532nm激光对面阵和线阵CCD损伤效应实验研究

为了研究面阵CCD和线阵CCD由结构差异所致激光损伤效应的区别,针对这两种类型CCD器件进行了机理分析和对比实验研究。分别测量出波长为532nm的激光对线阵CCD和面阵CCD图像传感器的光饱和串音阈值、所有像素串音阈值和硬损伤阈值。结果表明,面阵CCD的光饱和串音阈值和永久破坏阈值比线阵CCD低,而串音扩散到所有像素的阈值高于后者。反映出线阵CCD由于其1维结构更能抵抗激光的干扰和破坏,而面阵CCD在抵御饱和串音在像素间扩散上比线阵CCD有优势。     

基于ARM的线阵CCD测量系统应用分析

介绍了一种基于LPC2106的线阵CCD测量系统,其中应用了ARM微处理器,系统主要包括：线阵CCD传感器、模数转换器、ARM微处理器、显示模块及控制电路等几部分．阐述了线阵CCD的光采集工作原理和驱动脉冲的产生原理,以及ARM芯片LPC2106的软硬件设计和系统其他模块的具体操作．     

CCD线阵象传感器

一、引言CCD线阵象传感器广泛用于传真,光符识别(OCR)、工业测量等办公室自动化(OA)和工厂自动化(FA)领域.尤其是作为读取传真原稿的光电变换器件正趋向实用化.最近,传真技术向高分辨率和高速方向迅速发展,从而对读取速度更快的多象素CCD线阵象传感器产生了迫切的需求.此外利用其高精度,高分辨特性,CCD还广泛用于工件尺寸、形状、厚度、位置及缺陷等的非接触式测量与检验.     

线阵CCD图像传感器驱动电路的设计

随着CCD性能的不断提高,CCD技术在军、民用领域都得到了广泛的应用.介绍了TCD1501C线阵CCD的驱动电路设计,详细介绍了用VHDL完成的CCD图像传感器驱动时序设计和视频输出差分信号驱动电路的设计.     

CCD相机系统中驱动电路的设计

目前,线阵CCD图像传感器的种类很多,驱动时序的产生方法也是多种多样.CCD时序驱动电路的设计是CCD应用的关键,只有设计出符合要求的驱动时序,CCD器件才能稳定可靠的工作.常用的驱动方法存在某些缺点.在详细了解线阵CCD器件μPD795,分析其驱动时序与电路逻辑后,没有使用常规方法,而是使用CPLD进行功能的实现.该方法采用CPLD产生驱动,按要求写好VHDL代码产生可执行文件,通过JTAG接口下载到可编程器件中.实验结果表明该电路稳定可靠,在线阵CCD驱动电路中具有一定的代表性.     

微层析成像用传感器及其信号处理技术

研究了一种微层析成像(μCT,micro-computed tomography)用传感器.针对面阵CCD(charge coupled device)器件用于微层析成像线阵扫描中存在圆形光斑中心的图像问题,采用能量跟踪法及几何法等开展了信号处理技术的研究.新研制的传感器具有空间分辨率高(约几十μm)、结构灵活、光传输及光耦合效率高等特点.该新型传感器可实际用于微层析成像之中.     

微层析成像用传感器及其信号处理技术

研究了一种微层析成像(μCT,micro-computed tomography)用传感器.针对面阵CCD(charge coupled device)器件用于微层析成像线阵扫描中存在圆形光斑中心的图像问题,采用能量跟踪法及几何法等开展了信号处理技术的研究.新研制的传感器具有空间分辨率高(约几十μm)、结构灵活、光传输及光耦合效率高等特点.该新型传感器可实际用于微层析成像之中.     

