Jingjing Liu;Yuchen Wang;Bingjun Xiong;Zhipeng Li;Liang Shi;Junhao He
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An 88.96 dB HDR CMOS Image Sensor Modeled on Visual Neuronal Response
This brief proposes a low-voltage low-power high dynamic range (HDR) CMOS image sensor (CIS) with visual neuronal responses (VNR) tailored for IoT applications, especially biomedical scenarios, which demand low power consumption and limited transmission bandwidth. The proposed CIS modeled on the nonlinear compression characteristics of illumination in the visual nervous system to enhance the dynamic range (DR). By employing a dynamic readout of pixel signals and comparing with a reference ramp voltage, the output of the proposed CIS conforms to the Naka-Rushton function, which describes the response features of visual neurons. The proposed CIS adopts a column-parallel architecture to enable simultaneous exposure, readout, and quantization of pixels in each row, combined with several low-power reset circuits to reduce image lag and inter-row crosstalk. A $126\times 64$ HDR CIS with a $6.6~\mu $ m pixel pitch was fabricated using a 180 nm CMOS technology. Measurement results show a DR exceeding 88.96 dB, with a total power consumption of $18.62~\mu $ W at 60 fps and 0.8 V supply.
期刊介绍:
TCAS II publishes brief papers in the field specified by the theory, analysis, design, and practical implementations of circuits, and the application of circuit techniques to systems and to signal processing. Included is the whole spectrum from basic scientific theory to industrial applications. The field of interest covered includes:
Circuits: Analog, Digital and Mixed Signal Circuits and Systems
Nonlinear Circuits and Systems, Integrated Sensors, MEMS and Systems on Chip, Nanoscale Circuits and Systems, Optoelectronic
Circuits and Systems, Power Electronics and Systems
Software for Analog-and-Logic Circuits and Systems
Control aspects of Circuits and Systems.