改进的图像恢复张量扩散模型  

Improved Tensor Diffusion Model for Image Restoration

作　　者：刘国军[1] 张选德[1] 

机构地区：[1]宁夏大学数学计算机学院,银川750021

出　　处：《计算机辅助设计与图形学学报》2016年第9期1534-1542,共9页Journal of Computer-Aided Design & Computer Graphics

基　　金：国家自然科学基金(61461043;61362029;11261044;51269024;61462002);宁夏自然科学基金(NZ1309);宁夏大学自然科学基金(ZR1405)

摘　　要：受噪声的影响,图像的局部梯度特征很难被准确地估计,这影响了非线性扩散方法的滤波效果.根据影响视觉效果的2个低层次局部特征——相位一致性和梯度,提出一种各向异性张量扩散模型.首先结合梯度信息提出了极大相位一致性方向投影的散度矩阵;其次构造一种改进的张量扩散模型,并给出了相应的离散差分格式和算法流程.通过数值实验,验证了文中模型在计算效率、客观量化和视觉效果方面的有效性.The local gradient features of image can not be well measured due to the exist of noise, which affects the filtering effect of nonlinear diffusion method. Using two low-level local features of phase congruency and gradient, we propose an improved anisotropic tensor diffusion model. Firstly, a scatter matrix is designed by projection on maximum direction of phase congruency. Secondly, a tensor diffusion model is constructed. Further, a finite difference scheme and the algorithm procedure are listed. Finally, numerical experiments illustrate the computational efficiency of proposed model, objective assessment, and visual effect.

关 键 词：视觉信息 相位一致性 梯度特征 张量扩散 散度矩阵 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]