基于压缩标定与采样的中波红外超分辨率成像
Mid-wave infrared super-resolution imaging based on compressive calibration and sampling
AI总结：
针对高像素中波红外相机成本高昂的问题，本文利用压缩感知改进焦平面阵列压缩成像的标定矩阵测量与计算，提升对比度和信噪比，并实验实现达到系统设计极限的4×4长距离超分辨率重建。
摘要：
与可见光相机相比，具有大量像素的中波红外（MWIR）相机极其昂贵，因此，近年来通过增加成像像素来实现MWIR超分辨率成像（SRI）一直是研究热点。在过去十年中，随着压缩感知（CS）方法的广泛研究，基于焦平面阵列（FPA）的MWIR压缩成像在SRI方面发展迅速。本文提出了一种长距离超分辨率FPA MWIR压缩成像方法，改进了标定方法和成像效果。利用CS，我们高效且精确地测量并计算了光学系统的标定矩阵；与先前工作相比，该方法提高了成像对比度和信噪比（SNR）。我们还在实验中实现了长距离目标的4×4倍超分辨率重建，达到了系统设计的极限。
英文摘要：
Mid-wave infrared (MWIR) cameras for large number pixels are extremely expensive compared with their counterparts in visible light, thus, super-resolution imaging (SRI) for MWIR by increasing imaging pixels has always been a research hotspot in recent years. Over the last decade, with the extensively investigation of the compressed sensing (CS) method, focal plane array (FPA) based compressive imaging in MWIR developed rapidly for SRI. This paper presents a long-distance super-resolution FPA compressive imaging in MWIR with improved calibration method and imaging effect. By the use of CS, we measure and calculate the calibration matrix of optical system efficiently and precisely, which improves the imaging contrast and signal-to-noise ratio(SNR) compared with previous work. We also achieved the 4x4 times super-resolution reconstruction of the long-distance objects which reaches the limit of the system design in our experiment.
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