skip to main content
10.1145/3330393.3330398acmotherconferencesArticle/Chapter ViewAbstractPublication PagesicmsspConference Proceedingsconference-collections
research-article

Rational Function Model Based Color Correction in Image Stitching Applications

Published: 10 May 2019 Publication History

Abstract

In the field of image processing, color correction is usually used when there are significant differences in tone or brightness in the original images. This method is also often used as an image preprocessing method to assist many other applications. This paper introduces a method of color correction using rational function model and histogram. And we use two different mapping methods to get best stitching results according to different application scenarios. The problem of color discontinuity in many color correction algorithms is solved, and the experimental results show that our method has a faster time efficiency.

References

[1]
Nanda, H and Cutler, R. 2001. Practical calibrations for a real time digital omnidirectional camera. Technical Sketches. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (Kauai, HI, USA, December 08-14, 2001).
[2]
Brown, M. and Lowe, D. G. 2003. Recognising panoramas. In Proceedings of the IEEE International Conference on Computer Vision (Nice, France, October 13-16, 2003), 1218--1225.
[3]
Uyttendaele, M., Eden, A., and Szeliski R. 2001. Eliminating ghosting and exposure artifacts in image mosaics. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (Kauai, HI, USA, December 08-14, 2001).
[4]
Reinhard, E., Adhikhmin, M., Gooch, B., and Shirley, P. 2001. Color transfer between images. IEEE Computer Graphics and Applications, 21, 5 (September. 2001), 34--41.
[5]
Zhang, M. and Georganas, N. D. 2004. Fast color correction using principal regions mapping in different color spaces. Real Time Imaging, 10, 1 (February. 2004), 23--30.
[6]
Jia, J. and Tang, C. K. 2005. Tensor voting for image correction by global and local intensity alignment. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27, 1 (January. 2005), 36--50.
[7]
Piti´t F., Kokaram, A. C., and Dahyot, R. 2007. Automated colour grading using colour distribution transfer. Computer Vision and Image Understanding, 107, 1-2 (August. 2007), 123--137.
[8]
Xiang, Y., Zou, B., and Li H. 2009. Selective color transfer with multi-source images. Pattern Recognition Letters, 30, 7 (May. 2009), 682--689.
[9]
Yamamoto, K and Oi, R. 2008. Color correction for multi-view video using energy minimization of view networks. International Journal of Automation and Computing, 5, 3 (July. 2008), 234--245.
[10]
Yin, J. and Cooperstock, J. R. 2004. Color correction methods with applications to digital projection environments. J. Winter School Comput.Graph, 12, 3 (January. 2004), 499--506.
[11]
Oliveira, M., Sappa, A., and Santos, V. 2011. Unsupervised local color correction for coarsely registered images. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (Colorado Springs, CO, USA, June 20-25, 2011). 201--208.
[12]
Tai, Y. W., Jia, J., and Tang, C. K. 2005. Local color transfer via probabilistic segmentation by expectation-maximization. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (San Diego, California, USA, June 20-26, 2005). 747--754.
[13]
Xiao, X and Ma, L. 2006. Color transfer in correlated color space. In Proceedings of the ACM International Conference on Virtual Reality Continuum and Its Applications (Hong Kong, China, June 14-17, 2006). VRCIA '06. ACM, New York, NY, 305--309.
[14]
Fecker, U., Barkowsky, M., and Kaup, A. 2008. Histogram-based prefiltering for luminance and chrominance compensation of multiview video. IEEE Transactions on Circuits & Systems for Video Technology, 18, 9 (September. 2008), 1258--1267.
[15]
Hwang, Y., Lee, J. Y., Kweon, I. S., and Kim, S. J. 2014. Color transfer using probabilistic moving least squares. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (Columbus, OH, USA, June 23-28, 2014). 3342--3349.
[16]
Faridul, H. S., Stauder, J., Kervec, J., and Tremeau, A. 2013. Approximate crosschannel color mapping from sparse color correspondences. In Proceedings of the IEEE International Conference on Computer Vision Workshops (Sydney, Australia, December 02-08, 2013). 860--867.
[17]
Grogan, M., and Dahyot, R. 2017. Robust registration of Gaussian mixtures for colour transfer. {Online}. Available: https://arxiv.org/abs/1705.06091
[18]
Liao, D., Qian, Y., and Li, Z. N. 2016. Semisupervised manifold learning for color transfer between multiview images. In Proceedings of the International Conference on Pattern Recognition. (Cancun, Mexico, December 04-08, 2016). 259--264.
[19]
Bellavia, F. and Colombo, C. 2017. Dissecting and Reassembling Color Correction Algorithms for Image Stitching. IEEE Transactions on Image Processing, 27, 2 (September. 2017). 735--748.
[20]
Gao, J., Li, Y., Chin, T. J., and Brown, M. S. 2013. Seam-driven image stitching. In Eurographics, 45--48.
[21]
Preiss, J., Fernandes, F., and Urban, P. 2014. Color-image quality assessment: From prediction to optimization. IEEE Transactions on Image Processing, 23, 3 (March. 2014), 1366--1378.
[22]
Zhang, L., Mou, X., and Zhang, D. 2011. FSIM: A feature similarity index for image quality assessment. IEEE Transactions on Image Processing, 20, 8 (August 2011), 2378--2386.
[23]
Wang, Z., Bovik, A. C., Sheikh, H. R., and Simoncelli, E. P. 2004. Image quality assessment: From error visibility to structural similarity. IEEE Transactions on Image Processing, 13, 4 (April 2004), 600--612.

Cited By

View all
  • (2021)Quality assessment for color correction-based stitched images via bi-directional matchingJournal of Visual Communication and Image Representation10.1016/j.jvcir.2021.10305175(103051)Online publication date: Feb-2021

Index Terms

  1. Rational Function Model Based Color Correction in Image Stitching Applications

    Recommendations

    Comments

    Information & Contributors

    Information

    Published In

    cover image ACM Other conferences
    ICMSSP '19: Proceedings of the 2019 4th International Conference on Multimedia Systems and Signal Processing
    May 2019
    213 pages
    ISBN:9781450371711
    DOI:10.1145/3330393
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    In-Cooperation

    • Shenzhen University: Shenzhen University
    • Sun Yat-Sen University

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 10 May 2019

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. Color correction
    2. histogram matching
    3. image stitching
    4. rational function

    Qualifiers

    • Research-article
    • Research
    • Refereed limited

    Conference

    ICMSSP 2019

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)4
    • Downloads (Last 6 weeks)0
    Reflects downloads up to 19 Feb 2025

    Other Metrics

    Citations

    Cited By

    View all
    • (2021)Quality assessment for color correction-based stitched images via bi-directional matchingJournal of Visual Communication and Image Representation10.1016/j.jvcir.2021.10305175(103051)Online publication date: Feb-2021

    View Options

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Figures

    Tables

    Media

    Share

    Share

    Share this Publication link

    Share on social media