【摘要】 由于数字图像信息的复杂性和图像像素之间较强的相关性,在进行处理的过程中可能出现不确定性和不精确性的问题。粗集理论作为一种新的软计算方法,可以用作处理图像信息的含糊和不确定性问题的数学工具。本文将粗集理论应用到图像滤波中,在研究了传统图像滤波算法不能很好地解决图像细节丢失问题的基础上引入了图像色度比的概念,提出了基于色度比的图像噪声和边缘点的粗集判断标准,设计了一种基于粗集的新型滤波器。实验结果表明,该滤波器可以有效地去除图像中的噪声,并能较好地保持图像的边缘细节信息。更多还原

【Abstract】 Due to the complexity and relativity of image information,the problems of vagueness and uncertainty may emerge when the information is processed.Rough set theory is a new mathematical tool to deal with vagueness and uncertainty.It is a soft computing method and can be used as a useful tool for intellective information processing.Due to the fact that traditional image filtering does not solve the loss details of images,rough set theory is applied to image filtering.Chrominance Ratio is introduced,and a rough set judgement standard for checking noise pixels and the edge of images based on the chrominance ratio is presented,and a new filter based on rough set is designed.Experimental results show that the filter can preserve the edge and details of images very well when removing the noise effectively.更多还原