摘要
对于星空观测CCD图像,除星空背景成像为大面积起伏背景噪声外,其余均为近似点状小目标。分析深空背景的统计特性,并建立起精确的数学模型来描述图像中的起伏背景,这对背景滤除以及空间弱小目标检测、识别至关重要。结合实际观测图像分析星空图像的性质,提出一种基于局部直方图Gauss拟合的星图背景参数估计算法;然后,将背景参数的估计结果应用于星图弱小目标增强,提出了基于最优Gamma变换的弱小目标增强算法。实验结果证明,算法能够克服恒星的干扰,对星空背景图像的统计特性进行精确的估计,对空间弱小目标成像进行增强,为空间目标检测奠定了基础。
There are all dot-like space targets or fixed stars in the CCD star-sky observation image except the wide undulant clutter background.The investigation of statistical property of deep-space background image is carried out and a precious model to represent the background image is established,which is very important for the target detection and identification.Combining with the characteristics of star-sky image,an algorithm based on the part-histogram Gaussian fitting is proposed to estimate the background statistical parameters.Then,the estimated parameters are used in the field of space target enhancement and a space target enhancement algorithm based on the optimum Gamma transform is put forward.Experiments convince that the algorithm can get over influences of fixed stars,estimate background statistical parameters with high accuracy,and enhance the dim space targets in the starsky image.The paper provides a basis for the dim space targets' detection.
出处
《遥测遥控》
2013年第4期22-27,38,共7页
Journal of Telemetry,Tracking and Command
关键词
直方图
高斯拟合
星图
KL散度
图像增强
Histogram image
Gaussian fitting
Star-sky image
Kullback-Leibler divergence
Image enhancement
