强噪声干扰下的对数极坐标空间边缘提取算法

Algorithm of edge extraction in intensively noisy log-polar space

准确提取对数极坐标空间的目标边缘信息是对数极坐标变换视觉不变性获得成功应用的前提和关键。由于传统的边缘提取算法无法满足强噪声干扰下的单像素精度要求,在主动轮廓模型和水平集方法的基础上,设计了一种独特的边缘提取算法。经融合Canny算子的水平集方法全局降噪,利用能量驱动的主动轮廓模型逐次演化逼近,提取可能的边缘曲线,通过改进型跟踪寻迹剔除虚假信息,即可得到最终的目标边缘。实验表明,该算法行之有效,边缘提取特征相似度达96%以上。

Accurate extraction of a target＇ s edge in a log-polar space is a precondition and key point to successfully apply the visual invariance of the log-polar transformation. Since it is impossible for traditional algorithms to extract the single-pixel edge in an intensively noisy environment, a unique edge extraction algorithm on the basis of active contour model and level set method was designed. After noise removal on the whole via Canny operator based level set method, the energy-driving active contour model was used to iteratively approach the potential edges. By clearing out false edges with an improved tracing way, the true target＇ s edge was extracted finally. The experimental results demonstrate the effective performance of the proposed algorithm with the edge feature similarity up to 96%.