Manipulation Detection in Satellite Images Using Vision Transformer

Janos Horvath, Sriram Baireddy, Hanxiang Hao, Daniel Mas Montserrat, Edward J. Delp; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2021, pp. 1032-1041

Abstract

A growing number of commercial satellite companies provide easily accessible satellite imagery. Overhead imagery is used by numerous industries including agriculture, forestry, natural disaster analysis, and meteorology. Satellite images, just as any other images, can be tampered with image manipulation tools. Manipulation detection methods created for images captured by "consumer cameras" tend to fail when used on satellite images due to the differences in image sensors, image acquisition, and processing. In this paper we propose an unsupervised technique that uses a Vision Transformer to detect spliced areas within satellite images. We introduce a new dataset which includes manipulated satellite images that contain spliced objects. We show that our proposed approach performs better than existing unsupervised splicing detection techniques.

Related Material

[pdf] [arXiv]
[bibtex]
@InProceedings{Horvath_2021_CVPR, author = {Horvath, Janos and Baireddy, Sriram and Hao, Hanxiang and Montserrat, Daniel Mas and Delp, Edward J.}, title = {Manipulation Detection in Satellite Images Using Vision Transformer}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2021}, pages = {1032-1041} }