A 0.5V Real-Time Computational CMOS Image Sensor with Programmable Kernel for Always-On Feature Extraction

This paper presents a 0.5V computational CMOS image sensor (C2IS) with array-parallel computing capability for always-on feature extraction. By applying the developed pulsed-width modulation (PWM) pixel and switch-current integration (SCI), the in-sensor 8-directional matrix-parallel multiply-accumulate (MAC) operation is realized. Moreover, the analog-domain convolution-on-readout (COR) operation, the programmable $3\mathrm{x}3$ kernel with $\pm 3$ -bit weights, and the tunable-resolution column-parallel ADC (1b to $8\mathrm{b}$ ) are implemented to achieve the real-time feature extraction without use of additional memory. The $\mathrm{C}^{2}\mathrm{IS}$ prototype has been fabricated and verified to demonstrate the raw and feature images at $480\mathrm{fps}$ with a power consumption of 77/91 $(\mathrm{uW}$ and the resultant $\mathrm{FoM}$ of 9.8/11.6 (pJ/pix/frame), respectively.