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红外图像的边缘检测是图像处理领域的难题之一。结合红外图像的特点,将最小误差原理推广到模糊域进而应用到红外图像的边缘检测上,提出了一种基于标准差梯度的红外图像模糊边缘检测算法。首先提出了一种基于标准差的梯度算子,将图像中潜在的边缘区域很好地区分出来;而后引入模糊最小误差阈值算法,根据此算法自适应提取了标准差梯度图像中的最优阈值,从而实现了红外图像的目标边缘检测。与传统的基于梯度的红外图像边缘检测算法进行对比实验,结果表明,该算法用于红外图像边缘检测能获得更好的效果。
Edge detection of infrared images is one of the difficult problems in image processing. Combining the characteristics of infrared images, the principle of minimum error was extended to fuzzy domain and then applied to the edge detection of infrared images. An infrared image fuzzy edge detection algorithm based on standard deviation gradient was proposed. First of all, a gradient operator based on standard deviation is proposed to distinguish the potential edge regions in the image well. Then, a fuzzy minimum error threshold algorithm is introduced. Based on this algorithm, the optimal threshold in the standard deviation gradient image is adaptively extracted , So as to achieve the target edge detection of infrared images. Compared with the traditional gradient-based infrared image edge detection algorithm, the experimental results show that the proposed algorithm can be used to obtain better results in the infrared image edge detection.