摘要
为了实现星敏感器高斯灰度扩散模型的参数估计,设计了平行光管成像标定实验及相关算法。基于高斯规律建立并求解了以高斯扩散半径和像点质心坐标偏差为变量的方程组,进一步求得灰度能量系数;在3个不同平行光源方位拍摄图像,利用图像灰度数据计算模型参数的系列测量值,分别取均值作为其估计值;建立实验验证方法,将3个估计参数代入模型模拟静态星像点,将模拟图像与存在噪声的实拍图像做相似度比较,3pixel×3pixel窗口内相似度高于0.97,5pixel×5pixel窗口内高于0.98,7pixel×7pixel窗口内高于0.98。结果表明,方程组求解得到的高斯扩散半径、像点质心偏差的值可信,推导公式正确。
In order to estimate the parameters in Gaussian gray diffusion model, experiments with collimator are carried out while the parameter calibration algorithm is proposed. Equations which take the Gaussian diffusion radius and the deviation values of the centroid coordinate as variables are established and solved, furthermore, the energy- gray coefficient is obtained. Then, series of photos are taken under the same condition in three different orientations, and parameters whose mean values are taken as their estimates are calculated respectively using these gray data of photos. Finally, all the estimated parameters are put into the simulating model, and a model-generated star image spot is therefore got, the similarity between which and real shot ones is calculated in three different windows under the condition that noise is bound to exist. The similarity is a value of more than 0.97 within the window of 3 pixel× 3 pixel, more than 0.98 for a 5 pixel〈 5 pixel, and more than 0.98 for a 7 pixel× 7 pixel. The experimental results show that the solution formulas about δ, A and the deviation △x and △y are. right.
出处
《光学学报》
EI
CAS
CSCD
北大核心
2012年第3期267-272,共6页
Acta Optica Sinica
基金
航空科学基金(2007ZC51027)资助课题
关键词
图像处理
导航技术
参数估计
星图模拟
灰度扩散
image processing
navigation technique
parameter estimation
star-image simulation
gray proliferation
