%0 Journal Article
%T 自适应非张量积小波紧框架图像去噪<br>SELF-ADAPTIVE NON-TENSOR PRODUCT TIGHT WAVELET FRAME IMAGE DENOISING
%A 作者
%A 黄素莹
%A 羿旭明
%J 数学杂志
%D 2018
%X 本文研究了图像去噪的问题.利用光滑余因子协调法，构造了样条空间S64（△mn（2））中的二元六次样条函数，以此作为尺度函数，并基于酉延拓定理，构造了非张量积小波紧框架.利用构造的非张量积小波紧框架，提出了基于香农熵自适应确定最优小波紧框架分解层数以及改进的NormalShrink自适应阈值算法，并给出了图像去噪实例和结果分析，获得了理想的数值结果，显示了本文方法的有效性.<br>In this paper, we research the problem of image denoising. Via the use of the smoothing cofactor-conformality method, it constructs the bivariate and sextic spline function in spline space S64(△mn(2)), and while do it as scaling function, the non-tensor product tight wavelet frame is constructed based on the unitary extension principe. Then we propose the algorithm of the optimal decomposition levels of tight wavelet frame is self-adaptive determined based on the shannon entropy and the modified NormalShrink self-adaptive threshold algo-rithm by using the non-tensor product tight wavelet frame above, and offer the cases of image denoising and result analysis. The ideal numerical results are obtained, which verify the validity of this algorithm
%K 非张量积小波紧框架 最优分解层数 自适应阈值 图像去噪&lt
%K br&gt
%K non-tensor product tight wavelet frame optimal decomposition levels NormalShrink self-adaptive threshold image denoising
%U http://sxzz.whu.edu.cn/sxzz/ch/reader/view_abstract.aspx?file_no=20180319&flag=1