多光谱图像
像素
红外线的
光伏系统
材料科学
高光谱成像
图像分辨率
计算机科学
光电子学
遥感
图像传感器
宽带
多光谱模式识别
量子点
光学
光谱带
光子学
可见光谱
异质结
近红外光谱
时间分辨率
分辨率(逻辑)
光谱分辨率
高分辨率
作者
Wanqing Li,Cheng Bi,Min He,Xiaolong Zheng,Yuning Luo,Yimei Tan,Chenxi Liu,Salihuojia Talanti,Yanfei Liu,Ge Mu,Qun Hao,Kangkang Weng,Xin Tang
标识
DOI:10.1002/advs.202519991
摘要
ABSTRACT Visible to short‐wave infrared multispectral imaging is gaining significant attention across various fields, including agriculture, security, and medical diagnostics. Traditional multispectral imaging systems often rely on separate sensors for different spectral bands, leading to complex optical alignment and irreversible resolution loss. Here, we present hardware‐algorithm co‐designed architecture to achieve multispectral super‐resolution imaging. Specifically, we demonstrate a monolithic quad‐spectral photovoltaic imaging platform featuring a resolution of 640 × 512 pixels with <1% dead pixels per channel. The system achieves broadband spectral integration from visible to short‐wave infrared (350–2350 nm) by combining an all‐polymer bulk heterojunction with colloidal quantum dots within a single CMOS‐compatible architecture. The compatibility of all‐polymer bulk heterojunction with direct photopatterning allows for precise patterning and high‐density integration, enabling the devices to operate efficiently in photovoltage mode. To address resolution degradation inherent in planar‐integrated spectral sensing architectures, we applied a super‐resolution reconstruction method, restoring images to a resolution of 640 × 512. The demonstrated capability to simultaneously capture and process multispectral data paves the way for CMOS integration, multispectral Imagers, organic photodetector, super‐resolution reconstruction applications in diverse fields, from precision agriculture to medical diagnostics and beyond.
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