摘要
针对噪声在多小波分解后的尺度性以及图像本身的特性,提出了一种基于遗传算法的多小波自适应去噪算法,该方法能通过遗传算法自适应地寻求去噪后图像的最小均方误差.实验结果表明,该算法优于传统算法,不仅能有效滤除图像的噪声,而且能较好地保留图像的边缘信息,具有更加理想的去噪效果.
Aiming at the scaling of the noise after muhiwavelet decomposition and the characteristic of image, a multiwavelet adaptive denoising method was proposed based on genetic algorithm. This method can adaptivly look for the least RMSE of the denoised image according to genetic algorithm. The experimental results show that this algorithm is superior to the traditional methods. It can not only remove the noise of image, hut remain the better edge of image, and this method has more perfect denoising effects.
出处
《红外与毫米波学报》
SCIE
EI
CAS
CSCD
北大核心
2009年第1期77-80,共4页
Journal of Infrared and Millimeter Waves
基金
国家自然科学基金资助项目(60662003,60462003)
关键词
图像去噪
自适应阈值
遗传算法
图像特性
image denoising
adaptive threshold
genetic algorithm
image characteristic
