摘要
在航空摄影、景象匹配导航等领域,由光学相机采集的图像往往同时存在着运动模糊和散焦模糊。成像中的噪声进一步加大了混合模糊图像点扩展函数的参数辨识难度。提出了一种双谱混合模糊含噪图像的点扩展函数参数辨识方法。首先计算出经混合模糊后的标准测试图像所对应的运动和散焦模糊的双谱,然后通过曲线拟合出双谱中各自的统计特性与运动模糊尺度或散焦半径之间的函数关系,由此训练出的BP神经网络可以完成对其它含有噪声的混合模糊图像点扩展函数的参数辨识。实验结果表明,该方法适用于含有噪声的一定模糊参数范围内的混合模糊图像。在信噪比为25dB的情况下,辨别出的模糊参数偏差不超过0.5个像素。
There are motion blur and defocus blur in the images captured by optics cameras in rome areas, for example, in the areas of aeroplane photography and navigation using scene matching. Noise makes parameter identification of point spread function more difficult in mixed blur images. A robust bispectrum-based method to estimate the blur parameter in noisy and mixed blur images is proposed. At first, two bispectrums are calculated according to motion blur and defocus blur of a standard test image. Then the curve fitting is used to get the function relations between statistics characteristic in two bispectrums and degraded parameters. Finally, the BP neural network, which is trained by the aforementioned function relations, can accomplish the identification of blur parameter in other noisy and mixed blur images. The experimental results show that the method is effective in certain ranges. When SNR is 25dB, the tolerance of blur parameters recognized is less than 0.5 pixel.
出处
《光学技术》
CAS
CSCD
北大核心
2009年第6期910-914,918,共6页
Optical Technique
基金
总装预研基金资助项目(9140A01040307HT0125)
