本文選題：速度場(chǎng) + 局部相關(guān)跟蹤��； 參考：《昆明理工大學(xué)》2017年碩士論文

【摘要】：太陽圖像中蘊(yùn)含著大量不同尺度、不同頻率和不同速度的太陽活動(dòng)的運(yùn)動(dòng)學(xué)信息,比如大尺度的活動(dòng)(黑子、耀斑、暗條等)以及小尺度活動(dòng)(微耀斑、微暗條等)。當(dāng)不同尺度的太陽活動(dòng)混合在一起的時(shí)候,特定目標(biāo)的速度場(chǎng)的測(cè)量就變得非常困難,小尺度的變化會(huì)被大尺度的運(yùn)動(dòng)所掩蓋。本文的研究目標(biāo)是利用多尺度多分辨率的思想與光流技術(shù)相結(jié)合,計(jì)算不同空間尺度的速度場(chǎng),以進(jìn)行混合運(yùn)動(dòng)速度場(chǎng)的測(cè)量。從而得到各種尺度太陽活動(dòng)特征的運(yùn)動(dòng)趨勢(shì),全面地從局部到整體理解太陽特征的運(yùn)動(dòng)規(guī)律,為太陽物理學(xué)家提供研究太陽活動(dòng)演化的有效工具。本文主要進(jìn)行了以下研究:1.論文分析了傳統(tǒng)的單一尺度速度場(chǎng)測(cè)量方法,然后對(duì)局部相關(guān)跟蹤算法進(jìn)行改進(jìn),稱為加權(quán)局部相關(guān)跟蹤算法。改進(jìn)的內(nèi)容主要為粗細(xì)匹配的搜索策略、將最大互相關(guān)系數(shù)作為權(quán)重對(duì)局部區(qū)域進(jìn)行加權(quán)平均。并對(duì)局部相關(guān)跟蹤和加權(quán)局部相關(guān)跟蹤這兩種算法進(jìn)行了比較;2.為了測(cè)量不同尺度的太陽活動(dòng)的速度場(chǎng),將加權(quán)局部相關(guān)跟蹤算法與多尺度多分辨率分層細(xì)化的思想相結(jié)合,實(shí)現(xiàn)了多尺度加權(quán)局部相關(guān)跟蹤算法,以測(cè)量混合運(yùn)動(dòng)速度場(chǎng);3.為了驗(yàn)證多尺度加權(quán)局部相關(guān)跟蹤算法的精度,首先通過模擬實(shí)驗(yàn)進(jìn)行誤差分析。分析結(jié)果表明我們所改進(jìn)的多尺度加權(quán)局部相關(guān)跟蹤算法的測(cè)量誤差為1%;然后對(duì)三組真實(shí)的數(shù)據(jù)集進(jìn)行速度場(chǎng)的測(cè)量。不僅對(duì)黑子本影和半影的速度場(chǎng)進(jìn)行準(zhǔn)確測(cè)量,而且在其中的兩組數(shù)據(jù)集中,還發(fā)現(xiàn)黑子本影內(nèi)有運(yùn)動(dòng),這是傳統(tǒng)的單一尺度速度場(chǎng)測(cè)量方法不能得到的;4.討論了多尺度加權(quán)局部相關(guān)跟蹤算法的重要參數(shù),包括金字塔的層數(shù)、計(jì)算窗口大小的設(shè)置。本文所提出的方法不僅僅可用來分析相鄰時(shí)刻的變化,更重要的是從整個(gè)序列圖像的角度去考慮圖像內(nèi)容的變化。通過模擬實(shí)驗(yàn)以及真實(shí)的數(shù)據(jù)測(cè)量,我們發(fā)現(xiàn)該方法不僅能夠精確測(cè)量單一尺度運(yùn)動(dòng)的速度場(chǎng),而且可以解決混合運(yùn)動(dòng)中大尺度淹沒小尺度運(yùn)動(dòng)的問題。通過構(gòu)建金字塔圖像,可以定量的分析不同分辨率下的速度場(chǎng),得到在不同空間尺度的速度場(chǎng),從而體現(xiàn)各種尺度太陽活動(dòng)特征的運(yùn)動(dòng)趨勢(shì)。
[Abstract]:The solar images contain a great deal of kinematic information of solar activities with different scales, frequencies and velocities, such as large scale activities (sunspots, flares, dark strips, etc.) and small scale activities (micro flares, small dark strips, etc.). When the solar activities of different scales are mixed together, the measurement of the velocity field of a specific target becomes very difficult, and the small scale changes will be masked by the large scale motion. The purpose of this paper is to calculate the velocity field of different spatial scales by combining the idea of multi-scale and multi-resolution with optical flow technique to measure the velocity field of mixed motion. Thus, the motion trend of solar activity characteristics on various scales is obtained, and the motion law of solar characteristics is comprehensively understood from local to global, which provides an effective tool for solar physicists to study the evolution of solar activity. This article mainly carries on the following research: 1. This paper analyzes the traditional single scale velocity field measurement method, and then improves the local correlation tracking algorithm, which is called weighted local correlation tracking algorithm. The main content of the improvement is the search strategy of coarse and fine matching, in which the maximum cross-relation number is used as the weight to weighted the local region. The local correlation tracking and weighted local correlation tracking are compared. In order to measure the velocity field of solar activity at different scales, the weighted local correlation tracking algorithm is combined with the idea of multi-scale multi-resolution hierarchical thinning, and a multi-scale weighted local correlation tracking algorithm is implemented to measure the velocity field of mixed motion. In order to verify the accuracy of the multi-scale weighted local correlation tracking algorithm, error analysis is carried out through simulation experiments. The analysis results show that the measurement error of our improved multi-scale weighted local correlation tracking algorithm is 1 and then the velocity field of three groups of real data sets is measured. Not only the velocity fields of the sunspot shadow and penumbra are measured accurately, but also in the two sets of data sets, it is found that there is movement in the shadow of the sunspot, which can not be obtained by the traditional method of single scale velocity field measurement. The important parameters of the multi-scale weighted local correlation tracking algorithm are discussed, including the number of layers of the pyramid and the setting of calculating window size. The method proposed in this paper can be used not only to analyze the changes of adjacent moments, but also to consider the change of image content from the point of view of the whole sequence of images. Through simulation experiments and real data measurements, we find that this method can not only accurately measure the velocity field of a single scale motion, but also solve the problem of submergence of large scale and small scale motion in mixed motion. By constructing pyramid image, the velocity field at different resolution can be quantitatively analyzed, and the velocity field at different spatial scales can be obtained.
【學(xué)位授予單位】：昆明理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：P182;TP391.41

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