Crosstalk and microlens study in a color CMOS image sensor

The paper describes results of crosstalk investigations and microlens (/spl mu/-lens) scan experiments in a color CMOS image sensor with active pixel structure . The investigation of optical and electrical crosstalk was made on 7.8- and 5.6-/spl mu/m pixels by using samples with continuous shift of color filter (CF ) and /spl mu/-lens across the array. As a result of this investigation, the distribution of sensitivity inside a pixel has been determined. By using minimum crosstalk criteria, the optimum parameters of the /spl mu/-lens manufacturing process and optimum position of the /spl mu/-lens was determined. The paper presents color maps of pixel sensitivity and crosstalk criteria as well as snapshots illustrating sensitivity distribution and collection area. The paper presents spectral characteristics measured at different relative apertures (f-number) as well. The quantitative analysis of spectral responses allowed us to determine the contribution of each component to the overall crosstalk.     

New signal readout method for ultrahigh-sensitivity CMOS image sensor

We propose a new signal readout method that uses a charge-transfer circuit. Its application is to an ultrahigh-sensitivity CMOS image sensor on which an avalanche-mode photoconductive film is overlaid. The charge-transfer circuit makes it possible to obtain high signal-to-noise ratio features by transferring signal charges accumulated in each photodiode to a parasitic capacitance that is small compared with the photodiode capacitance. A 138 /spl times/ 138 passive-pixel prototype sensor that had the charge-transfer circuit in each column was fabricated and tested. The prototype's column-to-column fixed-pattern noise and random noise were, respectively, 56.7 and 58.4 dB below the saturation signal level, which demonstrated its potential as a signal readout circuit for a next-generation ultrahigh-sensitivity CMOS image sensor.     

A new accelerated transfer method for the CPD image sensor

A new charge transfer method for the CPD image sensor is proposed. In this method a high transfer speed is achieved with the use of an accelerated charge priming transfer (CPT) coupler, which consists of the array of the conventional CPT's and inverter amplifiers. This constitution strikingly increases the speed as well as the efficiency of the charge transfer from the vertical transport lines with large capacitance to the horizontal buried-channel charge-coupled (BCCD) shift register. Under a high transfer efficiency of more than 98 percent, a short transfer time less than 1 µs has been attained, independently of the signal charge magnitude.     

Computational image sensor for on sensor compression

We propose a novel integration of image compression and sensing in order to enhance the performance of an image sensor. By integrating a compression function onto the sensor focal plane, the image signal to be read out from the sensor is significantly reduced and the pixel rate of the sensor ran consequently be increased. The potential applications of the proposed sensor are in high pixel-rate imaging, such as high frame-rate image sensing and high-resolution image sensing. The compression scheme we employ is a conditional replenishment, which detects and encodes moving areas. In this paper, we introduce two architectures for on-sensor compression; one is the pixel parallel approach and the other is the column parallel approach. We prototyped a VLSI chip of the proposed sensor based on the pixel parallel architecture. We show the design and describe the results of the experiments obtained by the prototype chip     

基于最小二乘法的人脸素描卡通图像算法

为了合成具有高辨识度的素描卡通人脸图像,文中提出一种基于最小二乘法的智能化图像处理算法。文中在介绍最小二乘法的基本原理的基础上,详细阐明了该算法的具体细节,论述了真实人脸图像的预处理过程,建立了合成素描卡通人像的数学模型。同时基于最小二乘法引出了合成算法的误差估计方法,最终提出一种将真实照片转化为素描卡通人像的合成算法。仿真与测试结果表明,文中所提出的算法可以将真实人脸照片转化为具有素描卡通效果的人脸图像,且具有较高的辨识度。     

基于最小二乘法的气温曲线回归模型分析

随着我国气象事业的不断发展及气象数据的日益增加,进行气象数据分析及研究已成为科研人员的一项重要任务。文中充分利用MATLAB软件强大的科学计算功能及灵活的程序设计流程,基于最小二乘原理对某地某天的气温数据进行了一些研究。     

扭曲文本图像校正的新模型方法

由于书页弯曲的原因,摄像头拍摄的文本图像会有一定的扭曲现象,这样用光学字符识别(OCR)软件识别时会出现问题。为了解决这个问题,提出了一种新的抛物线数学模型,对文本线进行遍历,得到一系列文字的位置点,用位置点的坐标结合模型拟合出文本线,根据文本线与水平线之间的差距进行精确恢复,以得到水平分布的文本行。实验表明,该方法有效实现了扭曲文本图像的校正,并且有很高的时间效率。     

提高CCD图像传感器填充因子的微透镜阵列的研究

为了提高可见光CCD图像传感器的探测灵敏度,提出了516×516元石英微透镜阵列的设计方法,并简要介绍了其制作工艺.测量结果表明,所制作的微透镜阵列有优良的表面轮廓、较好的几何尺寸均匀性和光学性能,大幅度地提高了CCD图像传感器的填充因子.     