微层析成像用传感器及其信号处理技术

研究了一种微层析成像(μCT，micro—computed tomography)用传感器，针对面阵CCD(charge coupled device)器件用于微层析成像线阵扫描中存在圆形光斑中心的图像问题，采用能量跟踪法及几何法等开展了信号处理技术的研究，新研制的传感器具有空间分辨率高(约几十μm)、结构灵活、光传输及光耦合效率高等特点，该新型传感器可实际用于微层析成像之中。     

彩色线阵CCD用于物体尺寸精密测量的研究

现有精密尺寸测量系统采用单阵列的线阵CCD作为光电传感器,不能检测像元的排列方向与物体尺寸方向的夹角γ,而当夹角γ在测量中发生变化时将引起测量误差,本文采用彩色线阵CCD（TCD2901D）作为光电传感器进行精密尺寸测量,检测出夹角变化带来的尺寸测量误差,得到了误差的修正方法。     

基于FPGA的线阵CCD驱动设计

电荷耦合器件（CCD）作为一种新型的光电器件,被广泛地应用于非接触测量。而CCD驱动设计是CCD应用的关键问题之一。为了克服早期CCD驱动电路体积大,设计周期长,调试困难等缺点,以线阵CCD图像传感器TCD1251UD为例,介绍一种利用可编程逻辑器件FPGA实现积分时间和频率同时可调的线阵CCD驱动方法,使用Verilog语言对驱动电路方案进行了硬件描述,采用QuartusⅡ对所设计的时序进行系统仿真。仿真结果表明,该驱动时序的设计方法是可行的。     

一种基于线性迭代自定标方法

提出了一种新的利用线性迭代算法来实现摄像机的自定标方法,该方法不需要景物中的任何先验知识,只需要通过线性迭代就可以实现摄像机的自定标.本文所提出的方法分为两步:第一步假设s=0、主点坐标位于坐标原点,求到绝对二次曲面在射影空间中的像,得到摄像机的内参数;第二步,利用第一步得到的摄像机的内参数,通过图像的坐标变换,使图像符合第一步假设的摄像机所获取的图像,再返回到第一步.模拟实验和真实实验数据结果表明,该定标方法运算量小、鲁棒性好、收敛性好等优点.     

Image-pair-based deblurring with spatially varying norms and noisy image updating

This paper presents a deblurring method that effectively restores fine textures and details, such as a tree’s leaves or regular patterns, and suppresses noises in flat regions using consecutively captured blurry and noisy images. To accomplish this, we used a method that combines noisy image updating with one iteration and fast deconvolution with spatially varying norms in a modified alternating minimization scheme. The captured noisy image is first denoised with a nonlocal means (NL-means) denoising method, and then fused with a deconvolved version of the captured blurred image on the frequency domain, to provide an initially restored image with less noise. Through a feedback loop, the captured noisy image is directly substituted with the initially restored image for one more NL-means denoising, which results in an upgraded noisy image with clearer outlines and less noise. Next, an alpha map that stores spatially varying norm values, which indicate local gradient priors in a maximum-a-posterior (MAP) estimation, is created based on texture likelihoods found by applying a texture detector to the initially restored image. The alpha map is used in a modified alternating minimization scheme with the pair of upgraded noisy images and a corresponding point spread function (PSF) to improve texture representation and suppress noises and ringing artifacts. Our results show that the proposed method effectively restores details and textures and alleviates noises in flat regions.     

一种基于共线特征点的线阵相机内参标定方法

提出一种利用共线的标定特征点确定线阵相机内参的方法。所有标定特征点均在线阵相机的视平面内。首先,标定过程中对标定特征点逐一成像,直接得到标定特征点和其对应像点,解决了空间标定点与像点的对应问题;其次,通过数学建模得到线阵相机的成像模型,联立多个位置处的成像模型解算出相机内参;最后,对影响线阵相机标定的因素进行分析及实验验证。理论分析和实验结果表明,文中的线阵相机标定方法简单灵活,无需制作精密的靶标,可获得大量标定点,提高了线阵相机标定的准确性和稳定性,实验得到成像特征点重投影像点位置偏差均方根为0.37 pixel。     

基于样条曲线的一种遥感图像去云方法

在可见光遥感图像中,常常因为云的阻挡而很难获得有云区域的信息.在没有预知信息的情况下,为了从一幅图像中获取有云区域的信息,采用基于样条曲线的方法,对有云区域像素的亮度值进行拉伸,得到去云后的遥感图像,既保持了云区与边界的连续性,又容易获取云区域内的信息.再使用高通滤波器与云区内像素亮度值进行卷积,突出了云区内的图像信息.实验结果表明,对于一幅有1/4被乌云覆盖的遥感图像,突出了云区内隐藏的丰富信息,能获取诸如水坝的墙体、水流等重要信息,说明图像增强技术的多样性.     

