摘要
针对经典ICM进行分析并找出其结构中的缺陷,提出一种改进型交叉视觉皮层模型(Improved ICM,IICM)。该模型不仅减少了待定参数的个数,还构造了赋时矩阵T用于解决迭代次数的确定问题,同时实现了图像空间信息到时间信息的转换;其次,利用T提供的信息确定噪声点的具体位置;最后,提出基于IICM的自适应图像去噪算法,完成对图像脉冲噪声的有效滤除。该方法仅对受噪声污染的像素点进行处理,并可自适应调整区域窗口的尺寸,在去噪效果和运行效率上同其他方法相比具有明显的优势。
First, the the proposed IICM basic classic ICM is analyzed and its structural drawbacks are detected. is presented, which not only declines the number of parameters required Second, setting, but also constructs the time matrix T to settle the problem of setting the number of iterative times; meanwhile, he transformation from the image spatial information to time information can be realized. Third, the noisy pixels are located uilizing the information provided by the time matrix T in IICM. Finally, the task of efficiently filtering the impulsive noise in the image is completed by the proposed adaptive algorithm for image de-noising based on IICM. Because of only dealing with the polluted pixels and adjusting the size of area window adaptively, the proposed technique has remarkable superiority over other ones in both simulation performance and running efficiency.
出处
《吉林大学学报（工学版）》
EI
CAS
CSCD
北大核心
2014年第1期184-190,共7页
Journal of Jilin University:Engineering and Technology Edition
基金
国家自然科学基金项目(61309008
61309022)
陕西省自然科学基金项目(2013JQ8031)
中国博士后科学基金项目(2013M532133)
武警工程大学自然研究基础基金项目(WJY-201214
WJY-201312)
关键词
计算机应用
图像去噪
交叉视觉皮层模型
赋时矩阵
computer application
image de-noising
intersecting cortical model
time matrix
