發(fā)布時間：2018-06-28 09:33

  本文選題：影像拼接 + 特征提取�。� 參考：《北京建筑大學》2017年碩士論文

【摘要】：無人機遙感作為自然災害(如地震救援等)現場數據實時獲取與應急指揮和快速反應的重要技術,不僅具有成本低、操作簡單、機動靈活等特點,而且其獲取的圖像還具有數據量多、分辨率高和實時性強等優(yōu)點。同時無人機遙感影像又具有幅面小、像幅多、多重疊等問題,在應急指揮和快速反應的實時影像獲取中,如何實現快速、高效的無人機序列圖像拼接,就顯得尤為重要。在處理圖像拼接時,在影像配準這一過程中,不可避免的會產生變形。在處理無人機序列圖像拼接時,后面的影像依賴于前面已經配準過的拼接影像,這樣就會產生拼接誤差逐步積累的問題。因此,在完成拼接這一過程中時,不僅要保證拼接實施過程的效率,還要保證拼接結果的質量。這樣才能繼續(xù)發(fā)揮無人機遙感的優(yōu)勢,拓寬無人機序列拼接影像的應用范圍、提高無人機序列拼接影像使用價值。隨著多處理器計算機的普及以及并行化編程模型的不斷優(yōu)化,多核架構并行化編程已經成為不可阻擋的發(fā)展趨勢。它不僅能夠成功解決復雜冗余的大型計算問題,而且它的運行速度極快。為了進一步解放人力、物力,我們需要充分發(fā)揮多核計算機的使用性能,從而去提高無人機序列拼接影像的質量和效率。本論文首先對無人機影像進行預處理操作,主要是進行拉普拉斯銳化,增強影像邊緣、采用Wallis濾波對圖像均勻分塊,根據塊內灰度信息自適應勻光勻色、按照重疊度截取感興趣區(qū)。接著提出了一種基于規(guī)則格網的Harris特征提取,然后利用馬氏距離提取同名點,同時加入核線、唯一性多級約束條件實現由粗到精的匹配過程,最后利用RANSAC算法迭代求出最優(yōu)單應矩陣,將影像轉換到同一參考系統(tǒng)下,利用加權平均值算法,實現融合拼接。在這一基礎上,本文綜合考慮了影響無人機遙感影像拼接質量的來源,將多航帶無人機影像采用多級分組分塊進行拼接,對不同組塊的拼接誤差進行控制;同時引入多核并行編程技術,即保證影像拼接質量,又提高影像拼接效率。為了提高多核計算機運行加速比,本文提出了用動態(tài)創(chuàng)建線程和創(chuàng)建線程池來降低創(chuàng)建線程帶來的開銷的策略。通過實驗對比發(fā)現,與常用特征提取與匹配算法比較,本文提出的基于規(guī)則格網的Harris特征提取算子提取的特征點分布均勻,有利于全局匹配、提高影像配準與拼接質量;本文提出的無人機序列影像的多級分組分塊拼接與多核并行編程技術方法,即保證影像拼接質量,又提高影像拼接效率。有效控制了拼接誤差傳播的積累,同時大大減少了程序運行時間,一定程度上驗證了本文提出的基于規(guī)則格網的Harris特征提取及多級分組分塊并行化編程算法的可行性和有效性。
[Abstract]:UAV remote sensing is an important technology for real-time acquisition of field data of natural disasters (such as earthquake rescue), emergency command and rapid response. It not only has the characteristics of low cost, simple operation, flexibility and so on. Moreover, the obtained images also have the advantages of large amount of data, high resolution and real-time. At the same time, UAV remote sensing images have many problems, such as small format, multi-amplitude, multi-overlapping and so on. In emergency command and real-time image acquisition of rapid response, how to achieve rapid and efficient UAV sequence image mosaic, it is particularly important. In the process of image stitching, deformation will inevitably occur in the process of image registration. In the processing of UAV sequence image stitching, the back image depends on the pre-registered stitching image, which will lead to the problem of gradual accumulation of stitching errors. Therefore, in the process of stitching, we should not only ensure the efficiency of the mosaic implementation process, but also ensure the quality of the stitching results. In this way, the advantages of UAV remote sensing can continue to be brought into play, the application scope of UAV sequence mosaic image can be widened, and the use value of UAV sequence mosaic image can be improved. With the popularization of multiprocessor computer and the optimization of parallel programming model, parallel programming of multi-core architecture has become an irresistible trend. It not only can successfully solve the large-scale computing problem with complex redundancy, but also can run very fast. In order to further liberate manpower and material resources, we need to give full play to the performance of multi-core computer, so as to improve the quality and efficiency of UAV sequence stitching image. In this paper, firstly, the UAV image is preprocessed by Laplacian sharpening and image edge enhancement. Wallis filter is used to divide the image evenly into blocks, and the image is evenly colored adaptively according to the gray level information in the block. Intercept the area of interest according to overlap. Then, a Harris feature extraction method based on regular grid is proposed, and then the point of the same name is extracted by Markov distance, and the kernel line is added at the same time, and the unique multilevel constraint condition is used to realize the matching process from coarse to fine. Finally, the optimal homography matrix is iterated out by using the RANSAC algorithm, and the image is converted to the same reference system, and the weighted average value algorithm is used to realize fusion and stitching. On this basis, this paper synthetically considers the source of affecting the quality of UAV remote sensing image splicing, the multi-band UAV image is spliced by multi-level grouping, and the splicing error of different blocks is controlled. At the same time, multi-core parallel programming technology is introduced to ensure the quality of image stitching and improve the efficiency of image stitching. In order to improve the speedup ratio of multi-core computers, this paper proposes a strategy of dynamically creating threads and creating thread pools to reduce the overhead of creating threads. Compared with the common feature extraction and matching algorithms, the feature points extracted by Harris feature extraction operator based on rule grid in this paper are evenly distributed, which is conducive to global matching and improve the quality of image registration and stitching. In this paper, the multi-level grouping block splicing and multi-core parallel programming method for UAV sequence images is proposed, which ensures the quality of image mosaic and improves the efficiency of image stitching. The accumulation of splicing error propagation is effectively controlled, and the running time of the program is greatly reduced. To some extent, the feasibility and effectiveness of the proposed Harris feature extraction algorithm based on rule-based grid and multilevel block parallel programming algorithm are verified.
【學位授予單位】：北京建筑大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP391.41

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本文編號：2077535