“实践九号”A卫星光学遥感图像杂散光噪声去除

杂散光是影响卫星光学遥感图像像质的重要因素，严重时会在图像上形成明暗的杂散光条纹噪声，降低图像的对比度和清晰度。文章针对“实践九号”A（SJ-9A）卫星光学遥感图像存在的杂散光噪声现象，设计了一种基于成像载荷焦面入射杂散光空间分布特征的遥感图像杂散光条纹噪声去除方法，通过测量杂散光在推扫遥感图像上的空间分布特征，建立杂散光分布特征模型，采用分块自适应算法进行杂散光噪声滤波，消除SJ-9A遥感图像上随时空变化的杂散光条纹噪声。杂散光噪声去除后图像整体色调均匀，无条带噪声，满足CCD/TDI-CCD推扫遥感图像辐射校正精度（广义噪声）优于5%的指标要求。

Removal of SJ-9A Optical Imagery Stray Light Stripe Noise

If the stray light is not isolated and absorbed completely by optical imaging system, the resolution and contrast of CCD/TDI-CCD push-broom remote sensing imagery will be degraded, and the stray light stripe noise appeare obviously in relatively radiometric corrected imagery. The paper aims at removal of Shijian-9A （SJ-9A） optical remote sensing imagery stray light stripe noise, and devise a stray light stripe noise correction algorithm on the basis of stray light spatial distribution character on CCD/TDI-CCD focal plane. By measuring spacial distribution characteristics of the stray light noise in the push-broom image, a model of distribution characteristics of stray light noise is set up and sub-image adaptive algolithms are used to filter stray light noise, so as to remove the SJ-9A remote sensing stray light stripe noise which changes with time and space. The stray light noise removed images are of uniform colour and no stripe noise on the whole.The generalized noise value of stray light stripe noise removed image is below 5%, which is satisfied with the need of remote sensing imagery radiometric correction precision. The method has been used in SJ-9A panchromatic and multi-spectral imagery stray light stripe noise filtering process.