红外与毫米波学报2026，Vol.45Issue(1)：148-156,9.DOI:10.11972/j.issn.1001-9014.2026.01.016
用于PbS量子点焦平面探测器图像校正的多注意力机制U-Net神经网络
A multi-attention mechanism U-Net neural network for image correction of PbS quantum dot focal plane detectors
摘要
Abstract
Near-infrared image sensors are widely used in fields such as material identification,machine vision,and autonomous driving.Lead sulfide colloidal quantum dot-based infrared photodiodes can be integrated with sil-icon-based readout circuits in a single step.Based on this,we propose a photodiode based on an n-i-p structure,which removes the buffer layer and further simplifies the manufacturing process of quantum dot image sensors,thus reducing manufacturing costs.Additionally,for the noise complexity in quantum dot image sensors when capturing images,traditional denoising and non-uniformity methods often do not achieve optimal denoising re-sults.For the noise and stripe-type non-uniformity commonly encountered in infrared quantum dot detector imag-es,a network architecture has been developed that incorporates multiple key modules.This network combines channel attention and spatial attention mechanisms,dynamically adjusting the importance of feature maps to en-hance the ability to distinguish between noise and details.Meanwhile,the residual dense feature fusion module further improves the network's ability to process complex image structures through hierarchical feature extraction and fusion.Furthermore,the pyramid pooling module effectively captures information at different scales,improv-ing the network's multi-scale feature representation ability.Through the collaborative effect of these modules,the network can better handle various mixed noise and image non-uniformity issues.Experimental results show that it outperforms the traditional U-Net network in denoising and image correction tasks.关键词
硫化铅量子点焦平面探测器/卷积神经网络/图像去噪/U-NetKey words
PbS quantum dot focal plane detector/convolutional neural networks/image denoising/U-Net引用本文复制引用
王瀚霆,黄张成,褚君浩,沈宏,王建禄,狄云翔,齐星宇,沙英哲,王亚辉,叶凌枫,唐唯译,巴坤,王旭东..用于PbS量子点焦平面探测器图像校正的多注意力机制U-Net神经网络[J].红外与毫米波学报,2026,45(1):148-156,9.基金项目
Supported by the National key research and development program in the 14th five year plan 2021YFA1200700),the National Natural Sci-ence Foundation of China(62535018,62431025,62561160113),the Natural Science Foundation of Shanghai(23ZR1473400). （62535018,62431025,62561160113）
