计算机科学 ›› 2016, Vol. 43 ›› Issue (Z11): 208-209.doi: 10.11896/j.issn.1002-137X.2016.11A.047
孙少超
SUN Shao-chao
摘要： 利用GMM模型对自然图像块进行学习,对高斯分量的协方差矩阵做PCA,用其特征向量组成的矩阵作为子字典,用特征值 的大小作为对稀疏系数加权的依据,并将该模型应用到CSR模型中得到一种新的去噪模型,并给出模型的优化算法。为了验证提出的模型的有效性,设计了比较的仿真实验,实验表明与一些先进的模型相比,该方法具有优势。
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