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首页> 外文期刊>Very Large Scale Integration (VLSI) Systems, IEEE Transactions on >A CMOS Image Sensor With On-Chip Image Compression Based on Predictive Boundary Adaptation and Memoryless QTD Algorithm
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A CMOS Image Sensor With On-Chip Image Compression Based on Predictive Boundary Adaptation and Memoryless QTD Algorithm

机译:基于预测边界自适应和无记忆QTD算法的片上图像压缩CMOS图像传感器

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This paper presents the architecture, algorithm, and VLSI hardware of image acquisition, storage, and compression on a single-chip CMOS image sensor. The image array is based on time domain digital pixel sensor technology equipped with nondestructive storage capability using 8-bit Static-RAM device embedded at the pixel level. The pixel-level memory is used to store the uncompressed illumination data during the integration mode as well as the compressed illumination data obtained after the compression stage. An adaptive quantization scheme based on fast boundary adaptation rule (FBAR) and differential pulse code modulation (DPCM) procedure followed by an online, least storage quadrant tree decomposition (QTD) processing is proposed enabling a robust and compact image compression processor. A prototype chip including 64 $times$ 64 pixels, read-out and control circuitry as well as an on-chip compression processor was implemented in 0.35 $mu$m CMOS technology with a silicon area of 3.2 $times, {hbox {3.0 mm}}^{2}$ and an overall power of 17 mW. Simulation and measurements results show compression figures corresponding to 0.6–1 bit-per-pixel (BPP), while maintaining reasonable peak signal-to-noise ratio levels.
机译:本文介绍了单芯片CMOS图像传感器上的图像采集,存储和压缩的体系结构,算法和VLSI硬件。图像阵列基于时域数字像素传感器技术,该技术使用嵌入在像素级别的8位Static-RAM器件具备无损存储功能。像素级存储器用于存储积分模式期间的未压缩照明数据以及在压缩阶段之后获得的压缩照明数据。提出了一种基于快速边界自适应规则(FBAR)和差分脉冲编码调制(DPCM)程序,然后进行在线,最小存储象限树分解(QTD)处理的自适应量化方案,从而实现了强大而紧凑的图像压缩处理器。原型芯片采用0.35 µm CMOS技术实现,包括64 x 64像素,读出和控制电路以及片上压缩处理器,硅面积为3.2 x,{hbox {3.0 mm }} ^ {2} $,总功率为17 mW。仿真和测量结果显示,压缩数字对应于0.6–1每像素位(BPP),同时保持合理的峰值信噪比水平。

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