基于改进方向中值滤波的早期视觉模型边缘检测

R. Lu, Yi Shen, Qiang Wang
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引用次数: 5

摘要

边缘检测是超声图像分析的基本步骤。然而,由于超声图像固有的噪声特性,这仍然是一个难题。本文提出了一种将改进的方向中值滤波和早期视觉模型相结合的边缘检测算法。提出了一种改进的方向中值滤波方法,以减少中值滤波引起的模糊和抑制方向中值滤波引起的噪声的影响。早期视觉模型在许多文献中被证明是非常有效的边缘检测,即使在非常嘈杂的图像中也是如此。该方法将早期视觉模型的抗噪特性和纹理敏感特性有效地结合在一起,实验结果表明,该方法具有良好的应用前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Edge detection based on early vision model incorporating improved directional median filtering
Edge detection is a fundamental step for ultrasound image analysis. However, it remains to be a difficult problem due to the intrinsic noisy nature of ultrasound images. In this paper, an edge detecting algorithm is proposed, which combines an improved directional median filter and early vision model together. And this improved directional medial filtering method is put forward to reduce the blurring caused by the median filter and to depress the influence of noise caused by the directional median filter. The early vision model has been proved in many literatures to be highly effective for edge detecting, even in a very noisy image. In our way, the simpleness and the speediness of the median filter band the antinoise and texture-sensitive characters of the early vision model together efficiently and the experimental results show that out approach is promising.
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