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Swin transformer based siamese network for thermal and optical image registration

Title	Swin transformer based siamese network for thermal and optical image registration
Author	Elsaeidy, M., Yağmur, İsmail Can, Ateş, Hasan Fehmi, Güntürk, B. K.
Publication Date:	2023
Publication Place	- IEEE
Subject	Keypoint, Multi-modal image registration, Transformer network
Type	Document
Language	English
Digital	Yes
Manuscript	No
Library:	Özyeğin University
Library Asset ID	979-835034355-7
Record ID	f35f8154-40ad-4cab-b26c-2f743dcdc550
Library Location	Computer Science
Date	2023
Sample Text	The process of multi-modal image registration is fundamental in remote sensing and visual navigation applications. However, existing image registration methods that are designed for single modality images do not provide satisfactory results when applied to multi-modal image registration. In this research, our objective is to achieve highly accurate alignment of both infrared and optical (visible range) images. To accomplish this goal, we explore the effectiveness of the Swin Transformer encoder and cosine loss in enhancing the keypoint-based image registration process. Simulation results show the improvement achieved in multi-modal registration by using a transformer based Siamese network.
DOI	10.1109/SIU59756.2023.10224035

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Özyeğin University

Swin transformer based siamese network for thermal and optical image registration

Author Elsaeidy, M., Yağmur, İsmail Can, Ateş, Hasan Fehmi, Güntürk, B. K.

Publication Date 2023

Publication Place - IEEE

Subject Keypoint, Multi-modal image registration, Transformer network

Type Document

Language English

Digital Yes

Manuscript No

Library Özyeğin University

Library Asset ID 979-835034355-7

Record ID f35f8154-40ad-4cab-b26c-2f743dcdc550

Library Location Computer Science

Date 2023

Sample Text The process of multi-modal image registration is fundamental in remote sensing and visual navigation applications. However, existing image registration methods that are designed for single modality images do not provide satisfactory results when applied to multi-modal image registration. In this research, our objective is to achieve highly accurate alignment of both infrared and optical (visible range) images. To accomplish this goal, we explore the effectiveness of the Swin Transformer encoder and cosine loss in enhancing the keypoint-based image registration process. Simulation results show the improvement achieved in multi-modal registration by using a transformer based Siamese network.

DOI 10.1109/SIU59756.2023.10224035