A fast algorithm based on the grayscale distribution of infrared target and the weighted kernel function was proposed for the moving target detection(MTD) in dynamic scene of image series. This algorithm is used to de...A fast algorithm based on the grayscale distribution of infrared target and the weighted kernel function was proposed for the moving target detection(MTD) in dynamic scene of image series. This algorithm is used to deal with issues like the large computational complexity, the fluctuation of grayscale, and the noise in infrared images. Four characteristic points were selected by analyzing the grayscale distribution in infrared image, of which the series was quickly matched with an affine transformation model. The image was then divided into 32×32 squares and the gray-weighted kernel(GWK) for each square was calculated. At last, the MTD was carried out according to the variation of the four GWKs. The results indicate that the MTD can be achieved in real time using the algorithm with the fluctuations of grayscale and noise can be effectively suppressed. The detection probability is greater than 90% with the false alarm rate lower than 5% when the calculation time is less than 40 ms.展开更多
An algorithm of ramp width reduction based on the gray information of neighborhood pixels is proposed, which can sharpen the ramp edge effectively. Then, a new gray-weighted gradient operator and the automatic method ...An algorithm of ramp width reduction based on the gray information of neighborhood pixels is proposed, which can sharpen the ramp edge effectively. Then, a new gray-weighted gradient operator and the automatic method to determine its parameter are introduced when detecting the transition region of images. Gray-weighted gradient operator can not only make the correlation of gradient and gray information as big as possible, but also resist the noise in the images. Some experiments show that the algorithm in this paper can extract the transition region more effectively.展开更多
基金Project(61101185)supported by the National Natural Science Foundation of China
文摘A fast algorithm based on the grayscale distribution of infrared target and the weighted kernel function was proposed for the moving target detection(MTD) in dynamic scene of image series. This algorithm is used to deal with issues like the large computational complexity, the fluctuation of grayscale, and the noise in infrared images. Four characteristic points were selected by analyzing the grayscale distribution in infrared image, of which the series was quickly matched with an affine transformation model. The image was then divided into 32×32 squares and the gray-weighted kernel(GWK) for each square was calculated. At last, the MTD was carried out according to the variation of the four GWKs. The results indicate that the MTD can be achieved in real time using the algorithm with the fluctuations of grayscale and noise can be effectively suppressed. The detection probability is greater than 90% with the false alarm rate lower than 5% when the calculation time is less than 40 ms.
基金Supported by the National Natural Foundation of Guangdong(No.011750)
文摘An algorithm of ramp width reduction based on the gray information of neighborhood pixels is proposed, which can sharpen the ramp edge effectively. Then, a new gray-weighted gradient operator and the automatic method to determine its parameter are introduced when detecting the transition region of images. Gray-weighted gradient operator can not only make the correlation of gradient and gray information as big as possible, but also resist the noise in the images. Some experiments show that the algorithm in this paper can extract the transition region more effectively.
