基于标准差梯度的模糊边缘检测算法

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。

Fuzzy edge detection based on standard deviation gradient

Infrared image edge detection is one of the difficult problems in image processing.Based on the characteristics of infrared image,the minimum error thresholding algorithm is extended to the fuzzy domain and applied to the infrared image edge detection.The fuzzy edge detection algorithm for infrared image based on standard deviation is proposed.Firstly,a gradient operator based on local standard deviation is performed and potential edge regions are well separated.Secondly,a fuzzy minimum error thresholding algorithm is introduced to find a fuzzy thresholding of the gradient image,which partitions the gradient image into edge region and non-edge region.The experiment is conducted on various infrared images and the results show that the proposed approach has better performance than some classical edge detection methods based on gradient.