本文關(guān)鍵詞： 多源 多時(shí)相 衛(wèi)星遙感影像 影像匹配 影像分割 匹配傳播 預(yù)測(cè)位置修正 輪廓線相關(guān)　出處：《武漢大學(xué)》2014年博士論文　論文類型：學(xué)位論文

【摘要】：隨著數(shù)據(jù)獲取手段的不斷豐富,國(guó)內(nèi)外在軌衛(wèi)星數(shù)量的急劇增加,獲得海量多源衛(wèi)星數(shù)據(jù)已成為可能。單一衛(wèi)星由于成像環(huán)境、重訪周期等因素的限制,無法短時(shí)間內(nèi)獲得大范圍覆蓋的有效數(shù)據(jù),所提供的信息己完全不能滿足遙感對(duì)地觀測(cè)數(shù)據(jù)廣泛應(yīng)用的迫切需求。而現(xiàn)代攝影測(cè)量逐漸發(fā)展進(jìn)入一個(gè)多傳感器、多光譜、多分辨率和多時(shí)相的新階段。作為攝影測(cè)量處理的核心問題,影像匹配結(jié)果的好壞直接決定著最終產(chǎn)品的質(zhì)量。由于目前受各種技術(shù)條件的限制及傳統(tǒng)思維的束縛,針對(duì)多源、多時(shí)相衛(wèi)星遙感影像的聯(lián)合匹配技術(shù)尚不成熟,仍存在較多的問題需要解決。因此深入研究針對(duì)多源、多時(shí)相衛(wèi)星影像的聯(lián)合匹配方法,結(jié)合國(guó)內(nèi)外衛(wèi)星數(shù)據(jù)的特點(diǎn),突破傳統(tǒng)匹配思維的束縛,探索新的影像匹配方法與思路,對(duì)多源、多時(shí)相衛(wèi)星遙感數(shù)據(jù)的聯(lián)合攝影測(cè)量具有重要的意義。 論文以不同傳感器、不同時(shí)相差異的衛(wèi)星遙感影像匹配作為研究目標(biāo),在攝影測(cè)量領(lǐng)域,創(chuàng)新性地將影像分割技術(shù)應(yīng)用于匹配算法中,提出了一種基于區(qū)域分割的衛(wèi)星影像聯(lián)合匹配方法,設(shè)計(jì)了一套流程化的、行之有效的多源、多時(shí)相衛(wèi)星遙感影像匹配方案。論文的主要工作如下： 1、結(jié)合現(xiàn)有影像分割技術(shù),針對(duì)大數(shù)據(jù)量的衛(wèi)星影像特點(diǎn),本文提出了一種基于分裂-合并的影像并行分割方法。在分割方法中,本文構(gòu)建了結(jié)合光譜特征、紋理特征、邊界特征的合并代價(jià)度量準(zhǔn)則,盡可能保證區(qū)域合并的正確性；設(shè)計(jì)了一種并行分割策略,并針對(duì)并行分割中出現(xiàn)的重疊區(qū)域分割結(jié)果不一致的問題,提出了基于層次樹的分割結(jié)果無縫接邊方法,保證了不同分割任務(wù)在重疊區(qū)域的分割結(jié)果一致性,避免了合并時(shí)造成的接邊錯(cuò)位或斷裂問題。在多機(jī)多核硬件條件下,通過本文提出的并行分割方法將影像劃分為一系列局部連續(xù)、平滑的分割區(qū)域,用于后續(xù)匹配的空間約束；并利用基于游程編碼的矢量化方法在分割結(jié)果中提取邊緣輪廓線,用于后續(xù)輪廓線相關(guān)的匹配基元；另外,根據(jù)分割區(qū)域的相鄰關(guān)系,將區(qū)域間的公共交叉點(diǎn)作為后續(xù)影像匹配的特征點(diǎn),進(jìn)行影像間的特征點(diǎn)匹配。因此在本文中,影像分割及其結(jié)果貫穿于算法的始終,用于指導(dǎo)影像的匹配,最終獲得令人滿意的匹配結(jié)果。 2、由于國(guó)產(chǎn)衛(wèi)星數(shù)據(jù)的姿態(tài)軌道參數(shù)直接定位誤差較大,同名點(diǎn)初始預(yù)測(cè)精度較低,導(dǎo)致了匹配約束條件如近似核線的失效問題。針對(duì)上述問題,本文提出了一種基于邊緣輪廓線相關(guān)的方法,利用匹配獲得的同名輪廓線在像方對(duì)姿態(tài)軌道參數(shù)進(jìn)行修正,提高了同名點(diǎn)的初始預(yù)測(cè)精度,有效減小匹配搜索范圍,增強(qiáng)匹配約束條件的可靠性,從而提高匹配的精度與穩(wěn)定性。該方法首先利用基于支持向量機(jī)的云檢測(cè)方法,對(duì)云覆蓋的不可靠分割區(qū)域與輪廓線進(jìn)行檢測(cè)與剔除；其次構(gòu)建了一種循環(huán)可變夾角鏈碼,對(duì)輪廓線進(jìn)行描述,通過鏈碼間的相關(guān)性計(jì)算,確定局部最優(yōu)的候選輪廓曲線段,避免了起始點(diǎn)不一致和鏈碼順序問題造成的匹配失效現(xiàn)象,并對(duì)實(shí)際應(yīng)用中常見的同名輪廓線部分-部分對(duì)應(yīng)情況具有較好的適用性；之后提出了一種基于HOGC (Histogram of Oriented Gradients based on Contour)的輪廓線匹配方法,在候選輪廓曲線段中實(shí)現(xiàn)了同名輪廓線的最終確定；最后通過同名輪廓線上關(guān)鍵點(diǎn)的對(duì)應(yīng)關(guān)系,在像方對(duì)姿態(tài)軌道參數(shù)的同名點(diǎn)初始預(yù)測(cè)誤差進(jìn)行補(bǔ)償。 3、通過對(duì)于現(xiàn)有匹配方法所存在問題的分析,結(jié)合多源、多時(shí)相衛(wèi)星影像的特點(diǎn),本文提出了一種全球SRTM (Shuttle Radar Topography Mission)輔助下的特征點(diǎn)匹配方法。