基于对抗神经网络的遥感图像人工碎片检测

IF 1.1 Q4 OPTICS
M. Gashnikov, A. Kuznetsov
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引用次数: 0

摘要

我们研究了由对抗神经网络生成的遥感图像的人工碎片检测算法。我们考虑了一种基于生成对抗神经网络的光谱伪影检测的人工图像检测器,该伪影是由增强分辨率的层引起的。我们使用包含轮廓生成器的对抗神经网络来检测嵌入在自然遥感图像中的人工碎片。我们使用各种类型和分辨率的遥感图像,而替代区域,有些不是单连通的,有不同的大小和形状。实验证明,所研究的光谱神经网络探测器在检测遥感图像的人工碎片方面具有很高的效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detection of artificial fragments embedded in remote sensing images by adversarial neural networks
We investigate algorithms for detecting artificial fragments of remote sensing images generated by adversarial neural networks. We consider a detector of artificial images based on the detection of a spectral artifact of generative-adversarial neural networks that is caused by a layer for enhancing the resolution. We use the detecting algorithm to detect artificial fragments embedded in natural remote sensing images using an adversarial neural network that includes a contour generator. We use remote sensing images of various types and resolutions, whereas the substituted areas, some being not simply connected, have different sizes and shapes. We experimentally prove that the investigated spectral neural network detector has high efficiency in detecting artificial fragments of remote sensing images.
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来源期刊
Computer Optics
Computer Optics OPTICS-
CiteScore
4.20
自引率
10.00%
发文量
73
审稿时长
9 weeks
期刊介绍: The journal is intended for researchers and specialists active in the following research areas: Diffractive Optics; Information Optical Technology; Nanophotonics and Optics of Nanostructures; Image Analysis & Understanding; Information Coding & Security; Earth Remote Sensing Technologies; Hyperspectral Data Analysis; Numerical Methods for Optics and Image Processing; Intelligent Video Analysis. The journal "Computer Optics" has been published since 1987. Published 6 issues per year.
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