Differential Image Sensor With Decoupled Static and Dynamic Outputs

Acquiring and processing full-motion details in machine vision typically consumes a substantial amount of energy. In contrast, a hierarchical processing architecture, combining a low-power standby front end with an on-demand activated back end, provides an optimized energy-performance tradeoff. To achieve this, the complete acquisition and decoupling of static (brightness) and dynamic (amplitude and polarity) output at the sensory level are essential for activating on-demand vision function. Here, we report a differential image sensor (DIS) that leverages differential photodiodes with decoupled differential and tunneling modes. These modes can be read out via conventional ROICs, paving the way for the up-scaled integration (e.g., 640 × 512). With on-demand activated dynamic and static modes, the DIS implements a hierarchical motion-processing pipeline—from sparse motion detection to optical flow and depth analysis. This work provides a power-efficient and scalable strategy for advancing vision-based AIoT applications.