On Some Smoothing Techniques Used in Image Restoration
研究了用不同正则化方法复原模糊或含噪图像的问题，包括线性正则化、约束去卷积、最大熵复原和最小二乘滤波，并指出常用平滑度选择方法会导致过度平滑。
SUMMARY The problem is considered of restoring a blurred and/or noisy image using various regularization prescriptions. Preliminary work concerns the invertibility of point spread functions and the construction of a stochastic model for images. A simple linear regularization procedure is introduced, as well as the special cases of constrained deconvolution, maximum entropy restoration and least-squares filtering. Optimal choices for the degree of smoothing are obtained for the case of low noise-to-signal ratios. Certain techniques, prevalent in the image-restoration literature for choosing the degree of smoothing, are shown to oversmooth, in a well-defined sense.