Nothing Special   »   [go: up one dir, main page]

Skip to main content
Log in

Adaptive side window joint bilateral filter

  • Original article
  • Published:
The Visual Computer Aims and scope Submit manuscript

Abstract

Edge-preserving image smoothing is a fundamental step for many computer vision problems, and so far, countless algorithms have been proposed. Among these algorithms, bilateral filtering and its extensions are widely used in image preprocessing. However, several difficulties are hindering its further development. First, the phenomenon of "halo artifact" occurs along the edges. Second, most of the existing algorithms work only with a fixed filtering kernel and cannot accurately distinguish the edges and textures which leads to inappropriate filtering. To address these issues, we present a novel edge-preserving image smoothing via adaptive side window joint bilateral filtering. As a local optimized-based algorithm, different from the traditional filtering, the position of the target pixel in the filtering kernel is changed from the center to the optimal edge and the filtering kernel size of each pixel is effectively estimated. Combined side window filtering with the joint bilateral filter, the capability of texture removal and edge preservation is improved and the halo artifacts are alleviated. Experimental results show that the proposed method outperforms existing state-of-the-arts in removing the texture information while preserving the main image content.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20
Fig. 21
Fig. 22
Fig. 23
Fig. 24
Fig. 25
Fig. 26
Fig. 27
Fig. 28
Fig. 29
Fig. 30
Fig. 31
Fig. 32
Fig. 33
Fig. 34

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  1. Farbman, Z., Fattal, R., Dani, L., et al.: Edge-preserving decompositions for multi-scale tone and detail manipulation. ACM Trans. Graph. 27(1), 67–75 (2008)

    Google Scholar 

  2. Kou, F., Chen, W., Li, Z., et al.: Content adaptive image detail enhancement. IEEE Signal Process. Lett. 22(2), 211–215 (2015)

    Article  Google Scholar 

  3. Gu, B., Li, W., Zhu, M., et al.: Local edge-preserving multiscale decomposition for high dynamic range image tone mapping. IEEE Trans. Image Process. 22(1), 70–79 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  4. Wei, Z., Wen, C., Li, Z.: Local inverse tone mapping for scalable high dynamic range image coding. IEEE Trans. Circ. Syst. Video Technol. 28(2), 550–555 (2018)

    Article  Google Scholar 

  5. Xu, L., Yan, Q., Yang, X., et al.: Structure extraction from texture via relative total variation. ACM Trans. Graph. 31(6), 139–147 (2012)

    Article  Google Scholar 

  6. Prasath, V.B.S., Pelapur, R., Guna, S., et al.: Multiscale structure tensor for improved feature extraction and image regularization. IEEE Trans. Image Process. 28(12), 6198–6210 (2019)

    Article  MathSciNet  MATH  Google Scholar 

  7. Zhou, P.C., Zhang, J., Xue, M.G., et al.: Directional relative total variation for structure–texture decomposition. IET Image Proc. 13(11), 1835–1845 (2019)

    Article  Google Scholar 

  8. Veerakumar, T., Subudhi, B.N., Esakkirajan, S.: Empirical mode decomposition and adaptive bilateral filter approach for impulse noise removal. Expert Syst. Appl. 121, 18–27 (2019)

    Article  Google Scholar 

  9. Veerakumar, T., Subudhi, B.N., Esakkirajan, S., et al.: Iterative adaptive unsymmetric trimmed shock filter for high-density salt-and-pepper noise removal. Circ. Syst. Signal Process. 38(6), 2630–2652 (2019)

    Article  Google Scholar 

  10. Kim, B., Ponce, J., Ham, B.: Deformable kernel networks for joint image filtering. Int. J. Comput. Vision 129, 579–600 (2021)

    Article  Google Scholar 

  11. Tomasi, C. Manduchi, R.: Bilateral filtering for gray and color images. In: Proceedings of IEEE International Conference on Computer Vision, pp. 836–846 (1998)

