Laboratory of Image Science and Technology, Department of Computer Science and Engineering, Southeast University, China.
IEEE Trans Image Process. 2010 Mar;19(3):596-611. doi: 10.1109/TIP.2009.2036702. Epub 2009 Nov 20.
Processing blurred images is a key problem in many image applications. Existing methods to obtain blur invariants which are invariant with respect to centrally symmetric blur are based on geometric moments or complex moments. In this paper, we propose a new method to construct a set of blur invariants using the orthogonal Legendre moments. Some important properties of Legendre moments for the blurred image are presented and proved. The performance of the proposed descriptors is evaluated with various point-spread functions and different image noises. The comparison of the present approach with previous methods in terms of pattern recognition accuracy is also provided. The experimental results show that the proposed descriptors are more robust to noise and have better discriminative power than the methods based on geometric or complex moments.
处理模糊图像是许多图像应用中的一个关键问题。现有的获得对中心对称模糊不变的模糊不变量的方法是基于几何矩或复矩的。在本文中，我们提出了一种使用正交勒让德矩来构造一组模糊不变量的新方法。给出并证明了模糊图像的勒让德矩的一些重要性质。利用不同的点扩散函数和不同的图像噪声对所提出的描述符的性能进行了评估。还提供了基于模式识别精度与以前的方法进行比较的结果。实验结果表明，与基于几何矩或复矩的方法相比，所提出的描述符对噪声更鲁棒，具有更好的区分能力。
