Applied and Computational Engineering

- The Open Access Proceedings Series for Conferences

Proceedings of the 5th International Conference on Computing and Data Science

Series Vol. 17 , 23 October 2023

Open Access | Article

Adaptive block level bilateral filtering algorithm

Yuhao Zhang * 1
1 Sichuan University

* Author to whom correspondence should be addressed.

Applied and Computational Engineering, Vol. 17, 77-85
Published 23 October 2023. © 2023 The Author(s). Published by EWA Publishing
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Citation Yuhao Zhang. Adaptive block level bilateral filtering algorithm. ACE (2023) Vol. 17: 77-85. DOI: 10.54254/2755-2721/17/20230917.


During the acquisition or transmission process, video images are subject to random signal interference and generate noise, which can hinder people's understanding of the image and subsequent processing work. Therefore, it is necessary to study video image denoising and filtering algorithms. Bilateral filter is one of many typical video image filtering algorithms. However, the traditional bilateral filter algorithm does not consider the differences in the contents of different regions of the image. It is difficult to obtain the optimal filtering effect by using a fixed filtering weight to filter the entire image, which leads to problems such as blurred image edges and inadequate details processing. This paper studies the influence of different filter block sizes on the bilateral filter effect, and proposes an algorithm to adaptively update the bilateral filter weight according to the block's variance. The experimental result shows that the performance of adaptive bilateral filter with different block sizes is expected to be better than that of traditional algorithms with fixed filter weights.


video noise, video filtering, bilateral filtering, adaptive strength


1. U. erkan, D. N. H. Thanh, L. M. Hieu and S. Engínoğlu, "An Iterative Mean Filter for Image Denoising," in IEEE Access, vol. 7, pp. 167847-167859, 2019, doi: 10.1109/ACCESS.2019.2953924.

2. K. Panetta, L. Bao and S. Agaian, "A new unified impulse noise removal algorithm using a new reference sequence-to-sequence similarity detector", IEEE Access, vol. 6, pp. 37225-37236, 2018.

3. S. Wang, " Dictionary learning based impulse noise removal via L1 - L1 minimization ", Signal Process., vol. 93, no. 9, pp. 2696-2708, 2013.

4. M. Wang, S. Zheng, X. Li and X. Qin, "A new image denoising method based on Gaussian filter," 2014 International Conference on Information Science, Electronics and Electrical Engineering, Sapporo, Japan, 2014, pp. 163-167, doi: 10.1109/InfoSEEE.2014.6948089.

5. R. G. Gavaskar and K. N. Chaudhury, "Fast Adaptive Bilateral Filtering," in IEEE Transactions on Image Processing, vol. 28, no. 2, pp. 779-790, Feb. 2019, doi: 10.1109/TIP.2018.2871597.

6. Bai Xiaodong, Shu Qin, Du Xiaoyan, etc Improved adaptive bilateral filtering algorithm [J] Progress in Laser and Optoelectronics, 2020, 57 (4): 041003.

7. Zhang B Y, Allebach J P. Adaptive bilateral filter for sharpness enhancement and noise removal[J]. IEEE Transactions on Image Processing, 2008, 17(5): 664-678.

8. Shi K Q, Wei W G. Image denoising method of surface defect on cold rolled aluminum sheet by bilateral filtering[J]. Surface Technology, 2018, 47(9): 317-323.

9. C. Xiong, L. Chen and Y. Pang, "An Adaptive Bilateral Filtering Algorithm and its Application in Edge Detection," 2010 International Conference on Measuring Technology and Mechatronics Automation, Changsha, China, 2010, pp. 440-443, doi: 10.1109/ICMTMA.2010.41.

10. W. Rong, Z. Li, W. Zhang and L. Sun, "An improved Canny edge detection algorithm," 2014 IEEE International Conference on Mechatronics and Automation, Tianjin, China, 2014, pp. 577-582, doi: 10.1109/ICMA.2014.6885761.

11. L. Xuan and Z. Hong, "An improved canny edge detection algorithm," 2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS), Beijing, China, 2017, pp. 275-278, doi: 10.1109/ICSESS.2017.8342913.

12. V. Aurich and J. Weule, "Non-linear Gaussian filters performing edge preserving diffusion", Proceedings of the DAGM Symposium Proceed, vol. 17, pp. 538-545, 1995.

13. S. Smith and J. Brady, "Susan—a new approach to low level image processing", International Journal of Computer Vision, vol. 23, no. 1, pp. 45-78, 1997.

14. C Tomasi and R Manduchi, "Bilateral filtering for gray and color images", Proceedings of the Sixth International Conference on Computer Vision, pp. 839-846, 1998.

15. Podpora M, Korbas G P, Kawala-Janik A. YUV vs RGB-Choosing a Color Space for Human-Machine Interaction[C]//FedCSIS (Position Papers). 2014: 29-34.

16. Keith Jack. Video Demystified. ISBN 1-878707-09-4.

17. S. Winkler and P. Mohandas, "The Evolution of Video Quality Measurement: From PSNR to Hybrid Metrics," in IEEE Transactions on Broadcasting, vol. 54, no. 3, pp. 660-668, Sept. 2008, doi: 10.1109/TBC.2008.2000733.

Data Availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. Authors who publish this series agree to the following terms:

1. Authors retain copyright and grant the series right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this series.

2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the series's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this series.

3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See Open Access Instruction).

Volume Title
Proceedings of the 5th International Conference on Computing and Data Science
ISBN (Print)
ISBN (Online)
Published Date
23 October 2023
Applied and Computational Engineering
ISSN (Print)
ISSN (Online)
© 2023 The Author(s)
Open Access
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Copyright © 2023 EWA Publishing. Unless Otherwise Stated