Analysis and modeling of radiometric error caused by imaging blur in optical remote sensing systems

Imaging blur changes the digital output values of imaging systems. It leads to radiometric errors when the system is used for measurement. In this paper, we focus on the radiometric error due to imaging blur in remote sensing imaging systems. First, in accordance with the radiometric response calibration of imaging systems, we provide a theoretical analysis on the evaluation standard of radiometric errors caused by imaging blur. Then, we build a radiometric error model for imaging blur based on the natural stochastic fractal characteristics of remote sensing images. Finally, we verify the model by simulations and physical defocus experiments. The simulation results show that the modeling estimation result approaches to the simulation computation. The maximum difference of relative MSE (Mean Squared Error) between simulation computation and modeling estimation can achieve 1.6%. The physical experimental results show that the maximum difference of relative MSE between experimental results and modeling estimation is only 1.29% under experimental conditions. Simulations and experiments demonstrate that the proposed model is correct, which can be used to estimate the radiometric error caused by imaging blur in remote sensing images. This research is of great importance for radiometric measurement system evaluation and application.     

Software lens compensation applied to athermalization of infrared imaging systems

A different approach, aiming to achieve the constant blur status of point-spread function (PSF) at a certain defocused plane, is described. The correlation between the two PSF is used to control the PSF blur similarity, and simultaneously the Strehl ratio is also used to control the PSF blur minimization. By designing the PSF so that it is significantly insensitive to defocus or related defocus quantity, for example, due to temperature change, all the constantly blurred images can be accurately de-blurred by a simple inverse restoration filter for an adequate range of defocus. We refer to that as “software lens compensation” and apply a design method to solve the athermalization of middle wavelength infrared (MWIR) imaging systems. The resultant PSF is almost invariant in the temperature range from −10 to 50°C at the same focal plane. Consequently, the constant blur spot can be removed by a simple digital signal processing. Thus, clear and sharp de-blurred images at different temperatures are obtained.     

基于频谱分析的匀速运动模糊图像模糊方向识别

点扩展函数的设置是图像复原中的关键问题，对于匀速直线运动模糊图像，运动方向和模糊长度决定了点扩展函数。根据运动模糊图像和原始图像在频谱上存在的对应关系，即运动模糊图像频谱存在着对应于传递函数零点的暗条纹，提出对运动模糊图像，通过二维傅里叶变换、二值化以及Radon变换检测运动模糊图像频谱图上暗条纹的方向和位置，来实现运动方向测量的方法。用该方法对模糊图像进行检测，模糊方向的识别精度小于1°。实验证明该方法可以实现平面内任意方向运动的测量。     

二步法大景深反射全息图

以开拓反射全息图的景深表达能力为目的,从反射全息图的共轭物像关系出发,利用反射全息图的均匀介质耦合波理论和布拉格条件,对其白光再现像模糊作了具体的分析和讨论,得到色模糊和线模糊的表达式.指出反射全息图上不同各点对任意白光再现像点的色模糊和线迷糊的影响均存在差异,给出反射全息图白光再现像的景深表达式.实验利用二步法制作了一张景深为83 cm的反射全息图,与大景深彩虹全息图再现像相比,其再现像的立体感更加强烈.理论分析和实验结果表明,光源的再现角度和观察距离对反射全息图的再现像景深大小影响显著.在再现光垂直于反射全息图平面照明情况下,反射全息图具有最好的景深表达能力.     

Limits on rough-particle sizing with low-defocus interferometric imaging

We present a rigorous theoretical model for the influence of the aperture in interferometric out-of-focus imaging. We investigate the role of this effect on the properties of speckle-like patterns generated by irregular, rough particles. Finally, we determine the conditions under which these patterns are no longer representative of particle size but of the aperture itself and the defocus parameter.     

含散射闪光照相系统的布局优化

为了提高现有照相系统的图像品质,对使用CCD探测器的法国客体(FTO)照相布局进行了优化,获得最佳图像品质因子下的照相布局。研究结果为:在模糊实验测量结果和高斯分布近似下,系统放大倍率为2.0;后保护器件距离客体50 cm;系统布局总长与探测系统的噪声相关,噪声越大,布局总长越短,最优布局总长的范围为3~5 m;实验验证了这一结果。     

用神经网络鉴别退化图像的模糊类型

提出了一种用神经网络鉴别退化图像的模糊类型的方法。由于采用不同降质方法得到退化图像的频谱差异较大,以此作为判别依据,用概率神经网络实现了对四种模糊类型:离焦,矩形,运动和高斯模糊的鉴别。根据神经网络的鉴别结果决定点扩散函数的初始估计值,可大大地提高盲解恢复算法的复原质量和系统点扩散函数的估计精度,扩大了算法的实用范围。     

基于空间域共轭梯度法的盲目图像复原

针对图像退化的几种常见形式,在最小二乘法的基础上提出了一种基于共轭梯度法的空间域加权盲目图像复原方法。通过实验验证,该算法经过较少的迭代次数就可以实现运动模糊、离焦模糊图像的复原,并取得了较为满意的复原结果。     

Motion blur parameters estimation for image restoration

This paper deals with estimation of parameters for motion blurred images. The objectives are to estimate the length (L) and the blur angle (θ) of the given degraded image as accurately as possible so that the restoration performance can be optimised. Gabor filter is utilized to estimate the blur angle whereas a trained radial basis function neural network (RBFNN) estimates the blur length. Once these parameters are estimated the conventional restoration is performed. To validate the proposed scheme, simulation has been carried out on standard images as well as in real images subjected to different blur angles and lengths. The robustness of the scheme is also validated in noise situations of different strengths. In all situations, the results have been compared with standard schemes. It is in general observed that the proposed scheme outperforms its counterparts in terms of restoration parameters and visual quality.     

基于模糊度量的激光水下图像复原的盲去卷积方法

由于水体对激光存在着不可克服的吸收和散射效应,距离选通水下激光成像系统所获得的图像存在不同程度的劣化问题,具有信噪比低、边缘模糊等特点.为提高图像质量,将基于模糊度量的盲去卷积方法应用于激光水下成像的图像复原中.结合威尔斯小角度近似得出的点扩展函数与调制传递函数,分别讨论了最大期望,最小均方与多次乘法迭代盲去卷积算法,...