Image super-resolution reconstruction method and device based on quantum efficiency

By generating an X-ray standing wave field and performing sub-pixel displacement in an X-ray imaging system to obtain the quantum efficiency distribution matrix, the problem of resolution limitation due to focal size is solved, high-precision image super-resolution reconstruction is achieved, and the performance of the X-ray imaging system is improved.

CN122415798APending Publication Date: 2026-07-17ZHONGBEI UNIV

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
ZHONGBEI UNIV
Filing Date
2026-04-27
Publication Date
2026-07-17

AI Technical Summary

Technical Problem

In existing X-ray imaging techniques, the focal size limits the improvement of image resolution, and super-resolution reconstruction methods based on convolutional neural networks rely on large-scale paired datasets that are difficult to obtain, resulting in limited algorithm generalization ability, inability to optimize quantum efficiency, and a lack of physical realism in reconstructed details.

Method used

By generating an X-ray standing wave field and driving it to undergo sub-pixel displacement on the detector, a quantum efficiency distribution matrix is ​​obtained. Based on this matrix, the observed image is reconstructed and fused, eliminating detector response non-uniformity and noise distortion, and realizing subwavelength-level precise optical field excitation and a high-precision system response model.

Benefits of technology

It significantly improves the physical fidelity and spatial resolution of the image, eliminates detector non-uniformity and noise distortion, reconstructs the true incident photon distribution, and generates higher resolution X-ray images.

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Abstract

本发明公开一种基于量子效率的图像超分辨率重建方法及设备,方法包括:获取探测器探测到的各个探测周期对应的标定图像,确定各个像素的各个子区域在各个探测周期对应的接收光子数;基于各个探测周期对应的标定图像及各个像素的各个子区域在各个探测周期对应的接收光子数,确定各个像素的各个子区域的量子效率值,并基于各个像素的各个子区域的量子效率值,确定量子效率分布矩阵;获取每次亚像素位移时探测器探测到的观测图像,得到多帧观测图像;基于量子效率分布矩阵,对各帧观测图像进行重建,得到各帧观测图像对应的光子分布图,基于各帧观测图像对应的光子分布图,对多帧观测图像进行融合,确定超分辨率图像。
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