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点扩散函数(Point Spread Function,PSF)能够完整表征物空间一点发出的光经过相机系统在像空间的分布特性,是空域图像复原、图像超分等处理的关键先验信息。针对基于点源的星载面阵CMOS相机静态点扩散函数PSF测量受点源相位影响、采样点少的问题,分析了相位模型,建立了相位理论模型模板库,提出了基于相似性度量函数模板匹配的相位确定方法,首次形成一套点源阵列靶标设计及数据处理方法,并对该PSF测量方法进行蒙特卡洛仿真,结果表明文章提出的方法对信噪比变化不敏感,具有较强稳定性,以二维高斯分布标准差衡量,测量精度达到95%。将该方法用于“高分四号”卫星全色CMOS相机的静态PSF测试,证明了该方法在星载面阵CMOS相机静态PSF测试工程应用中的可行性。
The Point Spread Function (PSF) can completely characterize the distribution of light emitted by a single point in the image space through the camera system. It is the key prior information for spatial image restoration and image super-resolution processing. Aiming at the point source-based static point spread function (PSF) measurement of the satellite point space array CMOS camera is affected by the phase of the point source and the sampling points are few, the phase model is analyzed and the phase theory model template library is established. Based on the similarity measure function template Matching phase determination method, a set of point source array target design and data processing method are firstly formed, and the Monte Carlo simulation of the PSF measurement method is performed. The results show that the proposed method is insensitive to the change of signal-to-noise ratio and has a strong and stable Sex, measured by standard deviation of two-dimensional Gaussian distribution, measurement accuracy of 95%. The method is applied to the static PSF test of the high score four satellite panchromatic CMOS camera, which proves the feasibility of this method in the static PSF test project of the spaceborne array CMOS camera.