基于局部结构形态改进图像边缘限幅滤波算法研究

doi:10.3969/j.issn.1000-1158.2022.01.04

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Abstract It is easy to cause the problem that the high frequency edges are suppressed, the continuity of the edges is destroyed and the structural features of the target are lost when the classical clipping and filtering algorithm(CFA) is applied to the edge denoising. Therefore, an improved CFA based on local structure shape features is proposed for image edge filtering. Based on the principle of CFA, a sliding template composed of 5 adjacent edge points and sliding along the edge is used in the algorithm. The point that overruns the threshold in the sliding template is predicted by the local structural shape model. To be specific, the model of the local structural contour is established by using the sliding template and applied to predict the overrun point. Then, it is judged that whether the difference between the overrun point and its predicted value is greater than the threshold, in the physical sense it means that whether the step, flange or sharp structural features are encountered. In order to test the ability of the new algorithm in edge preservation and noise reduction, comparative experiments with the traditional algorithmare carried out. The experimental results show that the improved CFA based on local structure features not only has efficient denoising ability, but also has significant protection effect on the high-frequency edge of the target structure.

Key words： metrology image edge filtering clipping and filtering algorithm local structure shape machine vision

Received: 08 May 2021 Published: 06 January 2022

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TB96

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	Articles by authors
	SUN Xiao-hui
	CAI Yong-hong
	LIN Yan-fei

Cite this article:

SUN Xiao-hui,CAI Yong-hong,LIN Yan-fei. Improved Image Edge Clipping and Filtering Algorithm Based on Local Structural Shape[J]. Acta Metrologica Sinica, 2022, 43(1): 21-25.

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http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2022.01.04 OR http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2022/V43/I1/21

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