CMOS影像传感器的信噪比分析

本文使用像素密度归一化方法,对比分析了市场主流厂家生产的多系列数码相机产品中CMOS影像传感器的控噪水平。结论是：2009年尼康推出的采用瑞萨代工传感器的D3S在噪声控制方面达到了顶峰。之后的4年, CMOS控噪技术的发展似乎遇到了瓶颈,各厂商转而在提升像素密度方面大力进取。     

CMOS 图像传感器的发展现状

目的　了解当前 CMOS图像传感器的发展状况 .方法　详细介绍了图像传感器的历史背景、发展现状、像素单元的结构、工作原理以及 CMOS图像传感器芯片的整体结构 ,并比较了 CMOS图像传感器和 CCD图像传感器的优、缺点 .结果　指出了 CMOS图像传感器发展趋势 .结论　 CMOS图像传感器具有美好的发展前途     

CMOS图像传感器的消噪技术

目的　介绍 CMOS图像传感器的消噪技术 .方法　比较了 CMOS图像传感器与CCD图像传感器的优缺点 ,分析了 CMOS图像传感器消噪技术的方法 ,介绍了其研制现状及发展趋势 .结果　目前采用的消噪技术有效地降低了噪声 ,提高了信噪比 .结论　预见了CMOS图像传感器消噪技术的发展趋势 .     

Development of Low Power Cryogenic Readout Integrated Circuits Using Fully-Depleted-Silicon-on-Insulator CMOS Technology for Far-Infrared Image Sensors

We are developing low power cryogenic readout integrated circuits (ROICs) for large format far-infrared image sensors using fully-depleted-silicon-on-insulator (FD-SOI) CMOS technology. We have evaluated the characteristics of MOS FETs fabricated by the FD-SOI CMOS technology and have found that both p-ch and n-ch FETs show good static performance below the liquid helium temperature, where n-ch FETs fabricated by conventional bulk-CMOS technology usually suffer from anomalous behaviors such as kink and hysteresis. We have also designed and fabricated an operational amplifier (OP-AMP) and have successfully demonstrated that the OP-AMP works at the liquid helium temperature with an open loop gain of 7000 and a power consumption of 1.3 μW. The noise is dominated by mainly 1/f and has a value of at?1?Hz.     

Transient Response and Fixed Pattern Noise in Logarithmic CMOS Image Sensors

Logarithmic CMOS image sensors are appealing for their high-contrast and high-speed response but they require postprocessing to achieve high-quality images. Previously published work has explained the fixed pattern noise (FPN) in these image sensors using a steady-state analysis. This paper explains how the transient response of the readout circuit may also contribute to FPN. Thus, the performance of these CMOS cameras may be optimized with a proper understanding of the transient response, which is explained here through modeling and simulation with some experimental validation. In particular, the gain variation of a logarithmic camera is shown to be caused primarily by premature digitization. As logarithmic and linear active pixel sensors use similar circuits, some results in this paper, e.g., an analysis of readout capacitance, apply equally to the latter.     

Temperature Dependence of Fixed Pattern Noise in Logarithmic CMOS Image Sensors

This paper presents a model that is then simplified to explain the temperature dependence of fixed pattern noise (FPN) in logarithmic complementary metal–oxide semiconductor (CMOS) image sensors. The simplified model uses the average dark response of pixels, which depends only on temperature, to help predict the FPN in the light response, which depends on temperature and illuminance. To calibrate a logarithmic camera, one requires images that are taken at different temperatures and illuminances, which need not be measured, of a uniform stimulus. To correct the FPN in an arbitrary image, one uses the simplified model parameters, which are estimated once by the calibration, and the average dark response, which is infrequently determined by closing the aperture. Through simulation (using mismatch data from a real CMOS process) and experiment (using a commercial logarithmic camera), an improvement is shown in the residual error per image, after calibration, when the proposed method is compared with a related method in the literature that does not account for temperature dependence.      

CCD和CMOS图像传感器的异同剖析

不管是在静止图像还是在运动图像领域,所采用的图像传感器不外乎CCD和CMOS两种,文章首先介绍了两种传感器的工艺结构和工作特点,然后给出了二者在制造工艺及性能参数等方面的主要差异,其中对两种传感器光敏单元的作用和能否实现片上系统方面作了重点强调。     

Clusters of Spikes in CMOS Image Sensors Irradiated by Protons and Neutrons

The distribution of pixels with high-value dark current in CMOS image sensors irradiated by protons with the energy of 1000 MeV and neutrons with a continuous spectrum simulating the energy spectrum of atmospheric neutrons is explored. Data on generation of spike clusters in the irradiated sensors and the exposure time influence on the cluster parameters are obtained.     

