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Time domain CMOS image sensor: From photodetection to on-chip image processing.

机译:时域CMOS图像传感器:从光电检测到片上图像处理。

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摘要

The last decade has witnessed significant technological advancement of CMOS image sensors. CMOS imagers are undoubtedly gaining more territory when compared to their CCD counterparts. This is mainly due to their inherent advantages of low power, low cost and more importantly their ability to integrate image capture together with on-chip image processing. Deep sub-micron technologies have contributed significantly to paving the way to novel on-chip processing. The concept of "camera-on-a-chip" has already been introduced in the 90's and new development has seen more complex image processing. The recent emergence of new applications in the area of wireless video sensor network and ultra low power biomedical applications have created new design challenges and frontiers requiring extensive research work. In such applications, it is often required to capture a large amount of data and process them in real-time while the hardware is constrained to take little physical space and to consume little power. This is only possible using custom single chip solutions integrating image sensor and hardware-friendly image processing algorithms.; In a conventional CMOS imager, images are read-out using a clock, which switches the multiplexer from one sensor to another, reading a voltage value from each and every sensor after a fixed integration interval. Images are therefore produced by sequentially scanning the array using column and row scanners. Once the image is captured further image processing is performed by first buffering the entire frame before processing each frame sequentially. Conventional voltage mode scanning and sequential frame processing will soon fall short of meeting aggressive low power and high dynamic range requirements coupled with higher resolution and frame rate imagers. Therefore new approaches are required to overcome these limitations.; In this thesis, we explore new alternative ways to perform image capture and image processing using new encoding techniques. In contrast to conventional voltage mode encoding, we propose to perform image capture and image processing using time-domain encoding inherently featuring wider dynamic range and immunity against continuous reduction of the supply voltage in deep submicron technologies. The thesis will explore both spiking and time-to-first spike (TFS) pixel architecture. The performance of time domain digital pixel sensor will be compared with arbitrated time-to-first spike pixel and potential scaling in deep submicron technologies is also studied. A number of novel design concepts such as fair, high radix and pipelined arbitration are introduced in order to overcome the limitation of arbitrated image sensor array.; This work is further extended to show how a number of complex image processing operations can greatly benefit from time encoding. The inherent ordering property of the pixels' brightness at the output bus of the arbitrated TFS is exploited in order to significantly simplify the VLSI implementation of histogram equalization processing. A second case study of image processing is illustrated in image compression processing using an adaptive quantization scheme based on boundary adaptation procedure followed by an on-line quadrant tree decomposition processing. The image sensor chip together with the on-chip image compression processor have been implemented using 0.35mum CMOS technology and operates at 3.3V. Simulation and experimental results show compression figures corresponding to 0.6-0.8 Bit-Per-Pixel, while maintaining reasonable PSNR levels and very low operating power consumption.; The thesis described the design of a very promising CMOS image sensor with built-in time-based image processing capabilities. It also raises the need for addressing various new challenges such as timing errors at very high illumination levels, efficient external interfacing circuitry as well as improving the image quality in time based encoding. Resolving such issues will undoubtedly
机译:过去十年见证了CMOS图像传感器的重大技术进步。与CCD相比,CMOS成像器无疑获得了更多的领域。这主要是由于其固有的低功耗,低成本优势,更重要的是它们具有将图像捕获与片上图像处理集成在一起的能力。深亚微米技术为新型片上处理铺平了道路。 “片上相机”的概念已经在90年代引入,并且新的发展已经看到了更复杂的图像处理。无线视频传感器网络领域中的新应用程序和超低功耗生物医学应用程序的最新出现,带来了新的设计挑战,需要进行大量研究工作的前沿领域。在这样的应用中,通常需要捕获大量数据并实时处理它们,同时硬件被限制为占用很少的物理空间和消耗很少的功率。只有使用集成了图像传感器和硬件友好的图像处理算法的定制单芯片解决方案才有可能。在传统的CMOS成像器中,使用时钟读取图像,该时钟将多路复用器从一个传感器切换到另一个传感器,并在固定的积分间隔后从每个传感器读取电压值。因此,通过使用列和行扫描器顺序扫描阵列来产生图像。一旦捕获到图像,则在顺序处理每个帧之前先缓冲整个帧,然后执行进一步的图像处理。传统的电压模式扫描和顺序帧处理将很快无法满足苛刻的低功耗和高动态范围要求,并具有更高的分辨率和帧速率成像器。因此,需要新的方法来克服这些限制。在本文中,我们探索了使用新的编码技术执行图像捕获和图像处理的新方法。与传统的电压模式编码相比,我们建议使用时域编码来执行图像捕获和图像处理,其固有的特点是动态范围更广,并且在深亚微米技术中具有连续降低电源电压的能力。本文将探讨尖峰和第一时间尖峰(TFS)像素体系结构。时域数字像素传感器的性能将与仲裁的第一时间尖峰像素进行比较,并且还研究了深亚微米技术中的潜在缩放。为了克服仲裁图像传感器阵列的局限性,引入了许多新颖的设计概念,例如公平,高基数和流水线仲裁。进一步扩展了这项工作,以显示许多复杂的图像处理操作如何从时间编码中大大受益。为了显着简化直方图均衡处理的VLSI实现,利用了仲裁TFS输出总线上像素亮度的固有排序特性。在图像压缩处理中使用基于边界自适应过程的自适应量化方案,然后进行在线象限树分解处理,说明了图像处理的第二个案例研究。图像传感器芯片与片上图像压缩处理器一起使用0.35μmCMOS技术实现,并在3.3V电压下工作。仿真和实验结果表明,压缩数字对应于0.6-0.8每像素像素,同时保持了合理的PSNR水平和非常低的工作功耗。本文描述了具有内置基于时间的图像处理功能的非常有前途的CMOS图像传感器的设计。它还提出了解决各种新挑战的需求,例如在非常高的照明水平下的定时误差,有效的外部接口电路以及在基于时间的编码中提高图像质量。解决此类问题无疑将

著录项

  • 作者

    Chen, Shoushun.;

  • 作者单位

    Hong Kong University of Science and Technology (People's Republic of China).;

  • 授予单位 Hong Kong University of Science and Technology (People's Republic of China).;
  • 学科 Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 2007
  • 页码 145 p.
  • 总页数 145
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 无线电电子学、电信技术;
  • 关键词

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