STEMPix: A Phase-Transition-Material-Based Pixel Sensor for Resolving Edge-Movement Direction

📅 2026-09-03
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🤖 AI Summary
本文提出了一种基于相变材料的像素传感器STEMPix,通过结合时间变化信息与空间边缘信息生成3位局部边缘方向码,以解决图像传感器阵列中的边缘移动方向识别问题。
📝 Abstract
This paper proposes a spatio-temporal edge-movement direction pixel (STEMPix) for generating compact direction-aware edge movement information inside a CMOS-compatible image sensor array. The proposed design targets specialized sensing applications where local boundary movement is more important than full-frame intensity reconstruction. Instead of transferring full multi-bit frames for external processing, STEMPix generates a 3-bit local edge direction code (LEDC) by combining pixel-level temporal change information with neighboring-pixel spatial edge information. We design the architecture using a two-tier organization, where the photodiode layer is separated from the computation layer to preserve light-collection area while accommodating the additional in-array processing circuitry. The proposed circuit is evaluated through HSPICE transient simulations. The estimated implementation achieves a horizontal pitch of 1.73 μm, a vertical pitch of 2.36 μm, and a geometric fill factor of 95.47%. The average active switching energy is 0.465 fJ per LEDC operation across representative edge-movement cases. The proposed STEMPix operation also supports global-shutter capture and dynamic thresholding. These results indicate that STEMPix can provide a compact and scalable front-end representation for edge-movement-aware sensing systems.
Problem

Research questions and friction points this paper is trying to address.

edge-movement direction
CMOS-compatible image sensor
spatio-temporal
local boundary movement
Innovation

Methods, ideas, or system contributions that make the work stand out.

Phase-Transition-Material-Based
Direction-Aware Edge Movement
Local Edge Direction Code (LEDC)
Two-Tier Organization
In-Array Processing
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Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, TN 37996, USA
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