利用光学微扫描和亚像元成像处理技术,实现亚像元成像系统是当前提高光电成像系统空间分辨率的重要技术途径. 本文在分析二维凝视焦平面探测器的亚像元成像和重构原理的基础上,提出了一种改进的基于二维2×2 微扫描的亚像元成像处理方法,解决了边界精确标定法的标定以及边界值近似法的误差问题. 模拟分析表明:算法可有效实现亚像元成像,且处理工作量小,易于实现实时处理,可望在可见光和红外亚像元成像领域获得应用,算法对于发展高性能热成像系统具有重要的理论指导意义和实用价值.

The improved scene-based adaptive nonuniformity correction (NUC) algorithms using a neural network (NNT) approach for infrared image sequences are presented and analyzed. The retina-like neural networks using steepest descent model was the first proposed infrared focal plane arrays (IRFPA) nonuniformity compensation method, which can perform parameter estimation of the sensors over time on a frame by frame basis. To increase the strength and the robustness of the NNT algorithm and to avoid the presence of ghosting artifacts, some optimization techniques, including momentum term, regularization factor and adaptive learning rate, were executed in the parameter learning process. In this paper , the local median filtering result of Xij (n) is proposed as an alternative value of desired network output of neuron Xij (n) , denoted as Tij (n) , which is the local spatial average of Xij (n) in traditional NNT methods. Noticeably, the NUC algorithm is inter-frame adaptive in nature and does not rely on any statistical assumptions on the scene data in the image sequence. Applications of this algorithm to the simulated video sequences and real infrared data taken with PV320 show that the correction results of image sequence are better than that of using original NNT approach , especially for the short-time image sequences (several hundred frames) subjected to the dense impulse noises with a number of dead or saturated pixels.

The striping pattern nonuniformity of the infrared line scanner (IRLS) severely limits the system performance. An adaptive nonuniformity correction (NUC) algorithm for IRLS using neural network is proposed. It uses a one-dimensional median filter to generate ideal output of network and can complete NUC by a single frame with a high correction level. Applications to both simulated and real infrared images show that algorithm can obtain a satisfactory result with low complexity, no need of scene diversity or global motion between consecutive frames. It has the potential to realize real-time hardware-based applications.

根据人眼视觉实验,对光电成像系统的性能评价方法进行了理论研究,证明了光电成像系统与人眼之间存在最佳匹配状态,分析了视场角、成像系统性能以及系统角放大率对匹配的影响,定量描述电视型成像系统的最佳观察距离和直视型最佳目镜焦距的客观现象,所得结果与实际基本一致。