ITM Web Conf.
Volume 17, 20184th Annual International Conference on Wireless Communication and Sensor Network (WCSN 2017)
|Number of page(s)||8|
|Section||Session 1: Wireless Communication|
|Published online||02 February 2018|
A Digital Image Denoising Algorithm Based on Gaussian Filtering and Bilateral Filtering
Harbin University of Science and Technology, School of Test and Control Techniques and communication engineering, 150080 Harbin, China
2 Harbin Institute of Technology, School of Electronic engineering and Automation, 150001 Harbin, China
* Corresponding author: firstname.lastname@example.org
Bilateral filtering has been applied in the area of digital image processing widely, but in the high gradient region of the image, bilateral filtering may generate staircase effect. Bilateral filtering can be regarded as one particular form of local mode filtering, according to above analysis, an mixed image de-noising algorithm is proposed based on Gaussian filter and bilateral filtering. First of all, it uses Gaussian filter to filtrate the noise image and get the reference image, then to take both the reference image and noise image as the input for range kernel function of bilateral filter. The reference image can provide the image’s low frequency information, and noise image can provide image’s high frequency information. Through the competitive experiment on both the method in this paper and traditional bilateral filtering, the experimental result showed that the mixed de-noising algorithm can effectively overcome staircase effect, and the filtrated image was more smooth, its textural features was also more close to the original image, and it can achieve higher PSNR value, but the amount of calculation of above two algorithms are basically the same.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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