Influence impact of window-size, spatial and radiometric variance, of image bilateral denoising algorithm under AWGN ambiance†


  • Vorapoj Patanavijit Department of Electrical and Electronic Engineering, Vincent Mary School of Engineering, Assumption University of Thailand, Samuthprakarn 10540, Thailand


bilateral filter, denoising algorithm, digital image processing, radiometric variance, window size


Image denoising algorithms are one of the most crucial processes for improving image quality; therefore, a number of denoising algorithms have been proposed.  One of the most effective denoising filters is the bilateral filter.  The efficiency of the bilateral filter depends on the window size, spatial variance and radiometric variance.  In this paper, the impact of the three parameters on the quality of the denoising is investigated.  In our experiment, the bilateral filter was applied to suppress the noise of eight standard test images corrupted by five different levels of Gaussian noise.  The optimal parameters with regard to the PSNR of the denoised images were then determined.


Anantrasirichai, N., Nicholson, L., Morgan, J. E., Erchova, I., Mortlock, K., North, R. V., . . . Achim, A. (2014). Adaptive-weighted bilateral filtering and other pre-processing techniques for optical coherence tomography. Computerized Medical Imaging and Graphics, 38(6), 526-539.

Bae, T.-W. (2013). Spatial and temporal bilateral filter for infrared small target enhancement, Infrared Physics & Technology, 63, 42-53. DOI: 10.1016/j.infrared.2013.12.007

Chang, H., Hsiehy, T., Tingy, Y., & Chu, W. (2014). Rician noise removal in MR images using an adaptive trilateral filter. International Conference on Biomedical Engineering and Informatics (BMEI). Pages 467-471. Doi: 10.1109/BMEI.2011.6098281

Chaudhury, K. N., Sage, D., & Unser, M. (2011). Fast O(1) bilateral filtering using trigonomtric range kernels. IEEE Transactions on Image Processing, 20(12), 3376-3382. DOI: 10.1109/TIP.2011.2159234

Chen, D., Ardabilian, M., & Chen, L. (2015). A fast trilateral filter-based adaptive support weight method for stereo matching. IEEE Transactions on Circuits and Systems for Video Technology, 25( 5), 730-743. DOI: 10.1109/TCSVT.2014.2361422

Dai, L., Yuan, M., & Zhang, X. (2014). Accelerate bilateral filter using Hermite polynomials. Electronics Letters, 50(20), 1432-1434. DOI: 10.1049/el.2014.2758

Elad, M. (2002). On the origin of the bilateral filter and ways to improve it. IEEE Transactions on Image Processing, 11(10), 1141-1151. DOI: 10.1109/TIP.2002.801126.

Farsiu, S., Elad, M., & Milanfar, P. (2006). Multiframe demosaicing and super-resolution of color images. IEEE Transactions on Image Processing, 15(1), 141-159. DOI: 10.1109/TIP.2005.860336

Farsiu, S., Robinson, M. D., Elad, M., & Milanfar, P. (2004). Fast and robust multiframe super resolution. IEEE Transactions on Image Processing, 13(10), 1327-1344.

Gabiger-Rose, A., Kube, M., Weigel, R., & Rose, R. (2014). An FPGA-based fully synchronized design of a bilateral filter for real-time image denoising. IEEE Transactions on Industrial Electronics, 61( 8), 4093-4104. DOI: 10.1109/TIE.2013.2284133

Garnett, R., Huegerich, T., Chui, C., & He, W. (2005). A universal noise removal algorithm with an impulse detector. IEEE Transactions on Image Processing, 14(11), 1747-1754.

Gonzalez, R. C., & Woods, R. E. (2002). Digital image processing (2nd ed.). Upper Saddle River, NJ, USA: Prentice-Hall.

Hondt, O. D., Guillaso, S., & Hellwich, O. (2013). Iterative bilateral filtering of polarimetric SAR data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 6(3), 1628-1639. DOI: 10.1109/JSTARS.2013.2256881

Hung, K.-W., & Siu, W.-C. (2012). Fast image interpolation using the bilateral filter. IET Image Process, 6(7), 877-890. DOI: 10.1049/iet-ipr.2011.0050

Jung, S.-W. (2013). Enhancement of image and depth map using adaptive joint trilateral filter. IEEE Transactions on Circuits and Systems for Video Technology, 23(2), 258-269. DOI: 10.1109/TCSVT.2012.2203734

Kim, J., Jeon, G., & Jeong, J. (2014). Joint-adaptive bilateral depth map upsampling. Signal Processing: Image Communication, 29(4), 506-513.

