Validation method of infrared imaging simulation based on recognition range北大核心CSCD

随着红外成像技术的发展和应用,红外系统成像仿真及验证技术越来越受到重视。现有仿真模型验证方法没有考虑到人眼视觉的影响,可能导致严重后果,为了解决这一问题,提出了基于识别距离的红外系统成像仿真模型验证方法。以识别距离作为红外系统成像仿真模型的准确度评价因子,考评仿真图像与实测图像在灰度分布、信噪比、分辨率、成像大小、人眼视觉等方面的综合差异。     

Night vision dense crowd counting based on mid-term fusion of thermal imaging features北大核心CSCD

为了提高人群计数模型对尺度和光噪声的鲁棒性,设计了一种多模态图像融合网络。提出了一种针对夜间人群统计模型,并设计了一个子网络Rgb-T-net,网络融合了热成像特征和可见光图像的特征,增强了网络对热成像和夜间人群特征的判断能力。模型采用自适应高斯核对密度图进行回归,在Rgb-T-CC数据集上完成了夜视训练和测试。经验证网络平均绝对误差为18.16,均方误差为32.14,目标检测召回率为97.65%,计数性能和检测表现优于当前最先进的双峰融合方法。实验结果表明,所提出的多模态特征融合网络能够解决夜视环境下的计数与检测问题,消融实验进一步证明了融合模型各部分参数的有效性。     

Correspondence normalized ghost imaging on compressive sensing

Ghost imaging(GI) offers great potential with respect to conventional imaging techniques. It is an open problem in GI systems that a long acquisition time is be required for reconstructing images with good visibility and signal-to-noise ratios(SNRs). In this paper, we propose a new scheme to get good performance with a shorter construction time. We call it correspondence normalized ghost imaging based on compressive sensing(CCNGI). In the scheme, we enhance the signal-to-noise performance by normalizing the reference beam intensity to eliminate the noise caused by laser power fluctuations, and reduce the reconstruction time by using both compressive sensing(CS) and time-correspondence imaging(CI) techniques. It is shown that the qualities of the images have been improved and the reconstruction time has been reduced using CCNGI scheme. For the two-grayscale "double-slit" image, the mean square error(MSE) by GI and the normalized GI(NGI) schemes with the measurement number of 5000 are 0.237 and 0.164, respectively, and that is 0.021by CCNGI scheme with 2500 measurements. For the eight-grayscale "lena" object, the peak signal-to-noise rates(PSNRs)are 10.506 and 13.098, respectively using GI and NGI schemes while the value turns to 16.198 using CCNGI scheme. The results also show that a high-fidelity GI reconstruction has been achieved using only 44% of the number of measurements corresponding to the Nyquist limit for the two-grayscale "double-slit" object. The qualities of the reconstructed images using CCNGI are almost the same as those from GI via sparsity constraints(GISC) with a shorter reconstruction time.     

针对多散斑图的差分压缩鬼成像方案研究

鬼成像方案实现所需设备、成像的质量以及成像所花的时间是决定鬼成像技术可实用化的重要因素. 本文提出一种针对多散斑图的差分压缩鬼成像方案. 该方案通过连续探测多个独立的散斑图, 降低了热光鬼成像方案对探测器高时间分辨力的要求; 通过采用差分方法, 抑制了背景噪声和其他噪声源的干扰; 通过使用压缩感知重建算法, 有效地降低了鬼成像所需时间并同时提升成像的质量. 数值仿真结果表明, 对于二灰度“N” 图, 本方案在8000次的采样情形下与多散斑图鬼成像方案35000次采样的结果相比, 均方误差降低了96.9%、峰值信噪比提升15.1 dB. 对于八灰度“Pepper”图, 本方案与多散斑图鬼成像方案相比, PSNR提升11.4 dB. 本方案可降低探测设备的要求、提高成像质量、降低重建时间, 具有广阔的应用前景.     