基于光纤振动的激光散斑控制

散斑噪声的存在使得图像灰度剧烈变化,降低了图像分辨率,影响成像质量。为了控制散斑噪声,使用波长为405nm的激光作为显微系统照明光源,利用音圈电机振动光纤,通过对抛光玻璃显微成像,用CCD图像采集卡采集图像后进行了散斑噪声对比度分析。结果表明,在光纤振动幅度不变、振动频率在4Hz~55Hz内逐渐增加时,图像散斑对比度在0.0326~0.1197范围内逐渐变小;当频率大于51Hz时,图像散斑对比度曲线趋于平稳且对比度在0.0326处获得了最小值,图像清晰,达到良好的散斑控制。     

Refined automatic white balancing

An efficient automatic white balancing solution for captured image correction is introduced. Colour information of the digital camera image is adjusted using both the local and global spectral characteristics of the captured visual data. Experimentation indicates that the proposed solution produces visually-pleasing colour images     

New statistical features for the design of fiber optic statistical mode sensors

Novel statistical features are proposed for the design of fiber optic statistical mode sensors. The statistical features are radial pth order moments, more precisely first and second order moments. These new features are compared with correlation and image difference features which were reported in the literature earlier. The fiber optic statistical mode sensor experiments are conducted for different applied loads and the corresponding images are captured using the CCD camera. Different statistical features such as image differencing, correlation, first moment and second moment are extracted from the captured images. These features are compared with each other in terms of different characteristics such as precision error, non-linearity, and hysteresis. It is shown that the first and second order moment statistical features are better alternatives for the design of statistical mode sensors, when precision and linearity characteristics are more important than the hysteresis characteristic.     

面积约束下的最优阈值法分割LED像素点阵

针对基于CCD相机采集方式的亮度校正方法需要从采集图像中分割出每颗LED像素的亮度信息的问题,提出面积约束下的最优阈值分割法。在最优阈值分割法的基础上,根据先验信息引入面积约束条件,对阈值的取值范围进行约束。与传统的最优阈值法相比可以避免分割后LED像素区域连接的情况。面积约束下的最优阈值分割法生成采集图像的灰度直方图,利用最优阈值算法结合面积约束生成最优阈值,最后通过图像的阈值分割法将采集图像分割。实验表明,该方法可以比较好地分割出采集图像中的LED像素,并可避免当LED像素点分布密集时应用最优阈值法分割LED像素造成的区域连接问题。     

A novel haze image steganography method via cover-source switching

In realistic outdoor scenarios, image sensors tend to suffer from various weather conditions (e.g., haze, rain, etc.),which make the images of the same scene taken at different times may be different. Therefore, one should be able to securely embed secret messages into these images by making use of the variations of the weather effects. Inspired by some recent natural steganography algorithms, this paper presents a novel haze image steganography method, which embeds messages through adjusting the weather effects of an input haze image, making it resemble the same image captured under another weather condition. The proposed steganography method consists of three parts: (1) model parameter estimation of the input haze image, (2) haze effects adjustment according to the atmospheric scattering model, (3) message embedding using the floating-point adjusted haze image. 10,000 haze images captured under different haze conditions in various scenarios were used to test the proposed steganography algorithm. The experimental results show that the proposed steganography algorithm is more secure than S-UNIWARD and HILL for steganalyzers who only have raw haze images.     

Real‐Time Digital Image Stabilization for Cell Phone Cameras in Low‐Light Environments without Frame Memory

This letter proposes a real‐time digital image stabilization system for cell phone cameras without the need for frame memory. The system post‐processes an image captured with a safe shutter speed using an adaptive denoising filter and a global color correction algorithm. This system can transfer the normal brightness of an image previewed under long exposure to the captured image making it bright and crisp with low noise. It is even possible to take photos in low‐light conditions. By not needing frame memory, the approach is feasible for integration into the size‐constrained image sensors of cell phone cameras.