Edge detection investigation of low-SNR infrared image based on noise probability

Characteristics of IR images mostly include large noise, small distinction betweens target and background, blurry edge and so on. These characteristics make existent methods ineffective and require more effective method. Considering the random noise often accords with Gauss distribution, a statistic method based on noise probability distribution and noise characteristics has been put forward to detect image edge. By analyzing the probability model of noise,it is proved that if the difference of neighboring dots is larger than a determinate value, the edge of infrared image can be detected in large probability. By comparing the infection of noise for statistic method and gradient method in different conditions, it is found that the noise restrain capacity of statistic method is higher than that of gradient method. Comparison and analysis are made between the statistic method and the often used Sobel algorithms. The analyses indicate that good results can be obtained when this statistic method is used to detect edge of infrared image and this method is simple and fast.