In-sensor multilevel image adjustment for high-clarity contour extraction using adjustable synaptic phototransistors

Robotic vision has traditionally relied on high-performance yet resource-intensive computing solutions, which necessitate high-throughput data transmission from vision sensors to remote computing servers, sacrificing energy efficiency and processing speed. A promising solution is data compaction through contour extraction, visualizing only the outlines of objects while eliminating superfluous backgrounds. Here, we introduce an in-sensor multilevel image adjustment method using adjustable synaptic phototransistors, enabling the capture of well-defined images with optimal brightness and contrast suitable for achieving high-clarity contour extraction. This is enabled by emulating dopamine-mediated neuronal excitability regulation mechanisms. Electrostatic gating effect either facilitates or inhibits time-dependent photocurrent accumulation, adjusting photo-responses to varying lighting cond…