针对鬼成像的聚合型三维目标匹配滤波

doi:10.12068/j.issn.1005-3026.2023.02.005

东北大学学报（自然科学版） ›› 2023, Vol. 44 ›› Issue (2): 186-191.DOI: 10.12068/j.issn.1005-3026.2023.02.005

针对鬼成像的聚合型三维目标匹配滤波

张顺尧¹，桑爱军¹，宋立军²，王世刚¹

(1. 吉林大学通信工程学院，吉林长春130022； 2. 吉林工程技术师范学院，吉林长春130052)

修回日期:2021-11-08 接受日期:2021-11-08 发布日期:2023-02-27
通讯作者: 张顺尧
作者简介:张顺尧(1998-)，男，吉林省吉林市人，吉林大学硕士研究生；桑爱军(1973-)，女，山东莱州人，吉林大学教授.
基金资助:
吉林省自然科学基金资助项目(20200201295JC); 吉林省科技发展计划国际合作项目(20200801042GH) .

Convergent Three-dimensional Target Matching Filtering for Ghost Imaging

ZHANG Shun-yao¹， SANG Ai-jun¹， SONG Li-jun²， WANG Shi-gang¹

1. College of Telecommunication Engineering， Jilin University， Changchun 130022， China； 2. Jilin Engineering Normal University，Changchun 130052， China.

Revised:2021-11-08 Accepted:2021-11-08 Published:2023-02-27
Contact: SANG Ai-jun
About author:-
Supported by:
-

摘要/Abstract

摘要： 针对视频鬼成像重构采样次数少、清晰度低、噪声大等问题，提出了一种聚合型三维目标匹配滤波方法.首先将鬼成像视频中的每一帧图像与待优化帧进行块匹配，将块匹配后的每一帧图像按照时序排序组成三维矩阵.根据每一帧图片的帧序，赋予其不同的帧权值，对矩阵进行三维加权中值滤波.经过运动目标的欠采样仿真与实验对比后，结果表明本文方法相较于现存的三维滤波方法，不仅噪声系数更低、结构保留程度更好，同时获到了更好的主观评价(Brisque).对比原始实验恢复图，本文方法在噪声系数和边缘模糊度上分别下降34.25%，6.86%，在Brisque主观评价上提升了45.84%.

关键词: 计算鬼成像；块匹配算法；中值滤波；三维加权滤波；视频滤波

Abstract: Aiming at the problems of low sampling frequency， low resolution and high noise in video ghost imaging reconstruction， an aggregated three-dimensional target matching filtering method was proposed. Firstly， each frame of the ghost imaging video is block-matched with the frame to be optimized and each frame of images after block matching is arranged to form a three-dimensional matrix according to the time sequence. According to the frame sequence of each frame picture， different frame weights are assigned to it. Then the matrix is subjected to three-dimensional weighted median filtering. After under-sampling simulation and experimental comparison of moving targets， the method proposed has not only lower noise figure and better structure retention， but also a better subjective evaluation compared with the existing three-dimensional filtering methods. Compared with the original experimental restoration graph， the proposed method reduces the noise figure and edge ambiguity by 34.25% and 6.86%， respectively， and the Brisque subjective evaluation was improved by 45.84%.

Key words: computational ghost imaging; block matching algorithm; median filter; three-dimensional weighted filtering; video filtering

中图分类号:

TN919.81

张顺尧，桑爱军，宋立军，王世刚. 针对鬼成像的聚合型三维目标匹配滤波[J]. 东北大学学报（自然科学版）, 2023, 44(2): 186-191.

ZHANG Shun-yao， SANG Ai-jun， SONG Li-jun， WANG Shi-gang. Convergent Three-dimensional Target Matching Filtering for Ghost Imaging[J]. Journal of Northeastern University(Natural Science), 2023, 44(2): 186-191.

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针对鬼成像的聚合型三维目标匹配滤波

Convergent Three-dimensional Target Matching Filtering for Ghost Imaging

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