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Improved Image Edge Clipping and Filtering Algorithm Based on Local Structural Shape |
SUN Xiao-hui1, CAI Yong-hong2, LIN Yan-fei1 |
1. Guangzhou Institute of Technology, Guangzhou, Guangdong 510075, China
2. Guangzhou Institute of Measure and Testing Technology, Guangzhou, Guangdong 510663, China |
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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.
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Received: 08 May 2021
Published: 06 January 2022
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