A Real-Time Frame-Differencing CMOS Imager With ROI Filtering for Data and Power Reduction

This article presents a computational image sensor design based on frame differencing (FD) to reduce output data volume, thereby improving system energy efficiency in Internet of Things (IoT) applications. The proposed design features an 8T-1C pixel with a dynamic source follower (DSF), enabling in-pixel FD for motion detection (MD) without affecting image readout. The sensor integrates a multi-mode operation, offering full image output, data compression (DC), and MD modes. A novel 10-bit two-step current-mode analog-to-digital converter (ADC), featuring a 3-bit flash and a 7-bit single-slope (SS) ADC, is introduced for digitalization. The $64\times 64$ sensor prototype was implemented using a standard 0.18 $\mu $ m CMOS process. Test results demonstrate the effectiveness of the DSF in enhancing FD and reducing noise, leading to higher response linearity. Experimental validation of MD and DC modes shows an average of 10.9% of output data volume compared to full frame, and over high reconstructed image quality. The results demonstrate that the proposed design achieves efficient, on-chip data reduction with low power consumption and enhanced adaptability for real-time applications.