Scattered light imaging through complex turbid media has significant applications in biomedical and optical research. For the past decade, various approaches have been proposed for rapidly reconstructing full-color, depth-extended images by introducing point spread functions (PSFs). However, because most of these methods consider memory effects (MEs), the PSFs have angular shift invariance over certain ranges of angles. This assumption is valid for only thin turbid media and hinders broader applications of these technologies in thick media. Furthermore, the time-variant characteristics of scattering media determine that the PSF acquisition and image reconstruction times must be less than the speckle decorrelation time, which is usually difficult to achieve. We demonstrate that image reconstruction methods can be applied to time-variant thick turbid media. Using the time-variant characteristics, the PSFs in dynamic turbid media within certain time intervals are recorded, and ergodic scattering regimes are achieved and combined as ensemble point spread functions (ePSFs). The ePSF traverses shift-invariant regions in the turbid media and retrieves objects beyond the ME. Furthermore, our theory and experimental results verify that our approach is applicable to thick turbid media with thickness of 1 cm at visible incident wavelengths.
Vehicle recognition is a key issue of intelligent transportation systems. For traditional color-based vehicle recognition methods, an important problem is that color information of vehicle is susceptible on lumination variation, which will inevitably reduce the recognition accuracy. Another is that there are contrastive interfering vehicles with similar color in same exposure environment, which could result in misrecognition of target vehicle. This paper presents a novel technique for recognizing target vehicle in different lumination scenarios via spectral feature. This method consists of three parts, ambient light spectrum calibration, vehicle spectral reflectivity detection and vehicle recognition. And an prototype system named Selectable Imaging Spectrum Detection System (SISDS), has been setup by this spectral feature-based method. A new combination algorithm is proposed for the detection part which contains the deep learning model YOLOv3 and the discriminant tracking algorithm KCF. Also, a CNN model is designed for improving the recognition accuracy through transforming the spectral data into two-dimension matrix. The experimental results of the SISDS clearly demonstrate that the spectral feature-based method overcomes the shortcomings of the traditional color-based method, and it can not only distinguish the vehicles of different colors in the case of overexposure, but also can recognize the target vehicle from the same color interference vehicles under various lumination, the recognition accuracy is up to 96.4%. Compared with color based method, the spectral feature-based method has great lamination robustness, and high recognition accuracy.
In this paper, we propose a staggered design directional backlight system in an autostereoscopic display. Currently, one of the main deficiency of autostereoscopic display is low display uniformity in both horizon and depth direction. In order to optimized display unifomity, the system mainly employs a staggered backlight array designed by a trace-back algorithm and a light shaping diffuser. As result, the horizontal dark areas are fully compensated. Moreover, crosstalk of experimental system is as low as 0.9%.
In this article, we propose a quantitative evaluation for the display uniformity in a directional backlight system. Display uniformity is divided into two research aspects - static uniformity and motional uniformity. Factors influencing uniformity deterioration are then discussed in our evaluation. Furthermore, a visualized simulation based on ray-tracing model is proposed to analyze this display uniformity in quantitative depth. Optical distribution on the screen is obtained in this simulation to provide visualized results compared with the experimental results. Our work helps to fill the vacancy for the evaluation of display uniformity on directional backlight type 3D display.
Recent upsurge on virtual and augmented realities (VR and AR) has re-ignited the interest to the immerse display technology. The VR/AR technology based on stereoscopic display is believed in its early stage as glasses-free, or autostereoscopic display, will be ultimately adopted for the viewing convenience, visual comfort and for the multi-viewer purposes. On the other hand, autostereoscopic display has not yet received positive market response for the past years neither with stereoscopic displays using shutter or polarized glasses. We shall present the analysis on the real-world applications, rigid user demand, the drawbacks to the existing barrier- and lenticular lens-based LCD autostereoscopy. We shall emphasize the emerging autostereoscopic display, and notably on directional backlight LCD technology using a hybrid spatial- and temporal-control scenario. We report the numerical simulation of a display system using Monte-Carlo ray-tracing method with the human retina as the real image receiver. The system performance is optimized using newly developed figure of merit for system design. The reduced crosstalk in an autostereoscopic system, the enhanced display quality, including the high resolution received by the retina, the display homogeneity without Moiré- and defect-pattern, will be highlighted. Recent research progress including a novel scheme for diffraction-free backlight illumination, the expanded viewing zone for autostereoscopic display, and the novel Fresnel lens array to achieve a near perfect display in 2D/3D mode will be introduced. The experimental demonstration will be presented to the autostereoscopic display with the highest resolution, low crosstalk, Moiré- and defect- pattern free.
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