【摘要】：針對(duì)傳統(tǒng)的半全局匹配算法在處理視差變化大、遮擋嚴(yán)重的城市航空影像時(shí),存在匹配精度下降、匹配效率低下的問題,提出了一種基于區(qū)域生長的半全局密集匹配方法。采用區(qū)域生長算法獲取影像的初始視差,并從初始匹配點(diǎn)中挑選可靠的點(diǎn)作為視差控制點(diǎn);利用區(qū)域生長獲取的視差圖,限制各個(gè)方向動(dòng)態(tài)規(guī)劃的過程以加速最優(yōu)路徑的搜索;通過視差控制點(diǎn)對(duì)動(dòng)態(tài)規(guī)劃的路徑進(jìn)行修正,避免錯(cuò)誤匹配代價(jià)的傳播。基于城區(qū)無人機(jī)影像的實(shí)驗(yàn)結(jié)果表明,所提算法不僅可以提高匹配結(jié)果正確率,還能使耗費(fèi)的內(nèi)存和時(shí)間都不到原算法的50%。
[Abstract]:A semi-global dense matching method based on region growth is proposed to solve the problem of poor matching accuracy and low matching efficiency in the traditional semi-global matching algorithm when dealing with urban aerial images with large parallax variation and severe occlusion. The region growth algorithm is used to obtain the initial parallax of the image, and the reliable point is selected as the parallax control point from the initial matching point, and the parallax map obtained by the region growth is used to limit the process of dynamic programming in each direction in order to accelerate the search of the optimal path. The path of dynamic programming is modified by parallax control points to avoid the propagation of error matching cost. Experimental results based on urban UAV images show that the proposed algorithm can not only improve the accuracy of the matching results, but also make the memory and time consumed less than 50% of the original algorithm.
【作者單位】： 河海大學(xué);
【基金】：江蘇省自然科學(xué)基金項(xiàng)目(BK2012812)
【分類號(hào)】：P231;TP391.41

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本文編號(hào)：2252720