  12. Durand, F., Dorsey, J.: Fast bilateral filtering for the display of high dynamic-range images. ACM Trans. Graph. 21(3), 257–266 (2002)

    Article  Google Scholar 

  13. Porikli, F.: Constant time O(1) bilateral filtering. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 1–8 (2008)

  14. Yang, Q., Ahujia, N., Yang, R., et al.: Fusion of median and bilateral filtering for range image upsampling. IEEE Trans. Image Process. 22(12), 4841–4852 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  15. Paris, S., Durand, F.: A fast approximation of the bilateral filter using a signal processing approach. Int. J. Comput. Vis. 81, 24–52 (2009)

    Article  Google Scholar 

  16. Adams, A., Baek, J., Davis, M.A.: Fast high-dimensional filtering using the permutohedral lattice. Comput. Graph. Forum 29(2), 753–762 (2010)

    Article  Google Scholar 

  17. Petschnigg, G., Szeliski, R., Agrawala, M., et al.: Digital photography with flash and no-flash image pairs. ACM Trans. Graph. 23(3), 664–672 (2004)

    Article  Google Scholar 

  18. Eisemann, E., Durand, F.: Flash photography enhancement via intrinsic relighting. ACM Trans. Graph. 23(3), 673–678 (2004)

    Article  Google Scholar 

  19. Chen, B.H., Tseng, Y.S., Yin, J.L.: Gaussian-adaptive bilateral filter. IEEE Signal Process. Lett. 27, 1670–1674 (2020)

    Article  Google Scholar 

  20. Cho, H., Lee, H., Kang, H., et al.: Bilateral texture filtering. ACM Trans. Graph. 33(4), 1–8 (2014)

    Article  Google Scholar 

  21. Jeon, J., Lee, H., Kang, H., et al.: Scale-aware structure- preserving texture filtering. Comput. Graph. Forum 35(7), 77–86 (2016)

    Article  Google Scholar 

  22. Gavaskar, R.G., Chaudhury, K.N.: Fast adaptive bilateral filtering. IEEE Trans. Image Process. 28(2), 779–790 (2019)

    Article  MathSciNet  MATH  Google Scholar 

  23. Chen, B.H., Cheng, H.Y., Tseng, Y.S., et al.: Two-pass bilateral smooth filtering for remote sensing imagery. IEEE Geosci. Remote Sens. Lett. 99, 1–5 (2021)

    Google Scholar 

  24. Chaudhury, K.N., Sage, D., Unser, M.: Fast O(1) bilateral filtering using trigonometric range kernels. IEEE Trans. Image Process. 20(11), 3376–3382 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  25. Jevnisek, R.J., Shai, A.: Co-occurrence filter. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 3184–319 (2017)

  26. Ghosh, S., Gavaskar, R.G., Panda, D., et al.: Fast scale-adaptive bilateral texture smoothing. IEEE Trans. Circ. Syst. Video Technol. 30(7), 2015–2026 (2002)

    Google Scholar 

  27. Yin, H., Gong, Y.H., Qiu, G.: Side window filtering. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 8758–8766 (2019)

  28. Aurich, V., Weule, J.: Non-linear gaussian filters performing edge preserving diffusion. In: Proceedings of the DAGM Symposium, pp. 538–545 (1995)

  29. Paris, S., Kornprobst, P., Tumblin, J., et al.: Bilateral filtering: theory and applications. Found. Trends Comput. Graph. Vis. 4(1), 1–73 (2009)

    Article  MATH  Google Scholar 

  30. Zhang, Q., Shen, X., Xu, L., et al.: Rolling guidance filter. In: Proceedings of the 13th European Conference on Computer Vision, pp. 815–830 (2014)

  31. Xu, P.P., Wang, W.C.: Structure-aware window optimization for texture filtering. IEEE Trans. Image Process. 28(9), 4354–4363 (2019)

    Article  MathSciNet  MATH  Google Scholar 

  32. Cai, B., Xing, X., Xu, X.: Edge/structure preserving smoothing via relativity-of-Gaussian. In: Proceedings of IEEE International Conference on Image Processing, pp. 250–254 (2017)

