强噪声条件下数字图像模糊边缘检测算法

Digital Image Fuzzy Edge Detection Algorithm under Strong Noise

强噪声会造成图像细节不清晰,不利于获取高精度的图像边缘检测结果,为了有效解决上述问题,提出一种强噪声条件下数字图像模糊边缘检测算法。在强噪声条件下,采用分解算法预先处理数字图像,通过低通滤波器消除部分高频梯度信息,在滤除数字图像噪声的同时更好地保留边缘细节信息。将数字图像灰度信息模糊化,通过模糊偏移度最小准则确定模糊对比度操作系数,获取最优S型灰度映射函数,增强数字图像对比度,引入多方向模糊形态学检测数字图像模糊边缘。实验结果表明,所提算法可以有效检测数字图像模糊边缘,同时还可以有效提升检测效率。

Strong noise may cause unclear image details,which is not conducive to obtaining high-precision edge detection results.Therefore,an algorithm for detecting digital image fuzzy edges under strong noise conditions was proposed.Under the condition of strong noise,the decomposition algorithm was used to preprocess the digital image at first,and then a low-pass filter was used to eliminate partial high-frequency gradient information,so as to better retain the edge details while filtering the digital image noise.Moreover,the gray information of the digital image was blurred.After that,the fuzzy contrast operation coefficient was determined by the minimum fuzzy offset criterion.Meanwhile,the optimal S-gray mapping function was obtained.Furthermore,the contrast of digital images was enhanced.Finally,the multi-directional fuzzy morphology was introduced to detect the fuzzy edges of digital images.Experimental results show that the proposed algorithm can effectively detect the fuzzy edges of digital images and improve the detection efficiency.