基于预存储权值矩阵的多尺度Hough变换直线提取算法

Straight Line Extraction via Multi-scale Hough Transform Based on Pre-storage Weight Matrix

针对Hough变换提取直线算法在速度、精度和影像大小三方面的局限,提出一种基于预存储权值矩阵的多尺度Hough变换算法。首先阐述对经典Hough变换的改进策略,对参数空间中ρ的分辨率和θ的分辨率的最佳取值也作了探讨,之后详细说明基于预存储权值矩阵的多尺度Hough变换直线提取算法。实验证明,本文提出的算法能显著提高实际影像处理的速度和直线提取的精度,特别是对比较大的影像具有计算量小、抗噪能力强等特点。

Aiming at the critical time-consuming and accuracy issues of straight line extraction from large-size remote sensed imagery, after briefly reviewing the existing straight line extraction methods, a multi-scale Hough transform method based on the pre-storage weight matrix is proposed, which saves a lot of storage space, takes care of discretization errors, and avoids the abruption and conglutination of characters that are the drawbacks of the existing straight line extraction algorithms. The improvement of classical Hough transform method in detail is introduced. To optimize speed and precision, the best choice of accumulator based on image size is suggested too. The experimental results show that this algorithm is more efficient in computation and robust to noise, and is rich in feature content and accurate, especially for large-size images.