低信噪比红外图像直线段检测算法

因梯度场计算受噪声影响严重，直线段检测是低信噪比红外图像处理的一个难点。文中利用直线区域的相位分布具有显著非各向同性的基本事实，通过度量图像点邻域内的非各向同性度来区分直线点和非直线点。定义了图像的局部非各向同性度并给出了计算子，结合相位编组和背景反例模型，提出了一种能有效抑制噪声影响的新的直线段提取算法。实验表明，该算法能有效检测出低信噪比图像中的直线段，并具有很低的虚警率。

Line segment detection in low-SNR infrared image

Line segment detection in low-SNR infrared image is difficult as the gradient field calculation is badly affected by noise. In this paper, a new approach was presented to distinguish line elements and non-line ones in an image according to the fact that gradient field phase distribution of a line area distinctly appears non-isotropic. Local non-isotropy was defined and a calculating operator was presented. By combing phase-grouping algorithm and contrario detection framework, a new line segments detection algorithm was proposed. Experimental results indicate that the algorithm can effectively detect line segments in low-SNR images with a low false alarm rate.