Automated artefacts detection and removal in remote sensing optical imageries
Remote Sensing is the process of gathering information, recording, or observing objects or events from a far away distance, without contacting it physically. Remote sensing has increasingly become more popular due to its applicability in many different fields such as geography and military. However,...
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sg-ntu-dr.10356-1498182023-07-07T18:28:21Z Automated artefacts detection and removal in remote sensing optical imageries Guancia, Dustin Joseph Co LU Yilong School of Electrical and Electronic Engineering EYLU@ntu.edu.sg Engineering::Electrical and electronic engineering::Satellite telecommunication Engineering::Electrical and electronic engineering::Antennas, wave guides, microwaves, radar, radio Remote Sensing is the process of gathering information, recording, or observing objects or events from a far away distance, without contacting it physically. Remote sensing has increasingly become more popular due to its applicability in many different fields such as geography and military. However, the output images of the remote sensors have a poor quality, or sometimes contains artefacts. This will hinder the data processing from the captured images. This project aims to study and develop different methods to detect and remove artefacts in the satellite images. This project also explores the MATLAB Image Processing Toolbox and the corresponding functions to aid with the objective of the project. Several MATLAB image processing functions will be used to produce MATLAB algorithms for artefacts detection, followed by the removal. The different methods will then be compared and analyzed based on their efficiency to carry out the tasks. Bachelor of Engineering (Electrical and Electronic Engineering) 2021-06-08T08:54:42Z 2021-06-08T08:54:42Z 2021 Final Year Project (FYP) Guancia, D. J. C. (2021). Automated artefacts detection and removal in remote sensing optical imageries. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/149818 https://hdl.handle.net/10356/149818 en A3155-201 application/pdf Nanyang Technological University |
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Engineering::Electrical and electronic engineering::Satellite telecommunication Engineering::Electrical and electronic engineering::Antennas, wave guides, microwaves, radar, radio Guancia, Dustin Joseph Co Automated artefacts detection and removal in remote sensing optical imageries |
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Remote Sensing is the process of gathering information, recording, or observing objects or events from a far away distance, without contacting it physically. Remote sensing has increasingly become more popular due to its applicability in many different fields such as geography and military. However, the output images of the remote sensors have a poor quality, or sometimes contains artefacts. This will hinder the data processing from the captured images. This project aims to study and develop different methods to detect and remove artefacts in the satellite images. This project also explores the MATLAB Image Processing Toolbox and the corresponding functions to aid with the objective of the project. Several MATLAB image processing functions will be used to produce MATLAB algorithms for artefacts detection, followed by the removal. The different methods will then be compared and analyzed based on their efficiency to carry out the tasks. |
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LU Yilong |
author_facet |
LU Yilong Guancia, Dustin Joseph Co |
format |
Final Year Project |
author |
Guancia, Dustin Joseph Co |
author_sort |
Guancia, Dustin Joseph Co |
title |
Automated artefacts detection and removal in remote sensing optical imageries |
title_short |
Automated artefacts detection and removal in remote sensing optical imageries |
title_full |
Automated artefacts detection and removal in remote sensing optical imageries |
title_fullStr |
Automated artefacts detection and removal in remote sensing optical imageries |
title_full_unstemmed |
Automated artefacts detection and removal in remote sensing optical imageries |
title_sort |
automated artefacts detection and removal in remote sensing optical imageries |
publisher |
Nanyang Technological University |
publishDate |
2021 |
url |
https://hdl.handle.net/10356/149818 |
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1772826974070243328 |