本文選題：連接點(diǎn)提取 + SIFT�。� 參考：《測(cè)繪學(xué)報(bào)》2017年01期

【摘要】：針對(duì)空中三角測(cè)量影像連接點(diǎn)提取中存在的誤匹配、點(diǎn)位多而分布不均和點(diǎn)位定位精度低等問題,提出了一種影像連接點(diǎn)均衡化高精度自動(dòng)提取方法。首先采用分塊SIFT技術(shù)進(jìn)行特征的提取與匹配,并利用并查集數(shù)據(jù)結(jié)構(gòu)進(jìn)行特征點(diǎn)的高效多視追蹤;然后采用提出的物方分塊點(diǎn)位篩選算法對(duì)點(diǎn)位進(jìn)行了相對(duì)均衡化的擇優(yōu)挑選;最后采用最小二乘匹配技術(shù)對(duì)得到的SIFT連接點(diǎn)坐標(biāo)位置進(jìn)行精化。選取中國(guó)嵩山遙感定標(biāo)場(chǎng)的有人機(jī)影像和沙漠地區(qū)無人機(jī)影像作為試驗(yàn)數(shù)據(jù),通過目視檢查、像方反投影誤差和檢查點(diǎn)精度等3個(gè)指標(biāo)進(jìn)行了分析,結(jié)果表明本文方法有效克服了弱紋理和重復(fù)紋理導(dǎo)致的連接點(diǎn)提取與匹配困難,并改善了連接點(diǎn)分布的均勻性和提高了連接點(diǎn)的定位精度。
[Abstract]:In view of the problems of mismatching in the extraction of aerial triangulation images, the problem of multi location, uneven distribution and low point location accuracy, a high precision automatic extraction method for image connection point equalization is proposed. Firstly, the feature extraction and matching are carried out by block SIFT technology, and the feature points are carried out by using and searching the data structure. High efficiency and multi view tracking; then the point bit selection algorithm is used to select the relative equilibrium of the point position. Finally, the coordinates position of the SIFT connection point is refined by the least square matching technique. The human computer image and the unmanned aerial vehicle image of the Songshan remote sensing calibration field of China are selected as the test. The data are analyzed by visual inspection, such as 3 indexes such as square back projection error and inspection point accuracy. The results show that the method effectively overcomes the difficulty of extracting and matching connection points caused by weak texture and repeated texture, and improves the uniformity of connection points distribution and improves the positioning accuracy of connection points.

【作者單位】： 信息工程大學(xué)地理空間信息學(xué)院;地理信息工程國(guó)家重點(diǎn)實(shí)驗(yàn)室;
【基金】：國(guó)家自然科學(xué)基金(41501482) 地理信息工程國(guó)家重點(diǎn)實(shí)驗(yàn)室開放研究基金(SKLGIE 2015-M-3-6;SKLGIE 2014-M-3-1)~~
【分類號(hào)】：P231.4

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