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基于方向WPS改进TDI CCD遥感图像清晰度评价函数
引用本文:陶淑苹,张续严,金光,曲宏松,郑亮亮.基于方向WPS改进TDI CCD遥感图像清晰度评价函数[J].红外与激光工程,2013,42(8):2080-2084.
作者姓名:陶淑苹  张续严  金光  曲宏松  郑亮亮
作者单位:1.中国科学院长春光学精密机械与物理研究所,吉林 长春 130033;
基金项目:国家863计划(O93J32F090);国家自然科学基金青年基金
摘    要:在轨调焦是航天相机获取高质量图像的关键技术之一。针对航天相机在发射、在轨期间由于振动冲击及温度气压等环境参数变化引起的光学系统离焦现象,以及TDI CCD遥感相机成像场景实时变化的特殊特点,对基于功率谱的清晰度评价函数进行了研究。根据小波变换的多分辨率和带通特性,提出了一种对FFT功率谱的改进小波功率谱(WPS)估计。针对像移亦会导致TDI CCD图像模糊的问题,提出了方向WPS估计算法。参照功率谱地物无关性及离焦会引起功率谱高频分量损失的思路,设计了基于方向WPS的加权清晰度评价函数。实际外场推扫实验结果表明,提出的新清晰度评价函数能有效反映出实际推扫图像的离焦状态,另外相对于FFT功率谱,对场景差异更不敏感,误判率从0.36降低为0,曲线更加饱和。100个仿真样本的平均误判率仅为0.06,满足系统误差要求。因此文中算法满足单调性、灵敏度高、准确度高原则,更适合TDI CCD遥感相机的自动调焦。

关 键 词:自动调焦    小波    功率谱估计    图像清晰度评价函数
收稿时间:2012-12-11

Improvement of the definition evaluation function for TDI CCD remote sensing images by directional wavelet power spectrum
Tao Shuping , Zhang Xuyan , Jin Guang , Qu Hongsong , Zheng Liangliang.Improvement of the definition evaluation function for TDI CCD remote sensing images by directional wavelet power spectrum[J].Infrared and Laser Engineering,2013,42(8):2080-2084.
Authors:Tao Shuping  Zhang Xuyan  Jin Guang  Qu Hongsong  Zheng Liangliang
Affiliation:1.Changchun Institute of Optics,Fine Mechanics and Physics,Chinese Academy of Sciences,Changchun 130033,China;2.University of Chinese Academy of Sciences,Beijing 100049,China
Abstract:Autofocusing is one of the key techniques for space cameras to ensure a high quality image. The optical system of the camera defocuses in all probability due to many influential factors, such as the impulsion or jitter during launching, changes of temperature and air pressure. So, in order to retrieve the defocus, focus measure algorithm based on power spectrum was studied, where the algorithm was used in TDI CCD space cameras which imaging scenes changed anytime. Firstly, an improvement over Fourier transform power spectrum was proposed, namely wavelet power spectrum(WPS) estimation, which took advantage of the multi-resolution and band-passing characters of wavelet transform. Then, directional WPS was proposed in order to reduce the influence of image-moving-mismatching. Lastly, according to the theory that power spectrum is independent of scenes and defocus made the power spectrum's high frequency losing, the evaluation function for image definition was designed, using the weighted sum of directional WPS. The experimental results of the real pushblooming images show that the new definition evaluation method can reflect the real remote images' defocusing state validly. Moreover, the directional WPS is less sensitive to the scenes' variety compared to FFT PSS, which reduces the error ratio from 0.36 to 0, and the curve gets more saturated. In addition, the error ratio of all the 100 emulational samples is only 0.06. So the proposed algorithm meets the principles of monotony, excellent sensitivity and precision, and suits for the autofocus in TDI CCD remote sensing cameras better.
Keywords:autofocus  wavelet  power spectrum estimation  evaluation function for image definition
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