路面破损图像实时检测方法研究

提出一种路面破损图像实时检测的实现方法。对高速采集的路面图像去模糊后再进行裂纹特征分析。设计了一种基于邻域像素灰度值比较的特征快速提取方法,利用邻域相关及连贯性等知识智能去除虚假裂纹,从而提取真实裂纹信息。大量采集的图片的处理结果表明,该方法可实时快速检测路面破损信息,具有较强的鲁棒性和实际应用性。     

路面破损图像实时检测方法研究

提出一种路面破损图像实时检测的实现方法.对高速采集的路面图像去模糊后再进行裂纹特征分析,设计了一种基于邻域像素灰度值比较的特征快速提取方法,利用邻域相关及连贯性等知识智能去除虚假裂纹,从而提取真实裂纹信息.大量采集的图片的处理结果表明,该方法可实时快速检测路面破损信息,具有较强的鲁棒性和实际应用性.     

A generalized logarithmic image processing model based on the gigavision sensor model

The logarithmic image processing (LIP) model is a mathematical theory providing generalized linear operations for image processing. The gigavision sensor (GVS) is a new imaging device that can be described by a statistical model. In this paper, by studying these two seemingly unrelated models, we develop a generalized LIP (GLIP) model. With the LIP model being its special case, the GLIP model not only provides new insights into the LIP model but also defines new image representations and operations for solving general image processing problems that are not necessarily related to the GVS. A new parametric LIP model is also developed. To illustrate the application of the new scalar multiplication operation, we propose an energy-preserving algorithm for tone mapping, which is a necessary step in image dehazing. By comparing with results using two state-of-the-art algorithms, we show that the new scalar multiplication operation is an effective tool for tone mapping.     

一种改进的双变量收缩模型图像去噪

针对噪声图像低频子带含有噪声的特点,给出了一种改进的局部自适应双变量收缩模型的图像去噪算法,对于高频子带用局部自适应双变量模型进行去噪,而对低频子带用具有局部自适应的高斯模型进行去噪。该算法既体现了尺度内的聚类性,又体现了尺度间的相关性且具有很好的局部自适应性,在实验中用离散小波变换进行去噪。实验结果表明,这种改进的算法无论从峰值信噪比,还是从主观视觉效果上都要优于传统的去噪算法。     

Metric for multimodal image sensor fusion

A novel objective non-reference metric for multimodal image sensor fusion is presented. Using the joint segmentation of the input images and entropy of the regions as the priority, an `ideal' fused image is obtained. The metric is based on computing how accurately the important regions from the input images are transferred into the fused image. Experiments have shown that the obtained metric values correspond better to the subjective quality of the fused images than other state-of-the-art fusion metrics     

CMOS image sensors for sensor networks

We report on two generations of CMOS image sensors with digital output fabricated in a 0.6 μm CMOS process. The imagers embed an ALOHA MAC interface for unfettered self-timed pixel read-out targeted to energy-aware sensor network applications. Collision on the output is monitored using contention detector circuits. The image sensors present very high dynamic range and ultra-low power operation. This characteristics allow the sensor to operate in different lighting conditions and for years on the sensor network node power budget. Eugenio Culurciello (S’97–M’99) received the Ph.D. degree in Electrical and Computer Engineering in 2004 from Johns Hopkins University, Baltimore, MD. In July 2004 he joined the department of Electrical Engineering at Yale University, where he is currently an assistant professor. He founded and instrumented the E-Lab laboratory in 2004. His research interest is in analog and mixed-mode integrated circuits for biomedical applications, sensors and networks, biological sensors, Silicon on Insulator design and bio-inspired systems. Andreas G. Andreou received his Ph.D. in electrical engineering and computer science in 1986 from Johns Hopkins University. Between 1986 and 1989 he held post-doctoral fellow and associate research scientist positions in the Electrical and Computer engineering department while also a member of the professional staff at the Johns Hopkins Applied Physics Laboratory. Andreou became an assistant professor of Electrical and Computer engineering in 1989, associate professor in 1993 and professor in 1996. He is also a professor of Computer Science and of the Whitaker Biomedical Engineering Institute and director of the Institute’s Fabrication and Lithography Facility in Clark Hall. He is the co-founder of the Johns Hopkins University Center for Language and Speech Processing. Between 2001 and 2003 he was the founding director of the ABET accredited undergraduate Computer Engineering program. In 1996 and 1997 he was a visiting professor of the computation and neural systems program at the California Institute of Technology. In 1989 and 1991 he was awarded the R.W. Hart Prize for his work on mixed analog/digital integrated circuits for space applications. He is the recipient of the 1995 and 1997 Myril B. Reed Best Paper Award and the 2000 IEEE Circuits and Systems Society, Darlington Best Paper Award. During the summer of 2001 he was a visiting professor in the department of systems engineering and machine intelligence at Tohoku University. In 2006, Prof. Andreou was elected as an IEEE Fellow and a distinguished lecturer of the IEEE EDS society. Andreou’s research interests include sensors, micropower electronics, heterogeneous microsystems, and information processing in biological systems. He is a co-editor of the IEEE Press book: Low-Voltage/Low-Power Integrated Circuits and Systems, 1998 (translated in Japanese) and the Kluwer Academic Publishers book: Adaptive Resonance Theory Microchips, 1998. He is an associate editor of IEEE Transactions on Circuits and Systems I.     

