Coll. of Eng. and Appl. Sci., Rochester Univ., NY.
IEEE Trans Image Process. 1993;2(2):141-51. doi: 10.1109/83.217219.
The estimation of the point spread function (PSF) for blur identification, often a necessary first step in the restoration of real images, method is presented. The PSF estimate is chosen from a collection of candidate PSFs, which may be constructed using a parametric model or from experimental measurements. The PSF estimate is selected to provide the best match between the restoration residual power spectrum and its expected value, derived under the assumption that the candidate PSF is equal to the true PSF. Several distance measures were studied to determine which one provides the best match. The a priori knowledge required is the noise variance and the original image spectrum. The estimation of these statistics is discussed, and the sensitivity of the method to the estimates is examined analytically and by simulations. The method successfully identified blurs in both synthetically and optically blurred images.
提出了一种用于模糊识别的点扩散函数 (PSF) 估计方法，这通常是真实图像恢复的必要第一步。PSF 估计是从一组候选 PSF 中选择的，这些候选 PSF 可以使用参数模型构建，也可以通过实验测量得到。PSF 估计被选择为在恢复残余功率谱与其期望值之间提供最佳匹配，该期望值是在假设候选 PSF 等于真实 PSF 的情况下得出的。研究了几种距离度量来确定哪一种提供最佳匹配。所需的先验知识是噪声方差和原始图像频谱。讨论了这些统计量的估计，并且通过分析和模拟检查了该方法对估计值的敏感性。该方法成功地识别了合成和光学模糊图像中的模糊。
