高分辨SAR圖像自動(dòng)區(qū)域篩選目標(biāo)檢測(cè)算法

宋文青; 王英華; 劉宏偉

doi:10.11999/JEIT150808

高分辨SAR圖像自動(dòng)區(qū)域篩選目標(biāo)檢測(cè)算法

doi: 10.11999/JEIT150808

基金項(xiàng)目:

國(guó)家自然科學(xué)基金(61201292, 61322103, 61372132)，全國(guó)優(yōu)秀博士學(xué)位論文作者專(zhuān)項(xiàng)資金(FANEDD-201156)，中央高校基本科研業(yè)務(wù)費(fèi)專(zhuān)項(xiàng)資金

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- 文章訪問(wèn)數(shù): 1685
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- 被引次數(shù): 0
出版歷程
- 收稿日期: 2015-07-08
- 修回日期: 2015-11-20
- 刊出日期: 2016-05-19

An Automatic Block-to-block Censoring Target Detector for High Resolution SAR Image

Funds:

The National Natural Science Foundation of China (61201292, 61322103, 61372132), The Foundation for the Author of National Excellent Doctoral Dissertation of China (FANEDD-201156), The Fundamental Research Funds for the Central Universities

摘要

摘要: 在G0分布背景雜波假設(shè)下，基于VI-CFAR算法該文提出一種自動(dòng)區(qū)域篩選的恒虛警目標(biāo)檢測(cè)算法，以解決高分辨SAR圖像復(fù)雜環(huán)境背景下的目標(biāo)檢測(cè)問(wèn)題。該算法首先利用變化指數(shù)(VI)統(tǒng)計(jì)量對(duì)局部參考窗內(nèi)的均勻區(qū)域進(jìn)行篩選，以剔除參考窗內(nèi)具有目標(biāo)干擾點(diǎn)的非均勻區(qū)域；然后利用均值比(MR)統(tǒng)計(jì)量對(duì)參考窗內(nèi)同質(zhì)的均勻區(qū)域進(jìn)行區(qū)域合并，以解決雜波邊界處的背景雜波篩選問(wèn)題；最后利用篩選到的同質(zhì)均勻區(qū)域內(nèi)的像素集合進(jìn)行背景雜波參數(shù)估計(jì)，對(duì)待檢測(cè)區(qū)域?qū)崿F(xiàn)二值檢測(cè)。通過(guò)實(shí)測(cè)SAR圖像車(chē)輛目標(biāo)檢測(cè)實(shí)驗(yàn)表明，在多目標(biāo)和雜波邊界復(fù)雜環(huán)境背景下，該算法具有較穩(wěn)定的檢測(cè)性能和虛警抑制能力。
- 恒虛警檢測(cè) /
- 區(qū)域篩選 /
- 變化指數(shù) /
- 均值比 /
- G0分布
Abstract: Assuming theG0 distribution clutter background, an automatic block-to-block censoring CFAR (ABC-CFAR) detector is proposed based on VI-CFAR for high resolution SAR image in nonhomogeneous environments. Firstly the Variability Index (VI) statistic is used to censor the blocks in the local reference window in order to reject the non-homogeneous ones in which there exists interfering target samples. Then the Mean Ratio (MR) statistic is utilized to select and combine the homogeneous blocks which have the same distribution, in order to solve background clutter censoring problem in clutter edge situation. At last, with the selected blocks, the distribution parameters of the background clutter are estimated, and then the binary detection is implemented in the Block Under Test (BUT). Using the real SAR image data including ground vehicle targets, the experimental results show that the proposed ABC-CFAR detector has robust detection performance and false alarm regulation property in multi-target and clutter edge nonhomogeneous environment.
- Block-to-block censoring /
- Variability Index (VI) /
- Mean Ratio (MR) /
- G0distribution /

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