本文選題：遙感圖像　切入點：配準　出處：《國防科學技術大學》2014年碩士論文　論文類型：學位論文

【摘要】：圖像配準在許多遙感應用中是一個重要的、不可缺少的步驟。遙感圖像的規(guī)模隨著數(shù)據(jù)分辨率的不斷提高而日漸增大;同時,圖像配準是一個典型的計算和訪存密集型過程,計算復雜度較高,采用傳統(tǒng)串行處理模式已無法滿足軍事、農林等高端應用的實時性處理需求。隨著GPU計算性能和可編程性的不斷提升,GPU通用計算已成為計算機技術領域的研究熱點,這為加快遙感圖像的處理速度提供了新的思路。本文針對基于區(qū)域和基于特征兩類配準中的兩種典型方法,深入研究了基于GPU的遙感圖像配準并行算法及優(yōu)化策略,并面向實際應用設計實現(xiàn)了相應的并行處理軟件原型系統(tǒng)。本文的主要工作和貢獻體現(xiàn)在以下幾個方面:1.研究理解了CPU-GPU異構執(zhí)行模式。研究了以n VIDIA公司GPU為代表的GPU體系結構和相應的CUDA編程模型,系統(tǒng)掌握了使用CPU-GPU異構模式開發(fā)并行算法的基本技能。2.研究并提出了基于GPU的遙感圖像全局配準并行算法。選取一種基于相關系數(shù)全局配準算法作為GPU并行算法設計和優(yōu)化的基礎,給出了適合該類方法的GPU并行設計,并從數(shù)據(jù)加載、線程訪存、通信與同步等幾個方面給出了針對性的優(yōu)化實現(xiàn)策略。實驗結果表明,GPU并行程序獲得了良好的性能加速比。3.研究并提出了基于GPU的遙感圖像控制點匹配并行算法。搜索控制點和基于控制點的匹配參數(shù)計算是該類配準方法的核心步驟,該步驟涉及不規(guī)則數(shù)據(jù)訪問、多重分支、循環(huán)迭代等數(shù)據(jù)相關問題,并行設計和優(yōu)化更為困難。選取一種基于互信息的控制點匹配算法作為研究對象,在數(shù)據(jù)流分析的基礎上,重點針對互信息計算和最小二乘匹配過程設計了兩種GPU并行實現(xiàn)方案。實驗結果表明,在難以消除迭代相關的情況下,通過優(yōu)化利用本地存儲、原子操作等方法使得GPU程序仍然獲得了10倍以上的加速效果。4.設計實現(xiàn)了一個基于Web的遙感圖像并行處理原型系統(tǒng)。系統(tǒng)采用B/S模式,基于Java語言開發(fā),在Spring、Hibernate、Struts框架基礎上提供圖像處理服務,集成了包括上述配準算法研究成果在內12類共49種遙感圖像并行處理算法。系統(tǒng)提供了友好的交互界面并具有良好的可擴展性。
[Abstract]:Image registration is an important and indispensable step in many remote sensing applications. The scale of remote sensing images increases with the increasing resolution of data. At the same time, image registration is a typical computation- and memory-intensive process. Because of the high computational complexity, the traditional serial processing mode can no longer meet the military requirements. With the development of GPU computing performance and programmability, it has become a research hotspot in the field of computer technology. This provides a new way of thinking to speed up the processing of remote sensing image. In this paper, the parallel algorithm and optimization strategy of remote sensing image registration based on GPU are studied, aiming at the two typical methods of register-based and feature-based registration. The corresponding parallel processing software prototype system is designed and implemented for practical applications. The main work and contributions of this paper are as follows: 1.The heterogeneous execution mode of CPU-GPU is studied and understood, and the GPU of n VIDIA company is studied. Table GPU architecture and corresponding CUDA programming model, The system has mastered the basic skill of developing parallel algorithm using CPU-GPU heterogeneous mode. 2. The global registration parallel algorithm of remote sensing image based on GPU is studied and proposed. A global registration algorithm based on correlation coefficient is selected as GPU parallel algorithm. The basis of design and optimization, The GPU concurrent design suitable for this kind of method is given, and the data is loaded, and the memory is accessed by thread. Several aspects such as communication and synchronization are given. The experimental results show that the parallel program achieves a good speedup ratio. 3. The parallel algorithm of remote sensing image control point matching based on GPU is studied and proposed. Searching control points and calculating matching parameters based on control points are the core steps of this kind of registration method, This step involves irregular data access, multiple branches, cyclic iteration and other data-related problems. It is more difficult to design and optimize in parallel. A control point matching algorithm based on mutual information is selected as the research object, based on the data flow analysis. Two parallel implementation schemes of GPU are designed for mutual information computation and least square matching. The experimental results show that the local storage can be optimized under the condition that iterative correlation is difficult to be eliminated. Atomic operation and other methods make the GPU program still get more than 10 times the acceleration effect. 4. A prototype system of remote sensing image parallel processing based on Web is designed and implemented. The system adopts B / S mode and is developed based on Java language. Based on Spring hibernate Struts framework, image processing services are provided, and 49 parallel remote sensing image processing algorithms are integrated into 12 kinds of remote sensing image parallel processing algorithms, including the results of registration algorithms mentioned above. The system provides a friendly interactive interface and has good scalability.
【學位授予單位】：國防科學技術大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TP751
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本文編號：1596566