一種VideoSAR動目標(biāo)陰影檢測方法
發(fā)布時間：2019-03-15 09:51
【摘要】：在高幀率的視頻合成孔徑雷達(dá)(VideoSAR)成像模式獲得的圖像序列中,多普勒頻移使運動目標(biāo)在實際位置留下陰影,且相鄰幀圖像具有很強相關(guān)性。該文針對上述現(xiàn)象提出一種VideoSAR圖像中動目標(biāo)陰影檢測的方法。首先,對每幀圖像通過結(jié)合尺度不變特征變換(SIFT)和隨機抽樣一致性(RANSAC)算法實現(xiàn)配準(zhǔn)并進(jìn)行背景補償,再采用CattePM模型抑制相干斑噪聲。然后通過Tsallis灰度熵的最大化閾值分割方法自動分離目標(biāo)和背景,獲得二值圖像。最后,對相鄰多幀圖像背景建模并差分,再結(jié)合三幀間差分法提取動目標(biāo)陰影,結(jié)果標(biāo)記至原幀圖像相應(yīng)位置�；诿绹鳶andia實驗室公布的VideoSAR成像片段,實現(xiàn)了多個移動車輛的檢測,驗證了所提算法的有效性。
[Abstract]:In the high frame rate video synthetic aperture radar (VideoSAR) imaging image sequence, Doppler frequency shift causes the moving target to leave shadow in the real position, and the adjacent frame image has strong correlation. In this paper, a method for shadow detection of moving targets in VideoSAR images is proposed. Firstly, each frame is registered and compensated by combining scale invariant feature transform (SIFT) and random sampling consistent (RANSAC) (RANSAC) algorithm, and then the CattePM model is used to suppress speckle noise. Then the object and background are automatically separated by the maximum threshold segmentation method of Tsallis gray entropy, and the binary image is obtained. Finally, the background of the adjacent multi-frame image is modeled and differentiated, and then the moving object shadow is extracted by using the three-frame difference method, and the result is marked to the corresponding position of the original frame image. Based on the VideoSAR image fragment published by American Sandia Laboratory, the detection of several mobile vehicles is realized, and the effectiveness of the proposed algorithm is verified.
【作者單位】： 南京航空航天大學(xué)電子信息工程學(xué)院;南京工程學(xué)院計算機工程學(xué)院;
【基金】：國家自然科學(xué)基金(61671240) 江蘇省自然科學(xué)基金青年基金(BK20150730) 中央高�；究蒲袠I(yè)務(wù)費(NZ2016105) 南京航空航天大學(xué)研究生創(chuàng)新基地(實驗室)開放基金資助項目(kfjj20170401)~~
【分類號】：TN957.52
本文編號：2440522
[Abstract]:In the high frame rate video synthetic aperture radar (VideoSAR) imaging image sequence, Doppler frequency shift causes the moving target to leave shadow in the real position, and the adjacent frame image has strong correlation. In this paper, a method for shadow detection of moving targets in VideoSAR images is proposed. Firstly, each frame is registered and compensated by combining scale invariant feature transform (SIFT) and random sampling consistent (RANSAC) (RANSAC) algorithm, and then the CattePM model is used to suppress speckle noise. Then the object and background are automatically separated by the maximum threshold segmentation method of Tsallis gray entropy, and the binary image is obtained. Finally, the background of the adjacent multi-frame image is modeled and differentiated, and then the moving object shadow is extracted by using the three-frame difference method, and the result is marked to the corresponding position of the original frame image. Based on the VideoSAR image fragment published by American Sandia Laboratory, the detection of several mobile vehicles is realized, and the effectiveness of the proposed algorithm is verified.
【作者單位】： 南京航空航天大學(xué)電子信息工程學(xué)院;南京工程學(xué)院計算機工程學(xué)院;
【基金】：國家自然科學(xué)基金(61671240) 江蘇省自然科學(xué)基金青年基金(BK20150730) 中央高�；究蒲袠I(yè)務(wù)費(NZ2016105) 南京航空航天大學(xué)研究生創(chuàng)新基地(實驗室)開放基金資助項目(kfjj20170401)~~
【分類號】：TN957.52
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，本文編號：2440522
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