A novel ship CFAR detection algorithm based on adaptive parameter enhancement and wake-aided detection in SAR images

Speckles are inherent to SAR. They hide and undermine several relevant information contained in the SAR images. In this paper, a despeckling algorithm using the shrinkage of two-dimensional discrete orthonormal S-transform (2D-DOST) coefficients in the transform domain along with shock filter is proposed. Also, an attempt has been made as a post-processing step to preserve the edges and other details while removing the speckle. The proposed strategy involves decomposing the SAR image into low and high-frequency components and processing them separately. A shock filter is used to smooth out the small variations in low-frequency components, and the high-frequency components are treated with a shrinkage of 2D-DOST coefficients. The edges, for enhancement, are detected using a ratio-based edge detection algorithm. The proposed method is tested, verified, and compared with some well-known models on C-band and X-band SAR images. A detailed experimental analysis is illustrated.

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A CFAR Detection Algorithm for X-ray Pulsar Signal Based on Time-Frequency Entropy

China Satellite Navigation Conference (CSNC) 2016 Proceedings: Volume II - Lecture Notes in Electrical Engineering ◽

10.1007/978-981-10-0937-2_50 ◽

2016 ◽

pp. 595-610

Author(s):

Lu Wang ◽

Xizheng Ke

Keyword(s):

Detection Algorithm ◽

X Ray ◽

Time Frequency ◽

Cfar Detection

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Power Transmission Tower CFAR Detection Algorithm Based on Integrated Superpixel Window and Adaptive Statistical Model

IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium ◽

10.1109/igarss.2019.8900154 ◽

2019 ◽

Author(s):

Xin Zhou ◽

Xiuguo Liu ◽

Qihao Chen ◽

Zhengjia Zhang

Keyword(s):

Statistical Model ◽

Power Transmission ◽

Detection Algorithm ◽

Transmission Tower ◽

Cfar Detection

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A novel design of algorithm and framework for decentralized CFAR signal detection without prior information

MATEC Web of Conferences ◽

10.1051/matecconf/201818904006 ◽

2018 ◽

Vol 189 ◽

pp. 04006

Author(s):

Nan Wang ◽

Yunshan Xu ◽

Haibao Xia ◽

Jundi Wang

Keyword(s):

Signal Detection ◽

Prior Information ◽

Detection Method ◽

Detection Algorithm ◽

Constant False Alarm Rate ◽

Test Statistic ◽

Fusion Algorithm ◽

Cfar Detection ◽

Novel Design ◽

Fusion Detection

In this paper, a fusion detection algorithm that focuses on decentralized CFAR (Constant False Alarm Rate) signal detection problem without prior information is proposed. In the algorithm, the threshold and test statistic of the detection fusion algorithm derive from the conventional CFAR detection method. At last a framework for decentralized CFAR signal detection is designed corresponding to the fusion algorithm. Simulation results illustrate that an almost optimal detection performance is obtained by the proposed algorithm.

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