@inproceedings{40bee624849e41c4bdb133eeb002992d,
title = "Ladar imaging detection of salient map based on PWVD and R{\'e}nyi entropy",
abstract = "Spatial-frequency information of a given image can be extracted by associating the grey-level spatial data with one of the well-known spatial/spatial-frequency distributions. The Wigner-Ville distribution (WVD) has a good characteristic that the images can be represented in spatial/spatial-frequency domains. For intensity and range images of ladar, through the pseudo Wigner-Ville distribution (PWVD) using one or two dimension window, the statistical property of R{\'e}nyi entropy is studied. We also analyzed the change of R{\'e}nyi entropy's statistical property in the ladar intensity and range images when the man-made objects appear. From this foundation, a novel method for generating saliency map based on PWVD and R{\'e}nyi entropy is proposed. After that, target detection is completed when the saliency map is segmented using a simple and convenient threshold method. For the ladar intensity and range images, experimental results show the proposed method can effectively detect the military vehicles from complex earth background with low false alarm.",
keywords = "Ladar imaging, R{\'e}nyi entropy, Saliency map, Target detection",
author = "Xu Yuannan and Zhao Yuan and Deng Rong and Dong Yanbing",
year = "2013",
doi = "10.1117/12.2032430",
language = "英语",
isbn = "9780819498021",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
booktitle = "MIPPR 2013",
note = "8th Symposium on Multispectral Image Processing and Pattern Recognition, MIPPR 2013 ; Conference date: 26-10-2013 Through 27-10-2013",
}