关键词: 超分辨率重建, 人脸图像, 自适应规整化, 数值解法

Abstract: This paper proposes an eigen-subspace based regularization method for face image Super-Resolution Reconstruction（SRR），and presents three numerical solutions to the SRR problem.Under the affine motion model，it extends the interpolation of image using the four-neighbor interpolation to the estimation of image gradient field，and derives the Jacobian of the High Resolution（HR） image with respect to the motion parameters.By means of the total and partial differential expansions of the SRR cost functional，it reduces the nonlinear SRR problem to a linear problem and presents three iterative algorithms for the joint estimation of motion parameters and HR image.An adaptive calculation method for the SRR regularization parameter is proposed to fulfill the automatic SRR of facial imagery.Simulation results verify the superiority of the proposed face sub-space regularized method over the traditional regularization methods（Laplacian and Total Variation（TV）） and demonstrate good face image SRR performance even in the case of low signal to noise ratio.

Key words: super-resolution reconstruction, face images, adaptive regularization, numerical solutions