Range image noise suppression in laser imaging system

Laser radar is able to produce both intensity images and range images. These two images provide the full 3-D information of the target. The quality of the range image is negatively impacted by noise arising from dropouts and range anomalies. This paper proposes an algorithm for range image background suppression, utilizing the intensity image, a mathematical morphology (MM) filter and a mean filter. An order-mean-filter algorithm is applied to suppress the range anomaly. A comparison of the filter effects between various templates and templates in weighted mode was made, resulting in the selection of the order-mean-filter algorithm of the best multiple template. It was applied to the range image formed by the target in the actual radar.     

Correlation recognition for range image of laser radar

The target recognition of laser radar becomes hot research in recent years, because laser radar can produce high space resolution and collect rich target information, such as range image, intensity image and Doppler image. In the vertical detection of laser radar, the problem of in-plane target rotation invariance is firstly solved. In the paper, a new support vector machine (SVM) correlation filter is presented, which simultaneously has the attractive attributes of SVM and common correlation filter. Exploiting the idea of margin of separation maximization, the design criterion is produced. The filter is synthetic by the multiple training images which are generated by rotating one image. The real range images of laser radar are used to finish the correlation experiments. The results show that the filter is not sensitive to the noise, the correlation peak is changed slightly for the different testing images, and the precision of location is high.This design way can be used in other recognition fields.     

利用激光主动探测技术实现光电窥视设备检测

针对激光主动探测时光电设备表现出的猫眼效应,搭建了基于CCD的激光主动探测系统,提出了一套有效的光电窥视设备检测算法。该算法在激光脉冲的间隔,同时采集激光主被动图像,根据窥视目标与普通漫反射物体的回波强度差异,利用背景差法检测窥视目标。实验结果表明,在半径为5 m的作用范围内,该激光主动探测系统可有效、快速地将光电窥视目标从背景中检测出来,并且不受场景和光照的限制。通过对光学口径为2 mm的光电窥视设备在20个不同场景环境下进行实验,正确检测率达到95%,且每帧的检测时间在0.015~0.021 s内,满足了实时性需求,验证了本文系统搭建方案的正确性与软件处理算法的有效性。     

一种新的激光雷达距离像噪声抑制方法

主要针对激光雷达距离像的距离反常噪声抑制问题,阐述了激光雷达距离像的噪声原理,分析了应用传统中值滤波方法抑制距离反常噪声的缺陷,提出了基于包围准则的自适应中值滤波算法。该方法首先根据包围准则检测噪声,对5×5滤波窗口内的像素值进行排序差分;然后选择低于门限长度最长的连续差分值对应的像素值作为距离正常值;最后运用中值滤波和加权均值滤波进行噪声抑制。实验结果表明,该方法有效抑制了距离反常噪声,且较好地保护了距离图像中目标的边缘细节,均方根误差分别比3×3和5×5窗口中值滤波法减少了27.1%和9.1%。     

相干激光雷达距离像的噪声抑制算法研究

激光雷达能同时成距离像和强度像,较其他的成像体制给出更多的有用信息。距离像的去噪是激光雷达图像处理的关键步骤,去噪的好坏直接关系激光雷达在跟踪、定位等方面的精确性。根据距离像噪声来源,采用结合强度像的多级中值滤波对实际的雷达图像进行了去噪处理。首先利用强度像3×3邻域均值和图像平均值消除失落信息影响,然后采用多级中值滤波消除逸出值。分别给出了各步处理结果,最终获得了较清晰的距离像。研究结果表明运用结合强度像的多级中值滤波方法能够有效地抑制相干激光雷达距离像的噪声。     

4-D image reconstruction for Streak Tube Imaging Lidar

The Streak Tube Imaging Lidar (STIL) which is the flash laser radar is developed in recently years. It can output the 4-D image (3-D range image + 1-D intensity image). The core part of STIL is the streak tube, which is a line array detector. STIL can directly collect the image of returned light pulse, and consequently, it can’t output the 4-D target image. In the paper, the peak detection as the reconstruction algorithm is used to reconstruct the multiple streak tube images, and the clear 4-D target images are obtained. The outdoor imaging experiments are completed for the far distance buildings. The reconstruction for the multiple streak tube images is finished, and the results state that the peak detection algorithm can output the high-resolution 4-D target images. Original Text ? Astro, Ltd., 2009. The article is published in the original.     