基于阈值分割的并行压缩鬼成像方法

为了提高鬼成像的速度,提出了基于阈值分割的并行压缩差分鬼成像方法。首先通过设置合理的阈值筛选出涨落较为明显的数据进行采样;然后再通过并行分块降低图像维度,提高整体运算速度;最后通过压缩感知重构算法重构图像。通过对图"BUAA"的半物理仿真以及透射物体"光"的实验结果表明,与普通的二阶赝热光关联成像相比,该方法能以更少的采样次数和运行时间重构图像,可提升成像信噪比。     

菲涅耳非相干数字全息大视场研究

菲涅尔非相干相关全息术(Fresnel incoherent correlation holography, FINCH)通过空间光调制器(spatial light modulator, SLM)将来自物点的光波分解为曲率半径不同的两束自相干光,干涉条纹由CCD记录.由于受限于SLM与CCD的像素数目及像素尺寸, FINCH技术与光学全息术相比记录视场要小得多.本文通过对FINCH系统的记录过程进行理论分析,给出了SLM所能记录的视场角,说明通过调控加载在SLM上的双透镜光轴中心,能够扩大SLM的有效直径从而将SLM的有效记录范围增大2.77倍,有效扩大了系统的记录视场.搭建了非相干光反射式数字全息记录系统并对理论分析进行了实验验证,结果表明:在SLM上依次加载不同光轴中心位置的双透镜掩模进行FINCH记录及再现,将得到的各子图像拼接融合可以得到高分辨率大视场图像,为菲涅尔非相干全息术在高分辨大视场显微成像的进一步应用提供了有力支撑.     

高分辨率开环液晶自适应光学视网膜成像系统

利用液晶空间光调制器和夏克-哈特曼波前探测器作为核心器件搭建了一套开环双光源液晶自适应光学视网膜成像系统.系统采用人眼屈光0D基准设计并使用动态视标定位人眼,提高了人眼在测试时的稳定性,有效降低了由不同人眼个体差异带来的影响.通过补偿镜预补偿,配合微调照明光焦面,使照明光聚焦在眼底视觉细胞层,保证了像差探测精度和成像质量.利用人眼的偏振特性,采用偏振光照明的方式,将系统的能量利用率提高了20％.优化了系统的工作流程,优化后系统连续工作频率可超过20 Hz.对4名志愿者进行了实验,均获得了清晰的眼底视网膜细胞图像.     

开环双脉冲液晶自适应光学视网膜成像系统

为了获得高分辨率视网膜图像,利用液晶空间光调制器作为波前校正器建立了一套开环液晶自适应光学视网膜成像系统.与闭环模式相比,采用开环模式后,系统的能量利用率提高了1倍.系统采用双脉冲照明方式,以减少人眼曝光量,保护人眼安全.在照明光学系统中加入了大小视场切换装置使成像视场由之前的0.8°增至1.7°.同时优化了系统的时序控制流程,对人眼像差连续校正的同时快速调节成像相机的前后位置至最佳像面.对于开环模式对动态人眼像差的校正精度进行了测量,实验测得,经开环校正后,残差波面的均方根值约为0.09λ;相应的斯特雷尔(Strehl)比高于0.70,系统分辨率接近光学衍射极限的分辨率.对两名志愿者进行了实验,获得了清晰的眼底视网膜细胞图像.     

Evaluation of imaging protocol for ECT based on CS image reconstruction algorithm

Single-photon emission computerized tomography and positron emission tomography are essential med- ical imaging tools, for which the sampling angle number and scan time should be carefully chosen to give a good compromise between image quality and radiopharmaceutical dose. In this study, the image quality of different ac- quisition protocols was evaluated via varied angle number and count number per angle with Monte Carlo simulation data. It was shown that, when similar imaging counts were used, the factor of acquisition counts was more important than that of the sampling number in emission computerized tomography. To further reduce the activity requirement and the scan duration, an iterative image reconstruction algorithm for limited-view and low-dose tomography based on compressed sensing theory has been developed. The total variation regulation was added to the reconstruction process to improve the signal to noise Ratio and reduce artifacts caused by the limited angle sampling. Maximization of the maximum likelihood of the estimated image and the measured data and minimization of the total variation of the image are alternatively implemented. By using this advanced algorithm, the reconstruction process is able to achieve image quality matching or exceed that of normal scans with only half of the injection radiopharmaceutical dose.