摘要
针对自然条件下获取的图像通常含有混合噪声的情况,提出了二维小波变换与独立分量分析(independent component analysis,ICA)的自适应图像混合噪声消除方法。该方法不需要大量观测图像样本,无需事先掌握观测图像信号类型的详细信息,可针对单个观测图像进行自适应混合噪声消除。结果表明,该方法可以有效地消除图像中的混合噪声,突出图像细节,改善图像质量。
A new adaptive method of image de-noising based on two-dimensional wavelet transform and independent component analysis （ICA） is presented. It does not need a lot of observed image samples, and it is not necessary to know the details of the observed image signal type in advance. A single observed image could be de-noised by this method adaptive- ly. The principle of ICA virtual observed noise channels de-noising and two-dimensional wavelet transform constructing those channels are introduced , and the experimental results based on this method are given. The results show that by using the proposed method the hybrid noise is removed effectively and the image details are protruded and the image quality is improved.
出处
《武汉大学学报（信息科学版）》
EI
CSCD
北大核心
2008年第2期136-139,171,共5页
Geomatics and Information Science of Wuhan University
基金
河南省高等学校青年教师自主计划研究基金资助项目([2005]461)
关键词
二维小波变换
独立分量分析
图像消噪
虚拟通道
two-dimensional wavelet transform
independent component analysis
image de-noise
virtual channel