Embedding Image Through Generated Intermediate Medium Using Deep Convolutional Generative Adversarial Network

Deep neural network has proven to be very effective in computer vision fields. Deep convolutional network can learn the most suitable features of certain images without specific measure functions and outperform lots of traditional image processing methods. Generative adversarial network (GAN) is becoming one of the highlights among these deep neural networks. GAN is capable of generating realistic images which are imperceptible to the human vision system so that the generated images can be directly used as intermediate medium for many tasks. One promising application of using GAN generated images would be image concealing which requires the embedded image looks like not being tampered to human vision system and also undetectable to most analyzers. Texture synthesizing has drawn lots of attention in computer vision field and is used for image concealing in steganography and watermark. The traditional methods which use synthesized textures for information hiding mainly select features and mathematic functions by human metrics and usually have a low embedding rate. This paper takes advantage of the generative network and proposes an approach for synthesizing complex texture-like image of arbitrary size using a modified deep convolutional generative adversarial network (DCGAN), and then demonstrates the feasibility of embedding another image inside the generated texture while the difference between the two images is nearly invisible to the human eyes.     

A CMOS Integrable Oscillator-Based Front End for High-Dynamic-Range Resistive Sensors

A new oscillating circuit is proposed to estimate the resistance and parallel parasitic capacitance of resistive chemical sensors. The circuit is able to reveal the resistance in a wide range (from tens of kiloohms to more than 100 $hbox{G}Omega$) due to the adopted resistance-to-time technique. In addition, the parallel capacitance (up to 50 pF) can be estimated. The circuit, which does not need any initial calibration, is very simple and compact and is suitable to be integrated with a standard CMOS technology to obtain a low-cost and low-power device for a sensor array interface. Different kinds of postlayout simulations concerning the CMOS integrated implementation have been conducted. Experimental results obtained using a discrete prototype board, both on passive components and on real sensors (metal–oxide sensors), have shown good linearity and reduced percentage error with respect to the theoretical expectations.      

Plasmonic Color Filters for CMOS Image Sensor Applications

We report on the optical properties of plasmonic hole arrays as they apply to requirements for plasmonic color filters designed for state-of-the-art Si CMOS image sensors. The hole arrays are composed of hexagonally packed subwavelength sized holes on a 150 nm Al film designed to operate at the primary colors of red, green, and blue. Hole array plasmonic filters show peak transmission in the 40-50% range for large (>5 × 5 μm(2)) size filters and maintain their filtering function for pixel sizes as small as ～1 × 1 μm(2), albeit at a cost in transmission efficiency. Hole array filters are found to robust with respect to spatial crosstalk between pixel within our detection limit and preserve their filtering function in arrays containing random defects. Analysis of hole array filter transmittance and crosstalk suggests that nearest neighbor hole-hole interactions rather than long-range interactions play the dominant role in the transmission properties of plasmonic hole array filters. We verify this via a simple nearest neighbor model that correctly predicts the hole array transmission efficiency as a function of the number of holes.     

Reconfigurable Hybrid CMOS/Nanodevice Circuits for Image Processing

We have analyzed two options of using hybrid CMOS/nanodevice circuits with area-distributed (CMOL) interface for the low-level image processing tasks, on the simplest example of 2-D image convolution with a sizable filter window. The first option is to use digital, DSP-like circuits based on a reconfigurable CMOL fabric, while the second one is based on mixed-signal CMOL circuits with the analog presentation of input and output data and the binary presentation of the filter function. Estimates of the circuit performance have been carried out for the 45-nm CMOS technology and the 4.5-nm nanowire half-pitch, and the power consumption fixed at a manageable, ITRS-specified level. In the digital case, the circuit area per pixel is about 25times25 , and the time necessary for convolving a 10²⁴times10²⁴-pixel, 12-bit-accurate image with a 3232-pixel window function of similar accuracy is close to 25 , much shorter than that estimated for purely CMOS circuits with the same minimum feature size on 45 nm. For a mixed-signal CMOL circuit, the corresponding numbers are much better ( ~1 mum² and 1mus, respectively), but this option requires a very high (~1%) reproducibility of on currents of the necessary crosspoint devices (programmable diodes), which has not yet been reached experimentally.     