Lie, W.-N., Chen, C.-Y., & Chen, W.-C. (2011). 2D to 3D video conversion with key-frame depth propagation and trilateral filtering. Electronics Letters, 47(5), 319-321. DOI: 10.1049/el.2010.2912

Lin, G., Chen, C., Kuo, C., & Lie, W. (2014). A computing framework of adaptive support-window multi-lateral filter for image and depth processing. IEEE Transactions on Broadcasting, 60(3), 452-463. DOI: 10.1109/TBC.2014.2330391

Lin, C., Tsai, J., & Chiu, C. (2010). Switching bilateral filter with a texture/noise detector for universal noise removal. IEEE Transactions on Image Processing, 19(9), 2307-2320. DOI: 10.1109/TIP.2010.2047906

Lu, Q., & Fang, X. (2013). Joint trilateral motion vector filter for bidirectional motion compensation. Electronics Letters, 49(13), 798-800. DOI: 10.1049/el.2013.0995

Onuki, M.,& Tanaka, Y. (2014). Trilateral filter on graph spectral domain, IEEE International Conference on Image Processing (ICIP 2014). pp. 2046-2050.

Patanavijit, V. (2015). The bilateral denoising performance influence of window, spatial and radiometric variance. The IEEE International conference on Advanced Informatics: Concepts, Theory and Application (ICAICTA 2015), Chonburi, Thailand. pp. 1-6.

Peng, H., Rao, R., & Dianat, S. A. (2014). Multispectral image denoising with optimized vector bilateral filter. IEEE Transactions on Image Processing, 23(1), 264-273. DOI: 10.1109/TIP.2013.2287612

Pinto, A. M., Costa, P. G., Miguel, V. C., & Moreira, A. P. (2014). Enhancing dynamic videos for surveillance and robotic applications: the robust bilateral and temporal filter. Signal Processing: Image Communication, 29(1), 80-95.

Shi, B., Wei, J., & Pang, M. (2014). A modified optical flow algorithm based on bilateral-filter and multi-resolution analysis for PIV image processing, Journal of Flow Measurement and Instrumentation, 38, 121-130. DOI: 10.1016/j.flowmeasinst.2014.05.005

Tomasi, C., & Manduchi, R. (1998). Bilateral filtering for gray and color images, Proceedings of the 1998 IEEE International Conference on Computer Vision, Bombay, India. pp. 839-846.

Wang, S., Hu, B., Dong, X., & Yan, X. (2013). An improved super-resolution reconstruction algorithm based on regularization. ISCC-C '13 Proceedings of the 2013 International Conference on Information Science and Cloud Computing Companion. pp. 716-721. DOI: 10.1109/ISCC-C.2013.44

Wang, C., Zhang, L., He, Y., & Tan, Y. (2010). Frame rate up-conversion using trilateral filtering. IEEE Transactions on Circuits and Systems for Video Technology 20(6), 886-893. DOI: 10.1109/TCSVT.2010.2046057

Yang, Q. (2014). Hardware-efficient bilateral filtering for stereo matching. IEEE Transactions on Pattern Analysis and Machine Intelligence, 36(5), 1026-1032. DOI: 10.1109/TPAMI.2013.186

Yang, Q. (2015). Recursive approximation of the bilateral filter. IEEE Transactions on Image Processing, 24(6), 1919-1927. DOI: 10.1109/TIP.2015.2403238

Yang, Q., Ahuja, N., Yang, R., Tan, K.-H., Davis, J., Culbertson, B., . . . Wang, G. (2013). Fusion of median and bilateral filtering for range image upsampling. IEEE Transactions on Image Processing, 22(12), 4841-4852. DOI: 10.1109/TIP.2013.2278917

Yang, K., Zhao, Y., & Deng, N. (2015), Fast bilateral filtering using the discrete cosine transform and the recursive method. Optik - International Journal for Light and Electron Optics, 126(6), 592-595.

Yu, Y., Dong, G., & Wang, J. (2011). Despeckling trilateral filter. IEEE Workshop on IVMSP 2011. pp. 42-47. DOI: 10.1109/IVMSPW.2011.5970352

Yu, H., Zhao, L., & Wang, H. (2011). An efficient edge-based bilateral filter for restoring real noisy image. IEEE Transactions on Consumer Electronics, 57(2), 682-686.

Zheng, Y., Fu, H., Au, O. K.-C., & Tai, C.-L. (2011). Bilateral normal filtering for mesh denoising. IEEE Transactions on Visualization and Computer Graphics, 17(10), 1521-1532. DOI: 10.1109/TVCG.2010.264

Zhang, Y., Tian, X., & Ren, P. (2014). An adaptive bilateral filter based framework for image denoising. Neurocomputing, 140(1), 299-316(18).

Zhang, W. G., Zhang, Q., & Yang, C. S. (2011). Improved bilateral filtering for SAR image despeckling. Electronics Letters, 47(4), 286-288. DOI: 10.1049/el.2010.2982




How to Cite

Vorapoj Patanavijit. (2023). Influence impact of window-size, spatial and radiometric variance, of image bilateral denoising algorithm under AWGN ambiance†. Journal of Current Science and Technology, 7(1), 59–78. Retrieved from



Research Article