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2019-04-04
A Novel Method of Ship Detection in High-Resolution SAR Images Based on GaN and HMRF Models
By
Meng Yang,

    Prof. Meng Yang

    School of Communication Engineering

    Hangzhou Dianzi University

    China

    Homepage

Chenchen Yi

    Dr. Chenchen Yi

    College of Communication Engineering

    Hangzhou Dianzi University

    China

    Homepage

Progress In Electromagnetics Research Letters, Vol. 83, 77-82, 2019
doi:10.2528/PIERL19012502 | Google Scholar

Abstract
This research proposes a novel method based on generative adversarial network (GAN) and hidden Markov random field (HMRF) models, for use in large-scale high-resolution synthetic aperture radar (SAR) images. The method consists of three stages. In the first stage, a virtual target and a SAR image are generated by using the GAN model, according to the statistical and gray-level features of the original SAR image used in detection. In the second stage, the virtual target is embedded in the generated image. In the third stage, real targets are detected in the generated image by using the HMRF model. The experiment results show that the proposed algorithm based on GAN and HMRF models can be applied to ship detection in high-resolution SAR images, with high accuracy and processing speed.
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Citation
Meng Yang, and Chenchen Yi, "A Novel Method of Ship Detection in High-Resolution SAR Images Based on GaN and HMRF Models," Progress In Electromagnetics Research Letters, Vol. 83, 77-82, 2019.
doi:10.2528/PIERL19012502
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