节点文献
基于区域信息的模糊加权图像恢复方法
Region-information Based Fuzzy Weighted Mean Approach for Image Restoration
【摘要】 传统滤波器的优点是简单快速和不需图像的先验知识,但其效果不佳。neuro-fuzzy滤波器的优点是滤波效果较好,但滤波时需要一段训练学习时间。针对这点,文章提出了一种新的模糊滤波器,该滤波器除了具有上述两类滤波器优点的同时,又避免了它们各自的不足。实验表明该方法滤波效果优于传统的滤波器和其它模糊滤波器。
【Abstract】 Conventional filter has the benefits that it is simple and quick, but its performance is not good. Neuro-fuzzy filters has the benefits that its performance is good, but it needs a lot of training and learning time. In the light of this, a new fuzzy filter is proposed in this paper. The filter has advantages of both kinds of filters besides avoiding shortcomings of them. Experimental result shows that new-filter gives superior performance compared with conventional filters and other fuzzy filtes.
【关键词】 模糊加权平均滤波器;
脉冲噪声;
区域信息;
图像恢复;
模糊参数;
【Key words】 Weighted fuzzy mean filter; Impulsive noise; Region information; Image restoration; Fuzzy parameter;
【Key words】 Weighted fuzzy mean filter; Impulsive noise; Region information; Image restoration; Fuzzy parameter;
【基金】 国家自然科学基金资助项目(69972041)
- 【文献出处】 计算机工程 ,Computer Engineering , 编辑部邮箱 ,2003年19期
- 【分类号】TN911.73
- 【被引频次】3
- 【下载频次】84