APSIPA Transactions on Signal and Information Processing > Vol 11 > Issue 1

An Overview on the Generation and Detection of Synthetic and Manipulated Satellite Images

Lydia Abady, Dipartimento di Ingegneria Dell’Informazione e Scienze Matematiche, Universitá di Siena, Italy, abady@diism.unisi.it , Edoardo Daniele Cannas, Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Italy, Paolo Bestagini, Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Italy, Benedetta Tondi, Dipartimento di Ingegneria Dell’Informazione e Scienze Matematiche, Universitá di Siena, Italy, Stefano Tubaro, Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Italy, Mauro Barni, Dipartimento di Ingegneria Dell’Informazione e Scienze Matematiche, Universitá di Siena, Italy
 
Suggested Citation
Lydia Abady, Edoardo Daniele Cannas, Paolo Bestagini, Benedetta Tondi, Stefano Tubaro and Mauro Barni (2022), "An Overview on the Generation and Detection of Synthetic and Manipulated Satellite Images", APSIPA Transactions on Signal and Information Processing: Vol. 11: No. 1, e36. http://dx.doi.org/10.1561/116.00000142

Publication Date: 24 Nov 2022
© 2022 L. Abady, E. D. Cannas, P. Bestagini, B. Tondi, S. Tubaro and M. Barni
 
Subjects
 
Keywords
Remote sensinggenerative modelsfake image detectionsegmentation
 

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This is published under the terms of CC BY-NC.

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In this article:
Introduction 
Remote Sensing Imagery 
Generative Models 
Satellite Forgeries via Deep Neural Networks 
Beyond Forgeries 
Forgery Detection and Localization 
Discussion and Future Challenges 
Conclusion 
References 

Abstract

Due to the reduction of technological costs and the increase of satellite launches, satellite images are becoming more popular and easier to obtain. Besides serving benevolent purposes, satellite data can also be used for malicious reasons such as misinformation. As a matter of fact, satellite images can be easily manipulated relying on general image editing tools. Moreover, with the surge of Deep Neural Networks (DNNs) that can generate realistic synthetic imagery belonging to various domains, additional threats related to the diffusion of synthetically generated satellite images are emerging. In this paper, we review the State of the Art (SOTA) on the generation and manipulation of satellite images. In particular, we focus on both the generation of synthetic satellite imagery from scratch, and the semantic manipulation of satellite images by means of image-transfer technologies, including the transformation of images obtained from one type of sensor to another one. We also describe forensic detection techniques that have been researched so far to classify and detect synthetic image forgeries. While we focus mostly on forensic techniques explicitly tailored to the detection of AI-generated synthetic contents, we also review some methods designed for general splicing detection, which can in principle also be used to spot AI manipulate images.

DOI:10.1561/116.00000142