摘要
基于噪声检测的中值滤波器已广泛用于消除图像中的椒盐噪声，然而在高噪声密度情况下，对噪声像素的定位不准确很容易造成图像边缘的模糊。本文提出了一种基于GA-BP的椒盐噪声滤波算法，克服了这一缺陷。算法首先用遗传算法优化的BP网络对图像中的噪声像素定位，然后引入保边函数和PRP算法求目标函数的极值进而实现图像的去噪处理。实验结果表明，该算法比传统滤波算法效果有明显改善，且具有良好的泛化性、鲁棒性和自适应性。
Noise detection-based median filters have been widely adopted to reduce salt and pepper noise in images However, since noise pixel is not detected accurately, it is likely to blur the fringe of image under the case of high noise density. An algorithm of salt and pepper noise filter is proposed that is based on GA-BP algorithm noise detector to remove the salt and pepper noise in images. The algorithm firstly detects noise pixel＇s location in image by using optimized GA-based BP network. Then, it introduce edge-preserving function and PRP algorithm to solve the objective function of extreme value and realize the image denoising. Compared with the traditional algorithms, experimental results show that the proposed algorithm has an evident improvement, and good characters of generalization, robust and self-adaptive.
出处
《光电工程》
CAS
CSCD
北大核心
2011年第2期59-64,共6页
Opto-Electronic Engineering
基金
河南省教育厅自然科学研究计划基金资助项目（2009A510017）
关键词
GA-BP算法
椒盐噪声
噪声检测
保边函数
PRP算法
GA-BP algorithm
salt ＆ pepper noise
noise detection
edge-preserving function
PRP algorithm