Segmentation of holographic images using the level set method

Image segmentation, which is to distinguish objects from background, has played an important role in holographic image processing. In this work, we propose a technique that uses the combination of rough segmentation and the level set methods for segmentation of holographic images with zero-order diffraction interference. To improve the image quality, we eliminate the interference of zero-order diffraction in digital holography using Sobel differential gradient algorithm based on digital image processing. After reconstruction, the rough segmentation including intensity transformations and Morphology methods is applied to acquire the rough contour of the reconstruction image. Finally, we adopt level set methods to smooth the object contour and improve its accuracy. Segmentation results for objects in holographic images are presented.     

葡萄糖注射液中不溶性微粒的识别算法研究

针对传统人工目测法以及光阻检测法在葡萄糖注射液中不溶性微粒识别判断效率较低现象,提出了一种背景差预处理与改进的Mean Shift算法相结合的微粒识别算法。利用高分辨率数码相机采集在一定照度下葡萄糖注射液中不溶性微粒产生散射光的序列数字图像。对序列数字图像进行预处理及并标定数字图像有效检测区域。建立序列数字图像背景模型并对背景噪声与随机噪声进行抑制处理。采用改进的Mean Shift算法对葡萄糖注射液中不溶性微粒进行目标跟踪。通过对序列数字图像中被检测对象的分割与特征提取,实现了葡萄糖注射液中粒径在25μm以上不溶性微粒的识别。     

Research on a flash imaging lidar based on a multiple-streak tube

A flash imaging lidar based on a multiple-streak tube is presented in this paper; a fiber remapping optics maps light from an area in the focal plane of an imaging lens to multiple rows of fibers on the streak tube’s photocathode. The lidar system contains a multiple-streak tube, laser, transmitting and receiving telescope, remapping optical fibers, and CCD to capture stripe images from the streak tube’s phosphor screen. Data processing yields 48 × 48-pixel intensity and range images for each laser pulse. An experiment to test the property of this lidar is carried out in the laboratory; the intensity images and range images are gained by image remapping, and the range sampling is 0.21 m. Field test imagery demonstrated the capability of the flash lidar system to image a building 705 m away.     

高斯差分滤波多尺度损伤提取方法

提出了高斯差分滤波的多尺度损伤提取方法和流程,对大口径光学元件的损伤图像进行了处理,结果表明,该方法对微弱信号与强信号混杂有很好适应性,且能有效解决低信噪比光学元件损伤图像中的损伤提取难题,对于分辨率125 m、口径400 mm400 mm的光学元件损伤图像,该方法可以100％提取损伤图像中尺寸在50 m以上的所有损伤的种子,满足了大型激光装置安全运行的需要。     

背景高斯化的遥感图像目标检测

在假设单一地表遥感图像灰度起伏符合马尔可夫模型的条件下,得到了理想单一地表灰度起伏符合高斯分布的结果。将这一结果应用于遥感图像的目标检测,提出了一种新的基于背景高斯化的遥感图像目标检测方法。该方法首先将遥感图像进行高斯化处理,将其作为近似理想背景,然后将原图像与高斯化背景做差得到残差图,进而对残差图进行目标检测。由于目标本身的信息远离背景高斯化模型,因此在背景消减的过程中,目标信息得到了很好的保持,比在原图上进行目标检测性能得到了很大的提高。实验结果进一步验证了算法具有很好的检测性能。     

基于统计特性的激光雷达距离像噪声抑制算法

激光成像雷达在工作时会受到噪声干扰,因此需要滤除距离像中无法反映真实信息的异常点。根据激光成像雷达距离像噪声的分布,推导出距离像中非异常值的分布特性,并提出了一种距离像异常值的判定条件。将判定条件表示为小范围内抽样分布的函数,利用稳健统计中的中位值法可估算出判定条件的取值,从而可以移除异常点得到噪声抑制后的距离像。利用该算法分别对激光雷达距离像进行仿真和实际获得的激光雷达距离像进行处理并进行数学分析,并与中值滤波进行了比较,结果表明基于统计特性的噪声抑制算法同时具有很强的噪声抑制能力和保护目标细节信息能力,可以满足激光成像雷达距离像噪声抑制的要求。算法充分利用了激光成像雷达较高的测距精度,可以应对多种场景下的需求,具有很强的实用性。     

