摘要
为了更好地保护图像的局部结构和提高图像插值算法的鲁棒性,结合基于几何对偶性的普通最小二乘和基于非局部均方的加权最小二乘来统计稳态区域形态,并基于该模型提出了一种改进的图像插值算法。算法首先采用非局部均方估计加权最小二乘模型系数,同时用核岭回归作为正则化项进行系数修正,考虑到核岭回归的有偏性,将基于边缘的普通最小二乘模型作为正则化项引进图像插值算法中,并对正则化参数进行自适应调整。与采用单一回归分析的插值算法相比较,该算法不但有效抑制了插值图像的边缘模糊和锯齿现象,而且插值结果具有较高的峰值信噪比和结构相似度。
In order to protect the local structure of images better and improve the robustness of image interpolation algorithm,an improved image interpolation algorithm is proposed.It is based on a model that combines ordinary least squares based geometric duality and weighted least squares based non-local mean squares to form the steady-state region.Firstly,coefficients of weighted least square are estimated by non-local mean,and then are corrected by kernel ridge regression.Taking into account the bias of kernel ridge regression,ordinary least square is introduced as a regular term.The regularization parameters are adjusted adaptively.Compared with the algorithm with ordinary least squares or weighted least squares,the algorithm suppresses the interpolation artifacts effectively,and the results of image interpolation have higher peak signal to noise ratio and structural similarity.
出处
《计算机工程与应用》
CSCD
北大核心
2015年第16期151-156,233,共7页
Computer Engineering and Applications
基金
国家自然科学基金(No.61071161
No.61201388)
特殊环境机器人技术四川省重点实验室基金(No.14zxtk03)
关键词
图像插值
几何对偶性
普通最小二乘
非局部均方
加权最小二乘
核岭回归
image interpolation
geometric duality
ordinary least square
non-local mean square
weighted least square
kernel ridge regression
