Inst. of Inf. Theory and Autom., Czechoslovak Acad. of Sci., Prague.
IEEE Trans Image Process. 1996;5(3):533-8. doi: 10.1109/83.491327.
The article is devoted to the feature-based recognition of blurred images acquired by a linear shift-invariant imaging system against an image database. The proposed approach consists of describing images by features that are invariant with respect to blur and recognizing images in the feature space. The PSF identification and image restoration are not required. A set of symmetric blur invariants based on image moments is introduced. A numerical experiment is presented to illustrate the utilization of the invariants for blurred image recognition. Robustness of the features is also briefly discussed.
本文致力于针对线性移不变成像系统获取的模糊图像，基于特征的识别，与图像数据库相对比。所提出的方法包括通过对模糊不变的特征来描述图像，并在特征空间中识别图像。不需要进行 PSF 识别和图像恢复。引入了一组基于图像矩的对称模糊不变量。提出了一个数值实验来说明不变量在模糊图像识别中的应用。还简要讨论了特征的稳健性。
