一种基于LoG算子的量子图像边缘检测算法

A quantum image edge detction algorithm based on LoG operator

针对图像边缘的实时提取问题,设计了一种基于经典高斯-拉普拉斯算子(LoG算子)的量子LoG图像边缘检测算法。通过在经典计算机上利用Matlab软件对该量子LoG算法进行模拟仿真计算,证明了该量子LoG算法可以快速、有效地实现对图像边缘的识别与提取。此外,还考察了两类退相干效应对此算法的影响。计算结果表明,相较于目前已有的相关量子图像边缘检测算法,量子LoG算法具有更好的抗噪特性。

Aiming at the problem of real-time image edge extraction, a quantum LoG image edge detection algorithm based on classical Gauss-Laplacian operator(LoG operator) is designed. By simulating the quantum LoG algorithm with Matlab software on a classical computer, it is proved that the quantum LoG algorithm can quickly and effectively realize the recognition and extraction of image edges. In addition,the influence of two types of decoherence effects on the algorithm is also investigated. The calculation results show that compared with the existing corresponding quantum image edge detection algorithms, the quantum LoG algorithm has better anti-noise characteristics.