傅里叶相位差谱在卫星目标图像检测中的应用

提出一种利用序列图像傅里叶相位差谱的特征检测卫星目标的算法. 欲跟踪的卫星目标往往淹没在星海中，仅仅依据星体特征检测出目标很繁琐，也很困难. 从傅里叶变换的相谱差异特性出发，将序列图像相邻2帧图像中的前一帧图像通过相谱补偿后与后一帧图像对比，检测出奇异的卫星目标，再利用帧差法剔除伪目标，给出跟踪目标的运动轨迹. 同时，为了提高该算法的抗噪声能力，针对遇到的实际情况提出基于二维直方图改进的图像二值化算法. 通过实验验证了该算法的可行性，结果表明，所提出算法的检测误差与人工捕获相比不超过1个像素. 

Algorithm of Autonomous Satellite Recognition Base on Fourier Phase Difference

An algorithm is designed to recognize satellites in the sky based on phase difference of a series of images in frequency domain. It is complicated and difficult to recognize the satellites merely through stars’ characteristics because the satellites traced are always surrounded by a large number of stars. One frame image in a series of images is compensated and compared with its adjacent frame. From the comparison, the odd object can be recognized by the character of Fourier phase difference. Then frame subtraction method is used to eliminate fake objects. Finally the movement of tracing object is described. Meanwhile an improved algorithm of image binarization based on two dimension histogram is designed to strength its anti noise ability. At the end the experiment shows that the error between this algorithm recognition and human capture is less than one pixel.