English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The image forgery process can be simply defined as inserting some objects, with different sizes, in order to vanish some structures and/or scenes. Satellite images can be forged in many ways, such as copy-paste, copy-move and splicing processes. Recent approaches present a generative adversarial network (GAN) as an effective method for identifying the presence of spliced forgeries and identifying their locations with higher detection accuracy of large- and medium-sized forgeries. However, such recent approaches clearly show limited detection accuracy of small-sized forgeries. Accordingly, the localization step of such small-sized forgeries is negatively impacted. In this paper, two different approaches, for detection and localization of small-sized forgeries in satellite images, are proposed. The first approach is inspired from a recently presented GAN-based approach and is modified to an enhanced version. The experimental results manifest that the detection accuracy of the first proposed approach in noticeably increased to 86% compared to his inspiring one with 79% with respect to the small-sized forgeries. Whereas, the second proposed approach uses a different design of a CNN-based discriminator to significantly enhance the detection accuracy to 94%, using the same dataset obtained from NASA and US Geological Survey (USGS) for validation and testing. Furthermore, the results show a comparable detection accuracy in case of large- and medium-sized forgeries using the two proposed approaches compared to the competing ones.

Detection and localization enhancement for satellite images with small forgeries using modified GAN-based CNN structure