Regularized Kernel Regression for Image Deblurring
Hiroyuki Takeda, Sina Farsiu, Peyman Milanfar · 2006
The framework of kernel regression [1], a non- parametric estimation method, has been widely used in different guises for solving a variety of image processing problems including denoising and interpolation [2]. In this paper, we extend the use of kernel regression for deblurring applications. Furthermore, we show that many of the popular image reconstruction techniques are special cases of the proposed framework. Simulation results confirm the effectiveness of our proposed methods.