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  本文選題：遙感圖像匹配 + 局部不變特征�。� 參考：《西南交通大學(xué)》2017年碩士論文

【摘要】：基于局部不變特征的匹配方法是近年來圖像處理研究的一個熱點,被廣泛的應(yīng)用于各個領(lǐng)域,本文將局部不變特征方法應(yīng)用于遙感領(lǐng)域,主要研究遙感圖像的匹配算法。遙感圖像包括同源遙感圖像與異源遙感圖像,它們的匹配方法都有著各自的研究難點。同源遙感圖像匹配的難點主要是實現(xiàn)算法的實時性,而異源遙感圖像主要問題是解決圖像間的非線性灰度差異,基于以上問題,本文分別提出了以下的算法。為了解決遙感圖像匹配的實時性問題,目前的解決方案主要采用二進制描述子方法進行匹配。描述子通常需要計算主方向來獲得旋轉(zhuǎn)不變性,但主方向的計算往往存在誤差,會導(dǎo)致匹配效果不理想。針對上述問題,本文提出一種基于等距環(huán)局部二值模式的二進制描述子方法。在描述子構(gòu)造與描述子匹配過程中分別使用了等距環(huán)局部二值采樣模式與分組匹配策略,使得構(gòu)造的描述子具有旋轉(zhuǎn)不變性,解決主方向問題和加速匹配過程。實驗結(jié)果表明,與傳統(tǒng)二進制描述子相比,本文方法可以有效解決主方向問題,并且具有更快的匹配速度及更高的準確率。異源遙感圖像的匹配是一個難點,主要原因是異源圖像由于成像原理等因素的不同,造成獲得的圖像之間有較大的非線性灰度差異,使得傳統(tǒng)的基于灰度與基于梯度的匹配方法無法較好的進行異源圖像的匹配。針對上述問題,本文提出了一種粗細匹配結(jié)合的方法。在粗匹配階段消除圖像間的位移、旋轉(zhuǎn)、尺度變化,然后,在精匹配階段消除圖像間的非線性灰度差異,并使用模板匹配提高匹配的精確度。實驗表明,本文提出的算法可以有效地解決異源遙感圖像的匹配。
[Abstract]:The matching method based on local invariant feature is a hot topic in image processing in recent years and has been widely used in various fields. In this paper, the local invariant feature method is applied to remote sensing, and the matching algorithm of remote sensing image is mainly studied. Remote sensing images include homologous remote sensing images and heterogenous remote sensing images, and their matching methods have their own difficulties. The difficulty of homologous remote sensing image matching is mainly to realize the real-time performance of the algorithm, while the main problem of heterogeneous remote sensing image is to solve the nonlinear gray difference between images. Based on the above problems, the following algorithms are proposed in this paper. In order to solve the real-time problem of remote sensing image matching, the current solution mainly uses binary description sub-method to match. The descriptor usually needs to calculate the principal direction to obtain rotation invariance, but the calculation of the principal direction often has errors, which will lead to unsatisfactory matching effect. In order to solve the above problems, this paper presents a binary descriptor submethod based on the local binary mode of equidistant ring. In the process of descriptor construction and descriptor matching, the local binary sampling mode and grouping matching strategy of equidistant ring are used respectively, which makes the constructed descriptor rotation-invariant, solves the main direction problem and accelerates the matching process. Experimental results show that compared with the traditional binary descriptor, the proposed method can effectively solve the principal direction problem, and has faster matching speed and higher accuracy. The matching of heterogenous remote sensing images is a difficult problem. The main reason is that there is a large nonlinear gray difference between the different images due to the different imaging principles. It makes the traditional grayscale and gradient-based matching methods can not better match the heterogeneous images. In order to solve the above problems, this paper presents a method of combining coarse and fine matching. In the coarse matching stage, the displacement, rotation and scale change of the images are eliminated. Then, in the fine matching stage, the nonlinear gray difference between images is eliminated, and the accuracy of matching is improved by template matching. Experiments show that the proposed algorithm can effectively solve the matching of heterogeneous remote sensing images.
【學(xué)位授予單位】：西南交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP751

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本文編號：1846677