We present a pseudo-inverse ghost imaging(PGI) technique which can dramatically enhance the spatial transverse resolution of pseudo-thermal ghost imaging(GI). In comparison with conventional GI, PGI can break the limi...We present a pseudo-inverse ghost imaging(PGI) technique which can dramatically enhance the spatial transverse resolution of pseudo-thermal ghost imaging(GI). In comparison with conventional GI, PGI can break the limitation on the imaging resolution imposed by the speckle’s transverse size on the object plane and also enables the reconstruction of an N-pixel image from much less than N measurements. This feature also allows high-resolution imaging of gray-scale objects. Experimental and numerical data assessing the performance of the technique are presented.展开更多
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 use...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 the 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.展开更多
基金supported by the Hi-Tech Research and Development Program of China under Grant Project No. 2013AA122901the Youth Innovation Promotion Association CAS
文摘We present a pseudo-inverse ghost imaging(PGI) technique which can dramatically enhance the spatial transverse resolution of pseudo-thermal ghost imaging(GI). In comparison with conventional GI, PGI can break the limitation on the imaging resolution imposed by the speckle’s transverse size on the object plane and also enables the reconstruction of an N-pixel image from much less than N measurements. This feature also allows high-resolution imaging of gray-scale objects. Experimental and numerical data assessing the performance of the technique are presented.
基金This work was supported by the Pre-Research Foundation of National Defense under Grant No. 30404.
文摘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 the 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.
