摘要
独立分量分析(Independent Compondent Analysis,ICA)是近年来提出的一种非常有效的数据分析方法,主要用来从混合数据中提取出原始的独立信号.在独立分量分析基本模型的基础上,计算在变换基下的投影,应用软门限算子进行去噪处理,结合实例对含噪图像进行去噪.实验结果表明,该算法在峰值信噪比和主观视觉效果上都比传统图像去噪方法具有明显的改善.
Independent component analysis（ICA） is a newly developed and powerful technique for recovering latent independent sources given only from mixtures.On the basis of analyzing basic model of independent component analysis,calculating projection under the transforms base,we carry on denoising processing by using the soft threshold operator,combing the example to carry on the denoising for noisy image.Experiments show that the proposed algorithm has a better peak signal noise ratio and subjective vision effect, compared with traditional image-denoising methods.
出处
《天津理工大学学报》
2009年第6期57-60,共4页
Journal of Tianjin University of Technology
关键词
独立分量分析
峰值信噪比
图像去噪
independent component analysis
peak signal-noise ratio
image denoising
