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Ship infrared image edge detection based on an improved adaptive Canny algorithm:

机译:基于改进的自适应Canny算法的舰船红外图像边缘检测:

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Influenced by light reflection and water fog interference, ship infrared images are mostly blurred and have low signal-to-noise ratio. In this paper, an improved adaptive Canny edge detection algorithm for infrared image of ship is proposed, which aims to solve the threshold of the traditional Canny cannot be adjusted automatically and the shortcomings of sensitivity to noise. The contrast limited adaptive histogram equalization algorithm is adopted to enhance the infrared image, the morphological filter replaces the Gauss filter to smooth the image, and the OTSU algorithm is utilized to adjust the high and low thresholds dynamically. The experimental results show that the improved Canny algorithm, which can not only improve the contrast of the image and automatically adjust the threshold but also reduce the background sea clutter and false edges, is an effective edge detection method.
机译:受光反射和水雾干扰的影响,船上的红外图像大多模糊并且信噪比低。提出了一种改进的舰船红外图像自适应Canny边缘检测算法,以解决传统的Canny阈值不能自动调整以及对噪声敏感的缺点。采用对比度受限的自适应直方图均衡算法对红外图像进行增强,用形态学滤波器代替高斯滤波器对图像进行平滑处理,利用OTSU算法动态调整高低阈值。实验结果表明,改进的Canny算法不仅可以提高图像的对比度,可以自动调整阈值,而且可以减少背景杂波和虚假边缘,是一种有效的边缘检测方法。

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