Unsupervised constrained radar imaging of low resolution targets

A linear spectral estimation technique, the PDFT algorithm, is used as part of a nonlinear iterative reconstruction scheme to obtain improved radar images. The iterative PDFT algorithm is used to address the limited resolution problem inherent to imaging objects buried in soil and hidden under foliage. This is achieved by subsequent application of two properties of the PDFT algorithm: the energy parameter of the PDFT algorithm is used to determine the target shape, while the shape information in turn is used to obtain super-resolved images. We describe algorithms able to exploit both properties automatically and without manual intervention. Two methods are investigated in particular, one iteratively optimizing the constraints by monitoring the energy parameter, the other method computing energy values for all points, from which a weighted prior function is determined. In addition, we discuss variants of both algorithm which provide an optimized trade-off between computation time and performance. Additional attention is given to situations, where a known target is embedded in an unknown background. Imaging results are presented for both synthetic and measured data.     

3D卷积自动编码网络的高光谱异常检测

高光谱图像包含丰富的地物光谱信息,在遥感图像领域有着巨大的发展前景。高光谱图像异常检测无需任何先验光谱信息,便可检测出图像中的异常目标。因此,在国防军事和民用领域都有广泛的应用,是现阶段高光谱图像处理领域的研究热点。然而,高光谱图像存在数据复杂、冗余性强、未标记以及样本数量少等特点,这给高光谱图像异常检测带来了很大的挑战。尤其是在深度学习中,往往需要大量的图像数据作为训练样本,这对高光谱图像来说很难获得。针对现有大多数算法对高光谱图像自适应性不强和空间-光谱信息利用不足的问题,提出一种基于3D卷积自动编码网络的高光谱异常检测算法,可以在少量训练数据的前提下,有效利用高光谱图像信息,学习更加有判别性的特征表达,提高检测精度。首先,通过3D卷积、3D池化和3D归一化等步骤设计3D卷积网络,进而提取高光谱图像的空间-光谱结构特征。然后,将3D卷积网络和3D反卷积网络分别嵌入自动编码网络的编码器和解码器,通过最小化结合均方差和光谱角距离的重构误差进行背景重构。最后,利用原始高光谱图像待测像元与重构的背景图像之间的马氏距离进行异常检测。该算法可以在无先验信息的情况下,自动训练网络中的所有参数,以无监督的方式学习高光谱图像的有效特征并进行背景重构。为证明算法的有效性,利用截取来自三组真实高光谱数据集的九个图像进行异常检测,并与RX,SRX,CRD,UNRS和LRASR五种算法进行对比。结果表明,与现有的其他算法相比,该算法可以在复杂程度不同的高光谱图像背景下可以保持较高的检测效果和准确率。     

Accurate ball tracking in volleyball actions to support referees

This paper proposes a method for offline accurate ball tracking for short volleyball actions in sport halls. Our aim is to detect block touches on the ball and to determinate accurate trajectory and impact positions of the ball to support referees. The proposed method is divided into two stages, namely training and ball tracking, and is based on background subtraction. Application of the Gaussian mixture model has been used to estimate a background, and a high-speed camera with a capture rate of 180 frames per second and a resolution of 1920?×?1080 are used for motion capture. In sport halls significant differences in light intensity occur between each sequence frame. To minimize the influence of these light changes, an additional model is created and template matching is used for accurate determination of ball positions when the ball contour in the foreground image is distorted. We show that this algorithm is more accurate than other methods used in similar systems. Our light intensity change model eliminates almost all pixels added to images of moving objects owing to sudden changes in intensity. The average accuracy achieved in the validation process is of 0.57 pixel. Our algorithm accurately determined 99.8% of all ball positions from 2000 test frames, with 25.4?ms being the average time for a single frame analysis. The algorithm presented in this paper is the first stage of referee support using a system of many cameras and 3D trajectories.     

