本文選題：低空攝影測(cè)量 + 特征點(diǎn)提取　； 參考：《地理與地理信息科學(xué)》2017年03期

【摘要】：影像匹配是低空遙感數(shù)據(jù)處理的核心步驟,而特征提取是影像匹配的基礎(chǔ)。該文從興趣算子的角度分析了攝影測(cè)量中幾種主流特征點(diǎn)提取算法:Moravec算子、Forstner算子、SUSAN算子、Harris和SIFT算子,以角點(diǎn)類型較多的普通幾何圖形、衛(wèi)星遙感影像和動(dòng)力三角翼拍攝的低空遙感影像為數(shù)據(jù),通過(guò)實(shí)驗(yàn)得到各算法的速度、精度、局限性和適應(yīng)性。針對(duì)低空攝影測(cè)量影像,以重復(fù)率為指標(biāo)定量比較和分析了各算法在抗噪、抗對(duì)比對(duì)變化、抗光照變化和抗旋轉(zhuǎn)變化等方面的性能。實(shí)驗(yàn)結(jié)果表明,針對(duì)灰度信息豐富的低空遙感影像,SIFT算子具備尺度不變性,抗噪性最好,Harris算子提取速度最快,Forstner算子精度最高。實(shí)驗(yàn)結(jié)論為低空攝影測(cè)量影像處理提供了一種可行性方法。
[Abstract]:Image matching is the core step of low altitude remote sensing data processing, and feature extraction is the basis of image matching. In this paper, from the angle of interest operator, several main feature points extraction algorithms in photogrammetry are analyzed, such as: Moravec operator Forstner operator, Susan operator, Harris operator and sift operator. The satellite remote sensing image and the low-altitude remote sensing image taken by the power delta wing are used as data, and the speed, accuracy, limitation and adaptability of each algorithm are obtained through experiments. Aiming at low-altitude photogrammetric images, the performance of the algorithms in anti-noise, anti-contrast, anti-illumination and anti-rotation are compared and analyzed quantitatively with repetition rate as the index. The experimental results show that the sift operator is scale-invariant for low-altitude remote sensing images with abundant gray information, and the best anti-noise is the Harris operator, which has the fastest extraction speed and the highest precision of Forstner operator. The experimental results provide a feasible method for image processing of low altitude photogrammetry.
【作者單位】： 長(zhǎng)安大學(xué)測(cè)繪與空間信息研究所;
【基金】：國(guó)家青年科學(xué)基金項(xiàng)目(41504001) 中央高�；究蒲袠I(yè)務(wù)費(fèi)(310826175027)
【分類號(hào)】：TP751
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本文編號(hào)：2084019