通過對(duì)特征點(diǎn)的提取、匹配約束條件的確定、匹配策略的優(yōu)化、誤匹配的檢測(cè)四個(gè)方面的研究,獲得可靠且定位精度較高的特征同名點(diǎn)位,并作為種子點(diǎn),為后續(xù)的匹配傳播提供可靠的先驗(yàn)知識(shí)。 4、為獲取更加密集的匹配結(jié)果,本文提出了一種基于分割區(qū)域約束的匹配傳播方法。利用標(biāo)記分割區(qū)域代替常用的三角網(wǎng)或多邊形格網(wǎng)作為傳播約束類型,并結(jié)合紋理與幾何相似性,構(gòu)建了一種聯(lián)合距離、夾角、灰度分布的相似性測(cè)度-DANCC (An similarity measure integrates Distance, Angle, and Normalized Cross-Correlation),旨在增強(qiáng)紋理貧乏、重復(fù)區(qū)域、地形起伏較大區(qū)域的匹配正確性,提高匹配傳播的正確率與可靠性。 本文通過較為新穎的匹配思路,結(jié)合實(shí)際應(yīng)用中所遇到的匹配問題,針對(duì)現(xiàn)有算法的不足,充分探索匹配困難區(qū)域的匹配可行性,提出了一種基于區(qū)域分割的多源、多時(shí)相衛(wèi)星遙感影像聯(lián)合匹配方法,將影像分割與影像匹配技術(shù)進(jìn)行了深入的融合。為了證明本文方法的研究與應(yīng)用價(jià)值,本文利用實(shí)際數(shù)據(jù)分別進(jìn)行了多景大數(shù)據(jù)量的衛(wèi)星影像匹配、Google Earth影像輔助的控制點(diǎn)自動(dòng)匹配以及數(shù)字表面模型DSM (Digital Surface Model)自動(dòng)生成的應(yīng)用試驗(yàn)。通過試驗(yàn)結(jié)果證明了本文方法的有效性,為未來多源、多時(shí)相衛(wèi)星遙感數(shù)據(jù)的聯(lián)合攝影測(cè)量奠定了基礎(chǔ)。 值得一提的是,本文方法己成功應(yīng)用于資源系列衛(wèi)星、高分一號(hào)衛(wèi)星等多個(gè)型號(hào)與工程項(xiàng)目中,在實(shí)際應(yīng)用中匹配結(jié)果穩(wěn)定可靠。
[Abstract]:With the means to obtain data continuously enriched, dramatic increase in the number of domestic and foreign satellites, get massive Multi-source Satellite data has become possible. The single satellite imaging environment, revisit cycle and other factors, not a short period of time to obtain valid data coverage, the information provided has been unable to meet the urgent needs of the earth the observation data are widely used. Modern photography gradually develops into a multi-sensor, multi spectral, multi-resolution and multi temporal new stage. As a core problem of photogrammetric processing, image matching results directly determines the quality of the final product. Due to the limitation of current technology, affected by various conditions and the traditional thinking for matching technology combined with multi-source, multi temporal satellite remote sensing image is not mature, there are still many problems need to be solved. So the in-depth research on The joint matching method of multi-source and multi temporal satellite images, combined with the characteristics of satellite data at home and abroad, breaks through the shackles of traditional matching thinking, explores new methods and ideas of image matching, and is of great significance for joint photogrammetry of multi-source and multi temporal satellite remote sensing data.