  33. Cai, B., Xu, X., Guo, K., et al.: A joint intrinsic-extrinsic prior model for Retinex. In: Proceedings of IEEE International Conference on Computer Vision, pp. 4000–4009 (2017)

  34. Xu, L., Lu, C., Xu, Y., et al.: Image smoothing via L0 gradient minimization. ACM Trans. Graph. 30(6), 1–8 (2011)

    Google Scholar 

  35. Li, Z., Zheng, J., Zhu, Z., et al.: Weighted guided image filtering. IEEE Trans. Image Process. 24(1), 120–129 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  36. Kou, F., Chen, W., Wen, C., et al.: Gradient domain guided image filtering. IEEE Trans. Image Process. 24(11), 4528–4539 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  37. Bao, L., Song, Y., Yang, Q., et al.: Tree filtering: Efficient structure-preserving smoothing with a minimum spanning tree. IEEE Trans. Image Process. 23(2), 555–569 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  38. Subr, K., Soler, C., Durand, F.: Edge-preserving multiscale image decomposition based on local extrema. ACM Trans. Graph. 28(5), 1–9 (2009)

    Article  Google Scholar 

  39. Gastal, E.S.L., Oliveira, M.M.: Domain transform for edge-aware image and video processing. ACM Trans. Graph. 30(4), 1–12 (2014)

    Article  Google Scholar 

  40. Zhang, Q., Xu, L., Jia, J.Y.: 100+ times faster weighted median filter. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 1–9 (2014)

  41. He, K., Sun, J., Tang, X.: Guided image filtering. IEEE Trans. Anal. Mach. Learn. 35(6), 1397–1409 (2013)

    Article  Google Scholar 

  42. Dabov, K., Foi, A., Katkovnik, V., et al.: Image denoising by sparse 3-D transform-domain collaborative filtering. IEEE Trans. Image Process. 16(8), 2080–2095 (2007)

    Article  MathSciNet  Google Scholar 

  43. Wang, Z., Bovik, A.C., Sheikh, H.R.: Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13(4), 600–612 (2014)

    Article  Google Scholar 

  44. Lebrun, M.: An analysis and implementation of the BM3D image denoising method. Image Process. Line 2(25), 175–213 (2012)

    Article  Google Scholar 

  45. Fattal, R.: Image up-sampling via imposed edge statistics. ACM Trans. Graph. 26(3), 95 (2007)

    Article  Google Scholar 

  46. Zhu, F.D., Liang, Z.T., Jia, X.X., et al.: A benchmark for edge-preserving image smoothing. IEEE Trans. Image Process. 28(7), 3556–3570 (2019)

    Article  MathSciNet  MATH  Google Scholar 

  47. Xue, Y., Zhou, P.C., Xue, M.G.: Low-light image enhancement via layer decomposition and optimization. In: Proceedings of SPIE 11720, pp. 1–9 (2020)

  48. Land, E.H.: The Retinex theory of color vision. Sci. Am. 237(6), 108–128 (1977)

    Article  Google Scholar 

  49. Jobson, D.J., Rahman, Z.U., Woodell, G.A.: Properties and performance of a center/surround Retinex. IEEE Trans. Image Process. 6(3), 451–462 (1997)

    Article  Google Scholar 

  50. 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 Trans. Image Process. 6(7), 965–976 (1997)

    Article  Google Scholar 

Download references

Acknowledgements

The work was supported by the Natural Science Foundation of Anhui Province of China (No. 1908085MF208) and the Natural Science Foundation of China (No. 61379105). We sincerely thank Professor Gong Yuanhao for the side window filtering codes that he provided.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Pu-Cheng Zhou.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhou, PC., Xue, Y. & Xue, MG. Adaptive side window joint bilateral filter. Vis Comput 39, 1533–1555 (2023). https://doi.org/10.1007/s00371-022-02427-z

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00371-022-02427-z

Keywords

Navigation