intuitive technique according to a stitching line based on a novel energy map which is essentially a combination of gradient map which indicates the presence of structures and prominence map which determines the attractiveness of a region. The stitching line can easily skirt around the moving objects or salient parts based on the philosophy that human eyes mostly notice only the salient features of an image. We compare result of our method to those of 4 state-of-the-art image stitching methods and it turns out that our method outperforms the 4 methods in removing ghosting artifacts.

References

  1. P. Azzari and A. Bevilacqua. Joint spatial and tonal mosaic alignment for motion. Proceeding on AVSS 2006, pp.89-102, Nov. 2006.
  2. Jia jia, Chi-Keung Tang. Image stitching using structure deformation. Pattern Analysis and Machine Intelligence IEEE Transactions. 30(4):617-631, Apr. 2008.
  3. Yu Tang, Huiyan Jiang. Highly efficient image stitching based on energy map. CISP'09 , pp.1-5, Oct. 2009.
  4. Allene, C, Pons, J. Seamless image-based texture atlases using multi band blending. ICPR 2008, pp.1-4, Dec,2008
  5. Han,B, Lin, X. A novel hybrid color registration algorithm for image stitching. Consumer Electronics, IEEE Transcations, 52(3):1129-1134, Aug. 2006
  6. M.Brown, D.G. Lowe. Automatic panoramic image stitching using invariant features. International Journal of Computer Vision, Pp. 59-73, August. 2007
  7. M.Uyttedaele, A.Eden. Eliminating ghosting and exposure artifacts in image mosaics. CVPR2001, pp.509-516, Dec.2001.
  8. Tien-Der Yeh, Yon-Ping Che. An image stitching process using band-type optimal partition method. Asian Journal of Information Technology, 7(11):498-509, 2008.
  9. Xiong, Yingen. Eliminating ghosting artifacts for panoramic images. ISM'09 pp: 14-16, Dec. 2009
  10. Li Yao. Image mosaic on SIFT and deformation propagation. Knowledge Acquisition and Modeling Workshop, 2008, pp: 848-851, Dec. 2008.
  11. Anat Levin, Assaf Zomet. Seamless image stitching in the gradient Domain. ECCV 2004, pp:377-389,May.2004
  12. Baumberg, A. (2000). Reliable feature matching across widely separated views. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'2000), pages 774-781, Hilton Head Island.
  13. Brown, L. G. (1992). A survey of image registration techniques. Computing Surveys, 24(4), 325-376.
  14. Brown, M., Szeliski, R., and Winder, S. (2004). MultiImage Matching Using Multi-Scale Oriented Patches. Technical Report MSR-TR-2004-133, Microsoft Research.
  15. Brown, M., Szeliski, R., and Winder, S. (2005). Multiimage matching using multi-scale oriented patches. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition(CVPR'2005), pages 510-517, San Diego, CA
  16. P. J. Burt, K.Hanna, and R.J. Kolczynski. Enhanced image capture through fusion. In Proceedings of the Workshop on Augmented Visual Display Research, pages 207-224. NASA-Ames Research Center.,Dec.1993.
  17. J. DiCarlo and B. Wandell. Rendering high dynamic range images,. In Proceedings of SPIE, volume 3965, Jan. 2000.
  18. F. Drago, K. Myszkowski, T. Annen, and N. Chiba. Adaptive logarithmic mapping for displaying high contrast scenes. Computer Graphics Forum, 22:419- 426, 2003.
  19. R. Fattal, D. Lischinski, and M. Werman. Gradient domain high dynamic range compression. ACM Transactions on Graphics, 21(3):249-256, July 2002.
  20. E. Reinhard, M. Stark, P. Shirley, and J. Ferwerda. Photographic tone reproduction for digital images. ACM Transactions on Graphics, 21(3):267-276, July 2002.
  21. J. Tumblin and H. E. Rushmeier. Tone reproduction for realistic images. IEEE Computer Graphics and Applications, 13(6):42-48, Nov. 1993.
  22. Y. Li, L. Sharan, and E. H. Adelson. Compressing and companding high dynamic range images with subband architectures. ACM Transactions on Graphics, 24(3):836-844, Aug. 2005.
  23. G. Ward. Fast, robust image registration for compositing high dynamic range photographcs from hand-held exposures. Journal of Graphics Tools: JGT, 8(2):17- 30, 2003.
  24. Yu Tang, Jungpil Shin. De-ghosting for Image Stitching with Automatic Content-Awareness. Pattern Recognition (ICPR), 2010 20th International Conference on 23-26 Aug. 2010 2210 - 2213.
Download


Paper Citation


in Harvard Style

Tang Y. and Shin J. (2014). Image Stitching with Efficient Brightness Fusion and Automatic Content Awareness . In Proceedings of the 11th International Conference on Signal Processing and Multimedia Applications - Volume 1: SIGMAP, (ICETE 2014) ISBN 978-989-758-046-8, pages 60-66. DOI: 10.5220/0005087200600066


in Bibtex Style

@conference{sigmap14,
author={Yu Tang and Jungpil Shin},
title={Image Stitching with Efficient Brightness Fusion and Automatic Content Awareness},
booktitle={Proceedings of the 11th International Conference on Signal Processing and Multimedia Applications - Volume 1: SIGMAP, (ICETE 2014)},
year={2014},
pages={60-66},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005087200600066},
isbn={978-989-758-046-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 11th International Conference on Signal Processing and Multimedia Applications - Volume 1: SIGMAP, (ICETE 2014)
TI - Image Stitching with Efficient Brightness Fusion and Automatic Content Awareness
SN - 978-989-758-046-8
AU - Tang Y.
AU - Shin J.
PY - 2014
SP - 60
EP - 66
DO - 10.5220/0005087200600066