Based on different sensors, satellite remote sensing images at different phase differences, as the research object in the field of photogrammetry, innovativelinked image segmentation technique is applied to the matching algorithm, we propose a joint image matching method based on region segmentation, a streamlined design, effective multi-source, multi temporal the satellite remote sensing image matching scheme. The main work is as follows:
1, combined with the existing image segmentation technology, satellite images according to the characteristics of large amount of data, this paper proposes a parallel segmentation method based on Split Merge image segmentation. In the method, this paper constructs the combined spectral feature, texture feature, edge feature merging cost metric criteria, as far as possible to ensure the correctness of region merging; a parallel segmentation strategy is designed, and the parallel segmentation of overlapping segmentation results. The problem put forward the hierarchical tree segmentation results based on edge matching method, the different segmentation tasks in the overlapping area of the segmentation results of consistency, to avoid the merger caused by edge dislocation or fracture problems in the multi kernel hardware conditions, using the proposed parallel image segmentation method will be divided into a series of local continuity, regional segmentation, smoothing, for subsequent space constraints; And the use of vectorization method based on run length encoding to extract the edge contour in the segmentation results, relevant for subsequent contour matching; in addition, according to the relationship between adjacent region segmentation, feature points of the common intersection points between regions for subsequent image matching, feature matching between images. Therefore in this paper in the image segmentation and its results throughout the algorithm always used to match the image guidance, the final matching result is satisfactory.
2, because of the attitude and orbit parameters of domestic satellite data directly positioning error is large, the same point of initial prediction accuracy is low, leading to failure of the problem, constraint conditions such as approximate epipolar line. To solve the above problems, this paper presents a method of the edge contour line based on the use of the same name, obtain the contour lines in the image on the orbit and attitude parameters are modified to improve the prediction accuracy of the initial points, effectively reduce the search scope, enhance the reliability of matching constraints, thus improving the accuracy and stability of matching. This method uses the cloud detection method based on support vector machine, the cloud cover is not reliable to detect and eliminate segmentation and contour second line; building a circular alterable included angle chain code, description of the contour line, the correlation between the chain code calculation, to determine the local optimal candidate profile curve, To avoid the matching failure phenomenon caused by the starting point of disagreement and order of the chain code, and part of the same contour common application part corresponding situation has good applicability; after an algorithm based on HOGC (Histogram of Oriented Gradients based on Contour) matching method in the candidate contour line, contour curve the line is realized in the final name of contour line; finally through the corresponding relationship between the key points the same contour line, the compensation in the initial point of the same name as the parameters of attitude and orbit prediction error.
3, through the analysis, the problems existing matching methods combined with the characteristics of multi-source, multi temporal satellite images, this paper proposes a global SRTM (Shuttle Radar Topography Mission) feature point matching method. Assisted by extracting feature points, determine the matching constraints, matching strategy optimization research, four aspects of the detecting error, and obtain reliable and high positioning accuracy of the feature points, and as the seed point, provide prior knowledge for the subsequent matching propagation.
4, the matching results to get more intensive, this paper proposes a matching propagation segmentation method based on constraints. By labeling segmented regions instead of commonly used triangle or polygon grid as propagation constraint types, and combining the texture and geometric similarity, to construct a joint angle, distance, similarity measure -DANCC distribution (An similarity measure integrates Distance gray, Angle and, Normalized Cross-Correlation), is designed to enhance the texture is poor, the repeat region, the terrain matching accuracy of large area, improve the accuracy and reliability of matching propagation.
In this paper, a novel idea, combined with the matching problem encountered in the practical application, aiming at the shortcomings of existing algorithms, to fully explore the feasibility of matching matching difficult area, presents a multi region segmentation based matching method, combined with multi temporal satellite remote sensing image, image segmentation and image matching technology in-depth fusion in order to prove the method in this paper. The research and application of value, the actual data are satellite images view a large amount of data, the use of automatic matching and digital surface model DSM control point Google Earth images (Digital Surface Model) assisted the application test of automatic generation. Through the test results show the validity of this method for the future, multi-source, laid the foundation for joint photographic measurement of multitemporal satellite remote sensing data.
It is worth mentioning that this method has been successfully applied to many models and engineering projects such as resource series satellite, gou1 satellite and so on, and the matching results in practical applications are stable and reliable.

【學(xué)位授予單位】：武漢大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2014
【分類號(hào)】：P237

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