【摘要】：衛(wèi)星遙感技術(shù)已成為目前國內(nèi)外建立空天感知系統(tǒng)的研究重點。作為遙感圖像處理中至關(guān)重要的一步,遙感圖像的配準技術(shù)受到了越來越多的關(guān)注,其中,遙感圖像的特征提取和特征匹配技術(shù)是基于特征的遙感圖像配準技術(shù)的基礎(chǔ),直接影響最終配準的結(jié)果。在此背景下,本文重點研究了多源遙感圖像配準技術(shù)中特征提取和特征匹配的關(guān)鍵技術(shù),主要做了以下幾方面研究:針對遙感圖像特點,首先對遙感圖像中噪聲去除和輻射矯正進行了圖像預(yù)處理分析,并系統(tǒng)地介紹了遙感圖像配準基礎(chǔ)理論。針對遙感圖像特征提取,介紹了互信息特征、SIFT特征和SURF特征的提取原理,并引入信息熵和網(wǎng)格劃分的思想,在SURF特征提取前對大幅面遙感圖像進行二級網(wǎng)格劃分,通過根據(jù)信息熵提取特征網(wǎng)格的方式大大減少了特征提取計算量。針對灰度差異較大的多源遙感圖像,根據(jù)遙感圖像邊緣輪廓特征,提出了一種基于多項式擬合的形狀內(nèi)容特征提取算法。在對輪廓邊緣使用多項式擬合算法提取特征點的基礎(chǔ)上,改進了形狀內(nèi)容圓形模板使其對于旋轉(zhuǎn)縮放平移變換均具有良好的不變性。實驗證明本文提出算法在速度和魯棒性上均具有優(yōu)勢。針對遙感圖像特征匹配,分別對于SURF特征描述子和改進的形狀內(nèi)容描述子提出了不同的粗匹配算法,在此基礎(chǔ)上,提出了將RANSAC算法和互信息相結(jié)合的精匹配算法。實驗證明,本文方法能夠?qū)崿F(xiàn)多源遙感圖像自動精確的配準需要。
[Abstract]:Satellite remote sensing technology has become the focus of research on the establishment of space and space sensing systems at home and abroad. As a very important step in remote sensing image processing, the technology of remote sensing image registration has been paid more and more attention. Among them, the feature extraction and feature matching technology of remote sensing image is the basis of feature based remote sensing image registration technology. Directly affect the result of final registration. Under this background, this paper focuses on the key techniques of feature extraction and feature matching in multi-source remote sensing image registration technology. Firstly, the noise removal and radiation correction in remote sensing image are analyzed, and the basic theory of remote sensing image registration is introduced systematically. Aiming at feature extraction of remote sensing image, the extraction principle of mutual information feature, SIFT feature and SURF feature is introduced, and the idea of information entropy and mesh division is introduced. Before SURF feature extraction, the large format remote sensing image is divided into two levels of grid. The computation of feature extraction is greatly reduced by extracting feature grid according to information entropy. According to the edge contour feature of remote sensing image, a shape content feature extraction algorithm based on polynomial fitting is proposed for multi-source remote sensing image with large gray level difference. On the basis of using polynomial fitting algorithm to extract feature points from contour edge, the circular template of shape content is improved so that it has good invariance for rotation and zoom translation transformation. Experiments show that the proposed algorithm has advantages in speed and robustness. For remote sensing image feature matching, different coarse matching algorithms are proposed for SURF feature descriptors and improved shape content descriptors. Based on this, a precise matching algorithm combining RANSAC algorithm and mutual information is proposed. Experiments show that this method can realize the automatic and accurate registration of multi-source remote sensing images.
【學位授予單位】：南京理工大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP751

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