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http://dx.doi.org/10.6109/jkiice.2021.25.9.1176

Modified Gaussian Filter Algorithm using Quadtree Segmentation in AWGN Environment  

Cheon, Bong-Won (Dept. of Smart Robot Convergence and Application Eng., Pukyong National University)
Kim, Nam-Ho (Dept. of Control and Instrumentation Eng., Pukyong National University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.25, no.9, 2021 , pp. 1176-1182 More about this Journal
Abstract
Recently, with the development of artificial intelligence and IoT technology, automation, and unmanned work are progressing in various fields, and the importance of image processing, which is the basis of AI object recognition, is increasing. In particular, in systems that require detailed data processing, noise removal is used as a preprocessing step, but the existing algorithm does not consider the noise level of the image, so it has the disadvantage of blurring in the filtering process. Therefore, in this paper, we propose a modified Gaussian filter that determines the weight by determining the noise level of the image. The proposed algorithm obtains the noise estimate for the AWGN of the image using quadtree segmentation, determines the Gaussian weight and the pixel weight, and obtains the final output by convolution with the local mask. To evaluate the proposed algorithm, it was simulated compared to the existing method, and superior performance was confirmed compared to the existing method.
Keywords
Image processing; AWGN; Gaussian filter; Quadtree segmentation;
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Times Cited By KSCI : 1  (Citation Analysis)
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