Optimal depth estimation using modified Kalman filter in the presence of non‐Gaussian jitter noise-Reference-Cited by-同舟云学术

Optimal depth estimation using modified Kalman filter in the presence of non‐Gaussian jitter noise

Published:2018-12-23 Issue:3 Volume:82 Page:224-231
ISSN:1059-910X
Container-title:Microscopy Research and Technique
language:en
Short-container-title:Microsc. Res. Tech.

Author:

Jang Hoon‐Seok¹^ORCID,Muhammad Mannan Saeed²^ORCID,Choi Tae‐Sun¹

Affiliation:

1. Signal and Image Processing Lab, School of Mechanical EngineeringGwangju Institute of Science and Technology Gwangju Republic of Korea

2. Mechatronics Systems Design Lab, School of Electronic and Electrical Engineering, College of Information and CommunicationNatural Sciences Campus, Sungkyunkwan University Suwon Republic of Korea

Funder

National Research Foundation of Korea

Publisher

Wiley

Subject

Medical Laboratory Technology,Instrumentation,Histology,Anatomy

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/jemt.23162

Reference20 articles.

1. A heuristic approach for finding best focused shape

2. C. K. Chui G. Chen Kalman filtering with real‐time applications 2017 Springer Berlin Germany 20 32

3. Removal of jitter noise in 3D shape recovery from image focus by using Kalman filter

4. A survey on computing Lévy stable distributions and a new MATLAB toolbox

5. Hierarchical identification for multivariate Hammerstein systems by using the modified Kalman filter

Cited by 17 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Self-Calibrating Dynamic Projection Mapping System for Dynamic, Deformable Surfaces with Jitter Correction and Occlusion Handling;2023 IEEE International Symposium on Mixed and Augmented Reality (ISMAR);2023-10-16

2. A higher performance shape from focus strategy based on unsupervised deep learning for 3D shape reconstruction;Multimedia Tools and Applications;2023-09-28

3. A New High Quality Focus Measurement Operator Based on Nonsubsampled Shearlet Transform for 3D Shape Reconstruction;Mühendislik Bilimleri ve Araştırmaları Dergisi;2023-04-30

4. Acquisition of High-Quality Image by Using Maximum Correntropy Criterion Kalman Filter;2023 International Conference on Electronics, Information, and Communication (ICEIC);2023-02-05

5. Adaptive weighted guided image filtering for depth enhancement in shape-from-focus;Pattern Recognition;2022-11