基于量子柔性表示的图像边缘提取算法

Edge extraction algorithm based on quantum flexible representation

针对当前边缘提取算法的实时性问题,提高图像边缘连续性,提出基于量子柔性表示(flexible representation of quantum,FRQ)的边缘提取算法。将图像进行量子柔性表示,利用量子序列的叠加态存储图像的所有像素,通过量子并行计算显著提高效率,得到FRQ图像;对FRQ图像进行X、Y方向的平移变换,获得整个图像的邻域像素的相对量子;根据量子比特定义量子黑盒UΩ,结合Sobel算子计算像素的Sobel梯度,判断不同类别的像素并提取图像的边缘。实验结果表明,与当前边缘提取算法相比,所提方法具有更好的边缘连续性与更丰富的细节边缘。

Aiming at the real-time problem of the current edge extraction algorithm,and to improve the edge continuity,an edge detection algorithm based on FRQ（flexible representation of quantum）was proposed.The image was represented by quantum flexibility,all pixels of the image were stored by the superposition state of the quantum sequence,all pixels of the image were stored by the superposition state of the quantum sequence,quantum parallel computing significantly improved the efficiency,and FRQ image was got.The X image and the Y direction translation transformation were obtained for FRQ images,and the relative quantum of the neighborhood pixels of the whole image was obtained.Quantum black box was defined based on quantum bits of neighborhood pixels,Sobel gradient of pixels was calculated with Sobel operator,Sobel gradient was used to determine the different types of pixels and the edge of the image was extracted.Experimental results show the proposed algorithm has better edge continuity with richer detail edges compared with the current edge extraction algorithm.