摘要
提出了一种非局部的特征方向图像插值方法,有效地保持了插值图像轮廓的光滑,抑制了图像边缘的模糊.这种方法把非局部Hessian矩阵的特征向量视为图像特征方向,使图像能量泛函沿这个方向进行扩散,其扩散强度由图像局部Hessian矩阵特征值参与控制.它克服了传统方法以梯度方向指示图像特征方向的局部性,使图像能量泛函沿正确方向扩散,避免了对图像特征的模糊.数值实验结果显示,该方法既能很好地重建插值图像的边缘,又不会在插值图像中产生伪影或图像边缘失真.
A method of image interpolation with non-local feature directions is proposed. This method respectes the smooth of the contour profile of interpolated image and retrains blur edges. The eigenvector of the non-local Hessian matrix is considered as the image featrue direction. The diffusion of image energy functional is controlled by the eigenvalue of image local Hessian along the direction. It overcomes the local limit of gradient pointing image feature and drives image energy functional to diffuse along corrected direction. Thus the blur of image feature is avoids. Numerical experiments on real images show that images interpolated by the proposed method have better interpolated edges mad are almost artifact-free.
出处
《电子学报》
EI
CAS
CSCD
北大核心
2016年第5期1064-1070,共7页
Acta Electronica Sinica
基金
国家自然科学基金(No.61202349)
重庆市基础与前沿研究计划一般项目(No.cstc2013jcyj A40058
No.cstc2015jcyj A0142)
关键词
非局部梯度
非局部曲率
总变差
变分方法
图像插值
non-local gradient
non-local curvature
total variation
variational methods
image interpolation
