Color image detail enhancement based on quaternion guided filter

doi:10.1016/S1005-8885(17)60222-X

中国邮电高校学报(英文版) ›› 2017, Vol. 24 ›› Issue (4): 40-50.doi: 10.1016/S1005-8885(17)60222-X

• Artificial Intelligence • 上一篇下一篇

Color image detail enhancement based on quaternion guided filter

武昆,李桂菊,韩广良,杨航,刘培勋

中国科学院长春光学精密机械与物理研究所

收稿日期:2017-02-16 修回日期:2017-06-15 出版日期:2017-08-30 发布日期:2017-08-30
通讯作者: 武昆 E-mail:648581540@qq.com
基金资助:
国家自然科学基金重点项目

Color image detail enhancement based on quaternion guided filter

Received:2017-02-16 Revised:2017-06-15 Online:2017-08-30 Published:2017-08-30
Contact: Kun Wu E-mail:648581540@qq.com
Supported by:
National Science Foundation of China

摘要/Abstract

摘要： Color image enhancement is an active research field in image processing. Currently, many image enhancement methods are capable of enhancing the details of the color image. However, these methods only process the red, green and blue (RGB) color channels separately, which leads to color distortion easily. In order to overcome this problem, the paper presents an approach to integrate the quaternion theory into the traditional guided filter to obtain a quaternion guided filter (QGF). This method makes full use of the color information of an image to realize the holistic processing of RGB color channels. So as to preserve color information while enhancing details, this paper proposes a color image detail enhancement algorithm based on the QGF. Experimental results show that the proposed algorithm is effective in the applications of the color image detail enhancement, and enables image’s edges to be more prominent and texture clearer while avoiding color distortion. Compared with the existing image enhancement methods, the proposed method achieves better enhancement performance in terms of the visual quality and the objective evaluating indicators.

关键词: detail enhancement, quaternion guided filter, self-adaptive enhancement transform

Abstract: Color image enhancement is an active research field in image processing. Currently, many image enhancement methods are capable of enhancing the details of the color image. However, these methods only process the red, green and blue (RGB) color channels separately, which leads to color distortion easily. In order to overcome this problem, the paper presents an approach to integrate the quaternion theory into the traditional guided filter to obtain a quaternion guided filter (QGF). This method makes full use of the color information of an image to realize the holistic processing of RGB color channels. So as to preserve color information while enhancing details, this paper proposes a color image detail enhancement algorithm based on the QGF. Experimental results show that the proposed algorithm is effective in the applications of the color image detail enhancement, and enables image’s edges to be more prominent and texture clearer while avoiding color distortion. Compared with the existing image enhancement methods, the proposed method achieves better enhancement performance in terms of the visual quality and the objective evaluating indicators.

Key words: detail enhancement, quaternion guided filter, self-adaptive enhancement transform

参考文献

1. Grag R, Mittal B, Grag S. Histogram equalization techniques for image enhancement. The International Journal of Electronics and Communication Technology, 2011, 2(3): 107-111

2. Zhu R, Zhu L, Li D N. Study of color heritage image enhancement algorithms based on histogram equalization. Optik, 2015, 126(24): 5665-5667

3. Xu B L, Zhuang Y Q, Tang H L, et al. Object-based multilevel contrast stretching method for image enhancement. IEEE Transactions on Consumer Electronics, 2010, 56(3): 1746-1754

4. Zeng L, Chen J, Tong L, et al. Image contrast enhancement based on histogram similarity. Proceedings of the 2013 IEEE International Conference on Medical Imaging Physics and Engineering (ICMIPE’13), Oct 19-20, 2013, Shenyang, China. Piscataway, NJ, USA: IEEE, 2013: 269-273

5. Jobson D J, Rahman Z, Woodell G A. A multiscale retinex for bridging the gap between color images and the human observation of scenes. IEEE Transactions on Image Processing, 1997, 6(7): 965-976

6. Kimmel R, Elad M, Shaked D, et al. A variational framework for Retinex. International Journal of Computer Vision, 2003, 52(1): 7-23

7. Li J. Application of image enhancement method for digital images based on Retinex theory. Optik, 2013, 124(23): 5986-5988

8. Vidhyalavanya R, Madheswaran M. An improved denoising algorithm using parametric multiwavelets for image enhancement. International Journal of Advanced Science and Technology, 2010, 16: 1-10

