Reducing crosstalk of a multi-plane holographic display by the time-multiplexing stochastic gradient descent

串扰 随机梯度下降算法 全息术 计算机科学 多路复用 全息显示器 光学 基点 最速下降法 梯度下降 算法 人工智能 物理 数学优化 人工神经网络 电信 数学
作者
Zi Wang,Tao Chen,Qiyang Chen,Kefeng Tu,Qibin Feng,Guo‐Jiao Lv,Anting Wang,Hai Ming
出处
期刊:Optics Express [The Optical Society]
卷期号:31 (5): 7413-7413 被引量:10
标识
DOI:10.1364/oe.483590
摘要

Multi-plane reconstruction is essential for realizing a holographic three-dimensional (3D) display. One fundamental issue in conventional multi-plane Gerchberg-Saxton (GS) algorithm is the inter-plane crosstalk, mainly caused by the neglect of other planes’ interference in the process of amplitude replacement at each object plane. In this paper, we proposed the time-multiplexing stochastic gradient descent (TM-SGD) optimization algorithm to reduce the multi-plane reconstruction crosstalk. First, the global optimization feature of stochastic gradient descent (SGD) was utilized to reduce the inter-plane crosstalk. However, the crosstalk optimization effect would degrade as the number of object planes increases, due to the imbalance between input and output information. Thus, we further introduced the time-multiplexing strategy into both the iteration and reconstruction process of multi-plane SGD to increase input information. In TM-SGD, multiple sub-holograms are obtained through multi-loop iteration and then sequentially refreshed on spatial light modulator (SLM). The optimization condition between the holograms and the object planes converts from one-to-many to many-to-many, improving the optimization of inter-plane crosstalk. During the persistence of vision, multiple sub-hologram jointly reconstruct the crosstalk-free multi-plane images. Through simulation and experiment, we confirmed that TM-SGD could effectively reduce the inter-plane crosstalk and improve image quality.The proposed TM-SGD-based holographic display has wide applications in tomographic 3D visualization for biology, medical science, and engineering design, which need to reconstruct multiple independent tomographic images without inter-plane crosstalk.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
krinnme完成签到,获得积分20
2秒前
呗呗兔关注了科研通微信公众号
2秒前
一味地丶逞强完成签到,获得积分10
3秒前
3秒前
松111发布了新的文献求助10
4秒前
4秒前
123发布了新的文献求助10
5秒前
Alioth完成签到,获得积分10
5秒前
柚一发布了新的文献求助10
7秒前
依依发布了新的文献求助10
8秒前
浮游应助科研通管家采纳,获得10
8秒前
Hello应助科研通管家采纳,获得10
9秒前
NexusExplorer应助科研通管家采纳,获得10
9秒前
9秒前
JamesPei应助科研通管家采纳,获得10
9秒前
orixero应助科研通管家采纳,获得10
9秒前
隐形曼青应助科研通管家采纳,获得10
9秒前
Raven应助科研通管家采纳,获得10
9秒前
CipherSage应助科研通管家采纳,获得10
9秒前
浮游应助科研通管家采纳,获得10
9秒前
Owen应助科研通管家采纳,获得10
9秒前
研友_VZG7GZ应助科研通管家采纳,获得10
9秒前
9秒前
9秒前
9秒前
9秒前
小铭同学完成签到,获得积分10
10秒前
11秒前
12秒前
14秒前
一笑而过完成签到 ,获得积分10
14秒前
naturehome发布了新的文献求助10
15秒前
张嘎嘎发布了新的文献求助10
15秒前
xhj666完成签到,获得积分10
17秒前
豆觉子发布了新的文献求助10
17秒前
可靠冰棍发布了新的文献求助30
18秒前
乐乐应助krinnme采纳,获得10
19秒前
Zhao发布了新的文献求助30
21秒前
木子完成签到,获得积分20
23秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
HIGH DYNAMIC RANGE CMOS IMAGE SENSORS FOR LOW LIGHT APPLICATIONS 1500
Constitutional and Administrative Law 1000
The Social Work Ethics Casebook: Cases and Commentary (revised 2nd ed.). Frederic G. Reamer 800
Corrosion and corrosion control 500
Die Fliegen der Palaearktischen Region. Familie 64 g: Larvaevorinae (Tachininae). 1975 500
The Experimental Biology of Bryophytes 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5373754
求助须知:如何正确求助?哪些是违规求助? 4499770
关于积分的说明 14007232
捐赠科研通 4406707
什么是DOI,文献DOI怎么找? 2420672
邀请新用户注册赠送积分活动 1413421
关于科研通互助平台的介绍 1389992