Abstract

A novel algorithm for bridge recognition of median synthetic aperture radar (SAR) images using histogram entropy presented by Pun is proposed. Firstly, Lee filter and histogram proportion are used to denoise the original image and to make the target evident. Then, water regions are gained through histogram segmentation and the contours of water regions are extracted. After these, the potential bridge targets are obtained based on the space relativity between bridges and water regions using improved contour search. At last, bridges are recognized by extracting the feature of Pun histogram entropy (PHE) of these potential bridge targets. Experimental results show the good qualities of the algorithm, such as fast speed, high rate of recognition, and low rate of false target.

© 2009 Chinese Optics Letters

Terahertz 3D point cloud imaging for complex targets

Ningbo Wang and Feng Qi
Appl. Opt. 62(22) 5976-5981 (2023)

Nonrigid synthetic aperture radar and optical image coregistration by combining local rigid transformations using a Kohonen network

Mehdi Salehpour and Alireza Behrad
J. Opt. Soc. Am. A 34(10) 1865-1876 (2017)

Nonlinear techniques in optical synthetic aperture radar image generation and target recognition

Samuel Weaver and Kelvin Wagner
Appl. Opt. 34(20) 3981-3996 (1995)

Entropy optimized filter for pattern recognition

Michael Fleisher, Uri Mahlab, and Joseph Shamir
Appl. Opt. 29(14) 2091-2098 (1990)

Fast auto-focusing search algorithm for a high-speed and high-resolution camera based on the image histogram feature function

Chenzi Guo, Zelong Ma, Xu Guo, Wenxian Li, Xinda Qi, and Qinglei Zhao
Appl. Opt. 57(34) F44-F49 (2018)