9. Starck J L, Murtagh F, Candes E J, et al. Gray and color image contrast enhancement by the curvelet transform. IEEE Transactions on Image Processing, 2003, 12(6): 706-717

10. Hou W, Zhan B C, Wu Y Q, et al. Image enhancement based on adaptive and fuzzy complex contourlet transform. Proceedings of the 37th Annual Conference of the IEEE Industrial Electronics Society, Nov 7-10, 2011, Melbourne, Australia. Piscataway, NJ, USA: IEEE, 2011: 2222-2226

11. Nezhadarya E, Shamsollahi M B. Image contrast enhancement by contourlet transform. Proceedings of the 48th International Symposium ELMAR-2006 Focused on Multimedia Signal Processing and Communications (MLMAR Conference), Jun 7-10, Zadar, Croatia. Piscataway, NJ, USA: IEEE, 2006: 81-84

12. Perona P, Malik J. Scale-space and edge detection using anisotropic diffusion. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1990, 12(7): 629-639

13. Tomasi C, Manduchi R. Bilateral filtering for gray and color images. Proceedings of the 6th International Conference on Computer Vision (ICCV’98), Jan 4-7, 1998, Bombay, India. Piscataway, NJ, USA: IEEE, 1998: 839-846

14. Durand F, Dorsey J. Fast bilateral filtering for the display of high-dynamic-range images. ACM Transactions on Graphics, 2002, 21(3): 257-266

15. Sun G, Liu S L, Wang W H, et al. Dynamic range compression and detail enhancement algorithm for infrared image. Applied Optics, 2014, 53(26): 6013-6029

16. Ibrahim H M, Gharieb R R, Ibrahim A H. Edge preserving filtering by combining CBAE and median filter for image enhancement. Proceedings of the 18th National Radio Science Conference (NRSC’01): Vol 1, Mar 27-29, 2001, Mansoura, Egypt. Piscataway, NJ, USA: IEEE, 2001: 277-284

17. Langner J, Hofheinz F, Beuthien-Baumann B, et al. Locally adaptive filtering for edge preserving noise reduction on images with low SNR in PET. Proceedings of the 2011 IEEE Nuclear Science Symposium and Medical Imaging Conference, Oct 23-29, 2011, Valencia, Spain. Piscataway, NJ, USA: IEEE, 2011: 3102-3104

18. Bae S, Paris S, Durand F. Two-scale tone management for photographic look. ACM Transactions on Graphics, 2006, 25(3): 637-645

19. He K M, Sun J, Tang X O. Single image haze removal using dark channel prior. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2009, 33(12): 2341-2353

20. Li B, Wang S H, Zheng J, et al. Single image haze removal using content-adaptive dark channel and post enhancement. IET Computer Vision, 2013, 8(2): 131-140

21. Yan J Z, Lin S, Kang S B, et al. A learning-to-rank approach for image color enhancement. Proceedings of the Computer Vision and Pattern Recognition Conference (CVPR’14), Jun 23-28, 2014, Columbus, OH, USA. Piscataway, NJ, USA: IEEE, 2014: 2987-2994

22. He K M, Sun J, Tang X O. Guided image filter. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013, 35(6): 1397-1409

23. Hamilton W R. On quaternions; or on a new system of imaginaries in algebra. Philosophical Magazine Series 3, 1844, 25(163): 10-13

24. Zhai Y, Shah M. Visual attention detection in video sequences using spatiotemporal cues. Proceedings of the 14th ACM International Conference on Multimedia, Oct 23-27, 2006, Santa Barbara, CA, USA. New York, NY, USA: ACM, 2006: 815-824

25. Pei S C, Cheng C M. A novel block truncation coding of color images by using quaternion moment preserving principle. IEEE Transactions on Communications, 1997, 45(5): 583-595

26. Guo L Q, Dai M, Zhu M. Multifocus color image fusion based on quaternion curvelet transform. Optics Express, 2012, 20(19): 18846-18860

27. Li Y C, Zhang H, Jia W Y, et al. Saliency guided naturalness enhancement in color images. Optik, 2016, 127: 1326-1334

28. Zuiderveld K. Contrast limited adaptive histogram equalization. San Diego, CA, USA: Academic Press Professional, 1994: 474-485

Color image detail enhancement based on quaternion guided filter

Color image detail enhancement based on quaternion guided filter

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 0

编辑推荐

Metrics

本文评价