Application of PCA-CFAR-MNF to Image Enhancement for a UGV FLGPR
The UGV (Unmanned Ground Vehicle) FLGPR (Forward-Looking Ground Penetrating Radar) imaging model spatially variable characteristics lead to the relatively low image SCR (Signal-Clutter Ratio).In order to improve the image quality and improve the SCR, the coherence properties of the target in image sequences is used for image enhancement.That is, images from the same region at different time sequence are enhanced two times.First of all, CFAR (Constant False Alarm Rate) is a preliminary step to enhance the image sequence, and then PCA-CFAR-MNF enhancement algorithm is proposed: according to the iterative nature of the MNF (Maximum Noise Fraction), PCA (Principal Component Analysis) method is first used to transform selecting and then CFAR detection is used to estimate the image background in the iteration,.The measured data show that the proposed method not only keeping the target characteristics, but also have remarkable image enhancement effect, and have greatly improved SCR.
UGV FLGPR Image Enhancement PCA CFAR MNF
Zhang Han-hua Wang Yu-ming Song Qian
School of Electronics Science and Technology,National University of Defense Technology,Changsha,410073,China
国际会议
the 3nd International Conference on Digital Manufacturing & Automation (第三届数字制造与自动化国际会议(ICDMA 2012))
桂林
英文
656-660
2012-08-01（万方平台首次上网日期，不代表论文的发表时间）