Binary fuzzy rough set model based on triangle modulus and its application to image processing

Dan Wang, Mengda Wu
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引用次数: 2

Abstract

Rough sets theory is an important tool that process uncertainty information. In this paper, image processing based on rough sets theory is discussed in detail. The paper presents a binary fuzzy rough set model based on triangle modulus, which describes binary relationship by upper approximation and lower approximation. As image can be described by binary relationship, the upper approximation and lower approximation can be used to represent an image. The model in this paper is well fit for processing image that have gentle gray change. An edge detection algorithm by the upper approximation and the lower approximation of image is presented, and image denoising also is discussed. At last, its better effect can be testified by many experiments
基于三角模的二值模糊粗糙集模型及其在图像处理中的应用
粗糙集理论是处理不确定性信息的重要工具。本文详细讨论了基于粗糙集理论的图像处理方法。提出了一种基于三角模的二元模糊粗糙集模型,用上近似和下近似来描述二元关系。由于图像可以用二值关系来描述,所以可以用上近似和下近似来表示图像。该模型很适合处理灰度变化较小的图像。提出了一种基于图像上近似和下近似的边缘检测算法,并对图像去噪进行了讨论。最后,通过多次实验验证了该方法的良好效果
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