微光 CCD 图像传感器驱动电路设计

目的 制作适于ISD029型CCD图像传感器的驱动电路。方法 分析CCD图像传感器的工作原理及特点,设计相应的驱动电路。结果 该电路能有效地驱动CCD图像传感器。结论 实验结果表明：用此驱动电路及图像传感器可以作为相应CCD相机的核心单元。     

一种鲁棒的线纹尺图像刻线提取算法研究

为解决光照不均匀、锈斑、污损等因素造成的钢卷尺图像检测识别不准确问题,提出了一种基于Cabor变换的钢刻线提取方法。通过Cabor变换,使特征方向与特定频率的线条结构被过滤呈现出来,基于这些线条结构计算图像中的线纹尺待检刻线位置,之后通过RANSAC算法拟合刻线的双边缘,从而准确获得刻线中心位置。经实验证明,该算法可以在刻线质量较差的情况下,鲁棒地识别破损和有锈斑的刻线,有效地提高检测准确度和整个测量系统的鲁棒性,具有技术参考价值。     

基于星敏感器的深空探测器姿态解析算法

天文导航方法已经成为深空探测必备的导航方法.为了实现对深空探测器的姿态控制,必须准确知道深空探测器当前时刻的姿态.根据深空探测器机载的两个星敏感器跟踪两颗选定的已知恒星,测量出当前时刻相对初始时刻这两个恒星星光矢量在深空探测器机体坐标系中的角度变化量,通过姿态变换矩阵转换和公式推导,给出了确定深空探测器当前时刻姿态角的解析算法,从而为探测器的姿态控制提供准确的姿态数据.通过仿真结果验证了此方法的正确性和有效性.     

An Improved Deep Fusion CNN for Image Recognition

With the development of Deep Convolutional Neural Networks (DCNNs), the extracted features for image recognition tasks have shifted from low-level features to the high-level semantic features of DCNNs. Previous studies have shown that the deeper the network is, the more abstract the features are. However, the recognition ability of deep features would be limited by insufficient training samples. To address this problem, this paper derives an improved Deep Fusion Convolutional Neural Network (DF-Net) which can make full use of the differences and complementarities during network learning and enhance feature expression under the condition of limited datasets. Specifically, DF-Net organizes two identical subnets to extract features from the input image in parallel, and then a well-designed fusion module is introduced to the deep layer of DF-Net to fuse the subnet’s features in multi-scale. Thus, the more complex mappings are created and the more abundant and accurate fusion features can be extracted to improve recognition accuracy. Furthermore, a corresponding training strategy is also proposed to speed up the convergence and reduce the computation overhead of network training. Finally, DF-Nets based on the well-known ResNet, DenseNet and MobileNetV2 are evaluated on CIFAR100, Stanford Dogs, and UECFOOD-100. Theoretical analysis and experimental results strongly demonstrate that DF-Net enhances the performance of DCNNs and increases the accuracy of image recognition.     

Integrated Heat-Flux Sensors for Harsh Environments Using Thermal-Spray Technology

Heat-flux sensors are widely used in thermal and heat-transfer engineering applications. Commercial heat-flux sensors currently available for harsh environments, however, remain limited due to complications in positioning/attaching the sensor onto the component, the inability to operate at high temperatures, and potentially altering or degrading the engineering device by the physical presence of the sensor. In this paper, heat-flux sensors have been fabricated for the first time entirely by using a thermal-spray technology. The sensors are fabricated directly onto engineering surfaces and consist of five to seven thermocouples arranged electrically in series and thermally in parallel, such that the heat flux is measured normal to the surface, on which the sensor resides. Devices are tested under both steady-state and transient conditions at temperatures up to 100$^circhboxC$. They exhibit a very good linearity between the heat flux and voltage output. Analytical modeling of the steady-state and transient responses is also presented and compared to experimental results. If successful, thermal-spray heat-flux sensors could represent a significant enabling technology for heat-flux sensing at high temperatures, in harsh environments, and in embedded sensor applications.     

精密微小装配中的传感器与测量技术

装配是高性能精密微小器件或产品制造过程中的关键环节,由于零件及其关键结构的尺寸微小,微小装配必然是基于传感器与测量技术的精密装配。在微小零件装配过程中,需要精确测量待装配零件之间的相对位置和姿态的偏差,控制配合零件之间的接触力或接触状态。首先对用于精密微小装配的传感器技术进行了概述;然后结合精密微小装配中的应用需求,对机器视觉、力觉等主要传感器与测量技术进行了综述,并分析了精密测量与装配控制的技术与方法,旨在对精密装配相关的技术开发、装配设备研制提供参考和借鉴。