Development of a novel image sensor and its application to analysis of automobile components

The authors have developed a novel image sensor for continuous conditioned monitoring of high-precision tolerances of a complex automotive product. A novel mechanooptical arrangement has been designed and validated to capture the images/silhouettes of the components as input into a neural network designed on approximate reasoning architecture. The design is extensible to handle a large number of rules, and the speed of inference is almost independent of the number of rules.     

利用仿真星图的星敏感器地面功能测试方法

介绍了一种基于仿真星图的星敏感器地面功能测试方法.该方法对卫星(飞行器)运动轨道和姿态参数及星敏感器的姿态参数进行仿真计算、模拟生成星敏感器在轨状态下的仿真星图.星敏感器以此仿真星图作为测试信号源,通过对仿真星图的处理,实现对星点定位、星图识别、姿态计算等功能的全面测试.为简化电路设计,该方法选用星敏感器现有接口作为通讯接口.为满足功能测试的实时性需求,采取局部更新的手段来减少星图传输数据量.实验表明,该方法能对星敏感器电子部件的功能进行有效验证,在使用RS232接口、波特率设置为115 200 bps的情况下,可以实现20 Hz数据更新率的测试.该方法实现简单、通用性强且不依赖其他外部设备,可以满足航天环境试验和整星联调阶段的功能测试任务要求.     

表面等离子共振传感技术的发展与应用

表面等离子体共振（surface Plasmon Resonance SPR）技术是一种简单、直接的传感技术,是表面等离子体在金属和电介质的交界面上形成的一电荷层,在电磁波的激励下,表面等离子体发生共振现象。根据这一原理研制的表面等离子体传感器在检测、分析生物分子间的相互作用等方面得广泛的应用。介绍表面等离子传感器的工作原理和研究进展,由于其具有体积小、测量准确度高、抗电磁干扰能力强,因此表面等离子共振传感器在生物医学、环境保护、食品及化学等领域得到广泛的应用前景。     

CMOS prototype image sensor with edge enhancement to compensate for blurring

Small signal analytical analysis and large signal numerical calculations are presented for a gyroklystron in which a low order (TE₀₁₁) mode in the bunching cavity is coupled by the electron beam to a high order (TE₀₄₁) mode in the output cavity. A drift region separates the two cavities. We demonstrate that the probunching of the beam before entering the output cavity not only enhances the interaction efficiency of the TE₀₄₁ mode but also improves the mode stability by suppressing the TE₂₄₁ mode. The gyroklystron may be operated either as an oscillator or as an amplifier by a small variation of the applied magnetic field. The effect of the beam velocity spread on the efficiency is also investigated. It is found that the operation of the gyroklystron is more sensitive to beam velocity spread than that of a gyromonotron. Optimum conditions for a cold beam are not necessarily those for a wam beam.     

Trust evaluation method for clustered wireless sensor networks based on cloud model

Trust Management has been proved to be an effective method to detect malicious nodes and ensure security in Wireless Sensor Networks (WSNs). While, most existing trust management methods are not good at dealing with uncertainty of trust relationship such as randomness, fuzziness in WSNs, which leads to inaccurate trust metric. In this paper, a trust evaluation method for clustered wireless sensor networks based on cloud model is proposed and evaluated, which implements the conversion between qualitative and quantitative of sensor nodes’ trust metrics in order to achieve better trust evaluation. Firstly, the method considers multi-factors including communication factor, message factor and energy factor and builds mathematical model for each trust factor to get factor trust cloud. Secondly, immediate trust cloud is calculated by assigning adjustive weights for each factor trust cloud and combining them. Thirdly, recommendation trust cloud and immediate trust cloud are synthesized according to time sensitive factor in order to get final trust cloud. Furthermore, the final trust cloud of sensor node is converted to trust grade by trust cloud decision-making. Verification Experiments manifest that the proposed method has feasibility and accuracy in the aspect of evaluating sensor nodes’ trust. Moreover, comparison experiments under different attacks show that our method is sensitive to multiple attacks, it outperforms other trust evaluation methods not only in the accuracy of detecting malicious nodes, but also in the tolerance of abnormal conditions.     

采用图像分割方法进行木材表面缺陷的定量检测

随着木材加工业的集约化发展以及对木材表面加工质量高水平的苛求,传统的人工检测方式已经难以满足木材产品的加工生产。在了解木材表面缺陷的分类、缺陷产生原因和木材缺陷表面图像的特征的基础上,对比分析平均值法、最大值法和加权平均值法3种图像灰度化方法效果,并选定加权平均值法对木材缺陷图像进行灰度化预处理。在Matlab 6.5GUI编程框架下实现木材缺陷检测系统,通过选取Isodata聚类迭代法、Otsu最大方差法、最大熵法和Sobel边缘分割法为基础的4种阈值化图像分割方法对木材缺陷特征的分割效果和分割速率进行实验对比分析。实验结果表明,运用Isodata聚类迭代法的图像分割方法能够快速准确分割图像实现木材缺陷检测。