Image enhancement via Median-Mean Based Sub-Image-Clipped Histogram Equalization

This paper presents a robust contrast enhancement algorithm based on histogram equalization methods named Median-Mean Based Sub-Image-Clipped Histogram Equalization (MMSICHE). The proposed algorithm undergoes three steps: (i) The Median and Mean brightness values of the image are calculated. (ii) The histogram is clipped using a plateau limit set as the median of the occupied intensity. (iii) The clipped histogram is first bisected based on median intensity then further divided into four sub images based on individual mean intensity, subsequently performing histogram equalization for each sub image. This method achieves multi objective of preserving brightness as well as image information content (entropy) along with control over enhancement rate, which in turn suits for consumer electronics applications. This method avoids excessive enhancement and produces images with natural enhancement. The simulation results show that MMSICHE method outperforms other HE methods in terms of various image quality measures, i.e. average luminance, average information content (entropy), absolute mean brightness error (AMBE) and background gray level.     

Unsupervised constrained radar imaging of low resolution targets

Abstract

A linear spectral estimation technique, the PDFT algorithm, is used as part of a nonlinear iterative reconstruction scheme to obtain improved radar images. The iterative PDFT algorithm is used to address the limited resolution problem inherent to imaging objects buried in soil and hidden under foliage. This is achieved by subsequent application of two properties of the PDFT algorithm: the energy parameter of the PDFT algorithm is used to determine the target shape, while the shape information in turn is used to obtain super-resolved images. We describe algorithms able to exploit both properties automatically and without manual intervention. Two methods are investigated in particular, one iteratively optimizing the constraints by monitoring the energy parameter, the other method computing energy values for all points, from which a weighted prior function is determined. In addition, we discuss variants of both algorithm which provide an optimized trade-off between computation time and performance. Additional attention is given to situations, where a known target is embedded in an unknown background. Imaging results are presented for both synthetic and measured data.     

脉冲相干激光雷达的散斑成像模型及其散斑噪声压缩

推导了脉冲相干激光雷达的散斑成像模型,证明了脉冲相干激光雷达图像中散斑噪声的乘法性质。根据其统计规律,提出一种新的用于散斑噪声压缩的并行加权均值多方向形态滤波算法。模拟结果表明此算法既有 地压缩了散斑噪声又保持了图像的几何结构,并且通过比较,证明其优于Safa的多方向形态滤波算法。     

平顶线结构光的中心检测算法及光刀平面标定

针对传统线结构光光刀平面标定方法测量精度不高,应用范围小的问题,提出基于平面标靶的线结构光系统光刀平面标定,对无激光的标靶图片进行迭代摄像机标定,有激光的标靶图片进行光刀平面标定.提出光强符合均匀分布的平顶激光检测中心算法,将平顶激光建模为矩形的台阶函数,估计背景亮度和前景亮度,确定亮条纹宽度,再将窗口内的有效像素参与重心计算,得到光条纹中心.用该算法对不同噪声及不同量块的图片进行处理,结果表明,处理后图像的均方根误差分别在0.149pixel和0.176pixel内,表明该算法抗噪声能力强、精度高.用该算法提取光条中心,计算光条在标靶上的位置,根据至少两个姿态下的光条中心三维点,基于最小二乘法拟合光刀平面.通过迭代摄像机标定和光刀平面标定,利用三角测量法,在立体视觉模型下获取物体的三维点云数据.实验测量两个距离为100.5mm的标准球,相机与标准球距离为500mm,比较两球心距离与标准距离,测得平均误差为0.236mm.表明平顶激光检测中心算法切实可行,光刀平面标定方法基本满足要求.     

提高多光源汇聚光斑中心定位精度的形态学滤波方法

在激光指令传输中,为形成较大的光覆盖区域并增大光源的作用距离,将多个特性相同的激光器矩阵排列,构成组合光源。针对点阵多激光管光源在开放环境下成像光斑具有多个光能中心的特点,采用形态学滤波中的开启、闭合运算,去除背景噪声斑点,平滑光斑内部的小光斑叠加和干涉造成的不规则条、孔,使得能以简化的分割和定位算法,快速获得接近实际的完整光斑边界,光斑中心定位精度的均方差不大于1.2%。该方法能快速、高精度定位这种叠加光斑的中心,为远距离激光对准和测控提供了可靠的精度和时效保证。