kanvases/sihr

Ongoing effort of implementing single image highlight removal methods in MATLAB

About

An ongoing effort of developing new and implementing established single image highlight removal (SIHR) methods on MATLAB.

I welcome and encourage additions upon review.

Disclaimer: this repository is for educational purposes only.

Usage

Run SIHR.m for path setup.

Run help SIHR for (minimal) documentation.

The environment this repository is being developed is:

• MATLAB R2019a;
• Image Processing Toolbox.

The repository is structured as follows:

SIHR\
  ↳ img\
      ↳ Test images.
  ↳ Tan2005\
      ↳ Implementation of Tan's zHighlightRemoval class [3].
        Available at (C++):
        http://tanrobby.github.io/code/highlight.zip.
  ↳ Yoon2006\
      ↳ Implementation of Yoon's 2006 method [4].
  ↳ Shen2008\
      ↳ Code for [5].
        Also available at (MATLAB):
        http://ivlab.org/publications/PR2008_code.zip.
  ↳ Shen2009\
      ↳ Code for [6].
  ↳ Yang2010\
      ↳ Implementation of Yang's qx_highlight_removal_bf method [7, 10].
        Formerly available at (C++):
        http://www.cs.cityu.edu.hk/~qiyang/publications/code/eccv-10.zip.
  ↳ Akashi2015\
      ↳ Direct implementation of [11].
  ↳ Yamamoto2017\
      ↳ Implementation of improvements in [12].

Feel free to create either an issue or a PR or contact me for any questions, comments, or improvements.

Below are listed references for works herein present and a couple survey papers for further reading.

References

1. A. Artusi, F. Banterle, and D. Chetverikov, “A Survey of Specularity Removal Methods,” Computer Graphics Forum, vol. 30, no. 8, pp. 2208–2230, Aug. 2011 [Online]. Available: http://dx.doi.org/10.1111/J.1467-8659.2011.01971.X;

2. H. A. Khan, J.-B. Thomas, and J. Y. Hardeberg, “Analytical Survey of Highlight Detection in Color and Spectral Images,” in Lecture Notes in Computer Science, Springer International Publishing, 2017, pp. 197–208 [Online]. Available: http://dx.doi.org/10.1007/978-3-319-56010-6_17;

3. R. T. Tan and K. Ikeuchi, “Separating reflection components of textured surfaces using a single image,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 27, no. 2, pp. 178–193, Feb. 2005 [Online]. Available: http://dx.doi.org/10.1109/TPAMI.2005.36;

4. K. Yoon, Y. Choi, and I. S. Kweon, “Fast Separation of Reflection Components using a Specularity-Invariant Image Representation,” in 2006 International Conference on Image Processing, 2006 [Online]. Available: http://dx.doi.org/10.1109/ICIP.2006.312650;

5. H.-L. Shen, H.-G. Zhang, S.-J. Shao, and J. H. Xin, “Chromaticity-based separation of reflection components in a single image,” Pattern Recognition, vol. 41, no. 8, pp. 2461–2469, Aug. 2008 [Online]. Available: http://dx.doi.org/10.1016/J.PATCOG.2008.01.026;

6. H.-L. Shen and Q.-Y. Cai, “Simple and efficient method for specularity removal in an image,” Applied Optics, vol. 48, no. 14, p. 2711, May 2009 [Online]. Available: http://dx.doi.org/10.1364/AO.48.002711;

7. R. Grosse, M. K. Johnson, E. H. Adelson, and W. T. Freeman, “Ground truth dataset and baseline evaluations for intrinsic image algorithms,” in 2009 IEEE 12th International Conference on Computer Vision, 2009 [Online]. Available: http://dx.doi.org/10.1109/ICCV.2009.5459428;

8. Q. Yang, S. Wang, and N. Ahuja, “Real-Time Specular Highlight Removal Using Bilateral Filtering,” in Computer Vision – ECCV 2010, Springer Berlin Heidelberg, 2010, pp. 87–100 [Online]. Available: http://dx.doi.org/10.1007/978-3-642-15561-1_7;

9. H.-L. Shen and Z.-H. Zheng, “Real-time highlight removal using intensity ratio,” Applied Optics, vol. 52, no. 19, p. 4483, Jun. 2013 [Online]. Available: http://dx.doi.org/10.1364/AO.52.004483;

10. Q. Yang, J. Tang, and N. Ahuja, “Efficient and Robust Specular Highlight Removal,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 37, no. 6, pp. 1304–1311, Jun. 2015 [Online]. Available: http://dx.doi.org/10.1109/TPAMI.2014.2360402;

11. Y. Akashi and T. Okatani, “Separation of reflection components by sparse non-negative matrix factorization,” Computer Vision and Image Understanding, vol. 146, pp. 77–85, May 2016 [Online]. Available: http://dx.doi.org/10.1016/j.cviu.2015.09.001;

12. T. Yamamoto, T. Kitajima, and R. Kawauchi, “Efficient improvement method for separation of reflection components based on an energy function,” in 2017 IEEE International Conference on Image Processing (ICIP), 2017 [Online]. Available: http://dx.doi.org/10.1109/ICIP.2017.8297078;