Wide-dynamic-range APS-based silicon retina with brightness constancy.

IEEE transactions on neural networks Pub Date : 2011-09-01 Epub Date: 2011-07-29 DOI:10.1109/TNN.2011.2161591
Kazuhiro Shimonomura, Seiji Kameda, Atsushi Iwata, Tetsuya Yagi
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引用次数: 18

Abstract

A silicon retina is an intelligent vision sensor that can execute real-time image preprocessing by using a parallel analog circuit that mimics the structure of the neuronal circuits in the vertebrate retina. For enhancing the sensor's robustness to changes in illumination in a practical environment, we have designed and fabricated a silicon retina on the basis of a computational model of brightness constancy. The chip has a wide-dynamic-range and shows a constant response against changes in the illumination intensity. The photosensor in the present chip approximates logarithmic illumination-to-voltage transfer characteristics as a result of the application of a time-modulated reset voltage technique. Two types of image processing, namely, Laplacian-Gaussian-like spatial filtering and computing the frame difference, are carried out by using resistive networks and sample/hold circuits in the chip. As a result of these processings, the chip exhibits brightness constancy over a wide range of illumination. The chip is fabricated by using the 0.25- μm complementary metal-oxide semiconductor image sensor technology. The number of pixels is 64 × 64, and the power consumption is 32 mW at the frame rate of 30 fps. We show that our chip not only has a wide-dynamic-range but also shows a constant response to the changes in illumination.

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具有亮度恒定的宽动态范围aps基硅视网膜。
硅视网膜是一种智能视觉传感器,通过使用模拟脊椎动物视网膜神经元电路结构的并行模拟电路,可以执行实时图像预处理。为了提高传感器在实际环境中对光照变化的鲁棒性,我们设计并制作了基于亮度恒定计算模型的硅视网膜。该芯片具有很宽的动态范围,并且对光照强度的变化有恒定的响应。由于时间调制复位电压技术的应用,本芯片中的光敏传感器近似于对数照明到电压的转移特性。利用芯片中的电阻网络和采样/保持电路,实现了类拉普拉斯-高斯空间滤波和帧差计算两种图像处理。作为这些处理的结果,芯片在广泛的照明范围内显示亮度恒定。该芯片采用0.25 μm互补金属氧化物半导体图像传感器技术制作而成。像素数为64 × 64,帧率为30fps时,功耗为32mw。我们的研究表明,我们的芯片不仅具有宽动态范围,而且对光照的变化具有恒定的响应。
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来源期刊
IEEE transactions on neural networks
IEEE transactions on neural networks 工程技术-工程:电子与电气
自引率
0.00%
发文量
2
审稿时长
8.7 months
期刊最新文献
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