摘要
独立分量分析(Independent component analysis,ICA)作为一种有效的盲源分离方法,其目的是从由传感器收集到的混合信号中分离出相互独立的源信号,使得这些分离出来的信号之间尽可能的相互独立。针对红外线列扫描图像,提出了一种基于ICA的图像增强方法,该方法能够有效地去除红外线列扫描图像的非均匀性干扰。阐述了ICA的基本原理,介绍了基于负熵判据的FastICA算法,给出了该方法的具体实现步骤及相应的实验处理结果。结果表明,利用该方法能够达到图像增强的目的。
The Independent Component Analysis（ICA） is a kind of effective blind source separation methods, which aims to separate the independent source signals from the mixed signals, making the output signals to be mutually independent as far as possible, from the collects of signals observed. A method of infrared line-scan image processing based on ICA is presented, which can remove effectively the uneven interference of the image. The principle of ICA and a FastICA algorithm based on negentropy criterion is introduced. The detailed processes of the method and results are given, which show that the method can realize the aim of enhancing image.
出处
《光学技术》
CAS
CSCD
北大核心
2009年第2期288-291,共4页
Optical Technique
