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Remote Sensing Image Super-Resolution based on Siamese Networks with Cross Scale Non-Local Similarity for Segmentation of Buildings

Title
Remote Sensing Image Super-Resolution based on Siamese Networks with Cross Scale Non-Local Similarity for Segmentation of Buildings
Alternative Title
건물의 분할 영상을 위해 교차 크기의 비지역적 유사성을 활용하는 샴 네트워크 기반 항공 영상 초해상도 기법
Author(s)
Jaegeun Park
DGIST Authors
Jaegeun ParkJae Youn HwangKyong Hwan Jin
Advisor
황재윤
Co-Advisor(s)
Kyong Hwan Jin
Issued Date
2023
Awarded Date
2023-02-01
Type
Thesis
Description
Cross Scale Non-Local Similarity, Siamese Network, Super Resolution, Remote Sensing, Segmentation, 교차 크기의 비지역적 유사성, 샴 네트워크, 초해상도, 항공 영상, 분할 영상
Table Of Contents
Ⅰ. INTRODUCTION 1
Ⅱ. RELATED WORKS 6
2.1 Image Self-Similarity 6
2.2 Deep Learning-based Super Resolution 7
Ⅲ. METHODS 9
3.1 Overall Network Structure 9
3.2 Siamese Residual Non-local Similarity Module (SRNSM) 13
3.3 Siamese Cross Scale Non-Local Similarity Module (SCSNLS Module) 16
Ⅳ. RESULTS 19
4.1 Experimental Dataset and Evaluation 19
4.2 Training Details 21
4.3 Comparison between previous and SRNSM methods 22
4.4 Super Resolution results on the UCMerced Dataset 23
4.5 Super Resolution Results on the WHU Dataset 28
4.6 Segmentation Results on the WHU Dataset 31
Ⅴ. DISCUSSION 34
Ⅵ. CONCLUSION 40
REFERENCES 42
국문요약문 47
URI
http://hdl.handle.net/20.500.11750/45753

http://dgist.dcollection.net/common/orgView/200000655870
DOI
10.22677/THESIS.200000655870
Degree
Master
Department
Department of Electrical Engineering and Computer Science
Publisher
DGIST
Related Researcher
  • 황재윤 Hwang, Jae Youn
  • Research Interests Multimodal Imaging; High-Frequency Ultrasound Microbeam; Ultrasound Imaging and Analysis; 스마트 헬스케어; Biomedical optical system
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Department of Electrical Engineering and Computer Science Theses Master

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