The generation of speckle patterns via random matrices, statistical definitions, or apertures may not always result in optimal outcomes. Issues such as correlation fluctuations in low ensemble numbers and diffraction in long-distance propagation can arise. Instead of improving results of specific applications, our solution is catching deep correlations of patterns with the framework, Speckle-Net, which is fundamental and universally applicable to various systems. We demonstrate this in computational ghost imaging (CGI) and structured illumination microscopy (SIM). In CGI with extremely low ensemble number, it customizes correlation width and minimizes correlation fluctuations in illuminating patterns to achieve higher-quality images. It also creates non-Rayleigh nondiffracting speckle patterns only through a phase mask modulation, which overcomes the power loss in the traditional ring-aperture method. Our approach provides new insights into the nontrivial speckle patterns and has great potential for a variety of applications including dynamic SIM, X-ray and photo-acoustic imaging, and disorder physics.

相干激光测风雷达具有体积小、探测效率高、信噪比强等特点，在气象、航空保障以及风电等行业得到了广泛的应用，但是目前雷达数据产品大多是利用回波多普勒频移信息反演的风场数据产品，未对雷达回波信号强度信息进行数据挖掘。针对当前相干激光测风雷达数据产品开发不足的问题，介绍了一种新型基于相干探测的激光雷达数据产品生成技术，该技术在探测风场的同时，实现云高、消光系数及能见度等多种气象要素数据产品的生成。首先，通过分析回波信号特性，推导出雷达回波信号功率的计算方法，获取探测范围内各距离位置的回波信号强度信息。在此基础上，利用阈值法和微分零叉法反演出云底高度，同时采用改进型Klett算法实现大气消光系数的反演，继而实现能见度的测量。最后，与气象站能见度仪、激光云高仪以及532 nm气溶胶激光雷达进行数据对比验证试验，试验数据结果显示：云高对比精度可达5.0%，能见度对比精度可达12.2%，消光系数对比有较好的一致性，并可长期在多种气象环境下连续测量。

在利用多线结构光系统对大尺度连铸坯进行三维测量的过程中，线结构光中心条纹的提取精度是影响三维测量精度的重要因素。提出了一种对传统灰度质心方法进行优化的多线结构光中心条纹提取方法。对连铸坯表面激光横截面不满足高斯分布的线结构光条纹，利用图像背景差分的方式去除环境噪声，并根据线结构光条纹与背景间的灰度变化信息确定线结构光的边界，同时提取线结构光的感兴趣区域。根据光条在梯度方向上的灰度积分比例计算灰度质心法的自适应灰度阈值，利用灰度质心方法处理感兴趣区域提取出光条中心点，最后结合附近半径为5个像素的邻域内所定位的中心点进行质心重提取，获得连铸坯表面光条的亚像素中心坐标。现场测量结果表明：对反射特性不均匀的连铸坯表面的激光条纹光条中心进行提取，最终连铸坯边缘轨迹点的三维测量结果标准偏差在2 mm以内，该方法具有精度高、速度快、鲁棒性强的特点。

Optical imaging through scattering media has long been a challenge. Many approaches have been developed for focusing light or imaging objects through scattering media, but usually, they are either invasive, limited to stationary or slow-moving media, or require high-resolution cameras and complex algorithms to retrieve the images. By utilizing spatial–temporal encoded patterns (STEPs), we introduce a technique for the computation of imaging that overcomes these restrictions. With a single-pixel photodetector, we demonstrate non-invasive imaging through scattering media. This technique is insensitive to the motion of the media. Furthermore, we demonstrate that our image reconstruction algorithm is much more efficient than correlation-based algorithms for single-pixel imaging, which may allow fast imaging for applications with limited computing resources.

Semiconductor photocatalysis, as a key part of solar energy utilization, has far-reaching implications for industrial, agricultural, and commercial development. Lack of understanding of the catalyst evolution and the reaction mechanism is a critical obstacle for designing efficient and stable photocatalysts. This review summarizes the recent progress of in-situ exploring the dynamic behavior of catalyst materials and reaction intermediates. Semiconductor photocatalytic processes and two major classes of in-situ techniques that include microscopic imaging and spectroscopic characterization are presented. Finally, problems and challenges in in-situ characterization are proposed, geared toward developing more advanced in-situ techniques and monitoring more accurate and realistic reaction processes, to guide designing advanced photocatalysts.