本文選題：區(qū)域生長 + 高光譜遙感��； 參考：《大連海事大學(xué)》2015年碩士論文

【摘要】：隨著海上石油運輸業(yè)的蓬勃發(fā)展,溢油事故的發(fā)生愈加頻繁,其對海洋環(huán)境的污染無疑是毀滅性的。事故發(fā)生后,航載高光譜遙感監(jiān)測可以及時提供油區(qū)和油膜厚度信息,為溢油量的估計和風(fēng)險評估提供了有力依據(jù)。然而目前大部分的分割算法對高光譜海面溢油圖像的劃分效果并不十分理想,因此,對其進一步的研究十分必要。基于現(xiàn)有的區(qū)域生長算法,論文結(jié)合高光譜技術(shù)和溢油圖像特點,從以下幾個方面展開研究工作。(1)結(jié)合溢油圖像本身的特點,首先采用非監(jiān)督端元提取思想自動獲取種子點。之后,對高光譜溢油圖像進行解混,得到與高光譜圖像對應(yīng)的豐度圖,以豐度作為距離尺度,在二維的豐度圖上進行區(qū)域生長。(2)由于海面上獲取的圖像受波浪和太陽耀光的影響嚴重,在溢油圖像中產(chǎn)生大量的異常點,論文嘗試了三種改進的生長方式,分別為鄰域均值生長方式、鄰域極值生長方式和拋去鄰域內(nèi)異常點后的均值生長方式。將這三種生長方式與原始生長方式一起,分別與上述兩個步驟相結(jié)合進行實驗分析,并與采用閾值分割方法和聚類分割方法得到的結(jié)果進行對比,驗證了所提方法的有效性。(3)最后,在區(qū)域生長過程中的閾值選擇方面,以區(qū)域邊界點的平均梯度和區(qū)域內(nèi)部的方差作為參數(shù)構(gòu)建模型,實現(xiàn)自動閾值最優(yōu)化選擇,確保得到最佳的分割效果。論文分別利用模擬圖像、在美國印第安納州(Indiana)某農(nóng)林混合試驗場獲取的AVIRIS高光譜圖像數(shù)據(jù)和蓬萊19-3C平臺溢油遙感圖像作為實驗數(shù)據(jù),進行了實驗分析和效果對比。通過實驗結(jié)果證明,論文中提出的結(jié)合解混技術(shù)和改進的生長方式的區(qū)域生長方法是有效且可行的。該方法減輕了錯分和漏分的現(xiàn)象,提高了分割的精度,且降低了運行時間。
[Abstract]:With the booming development of offshore oil transportation, oil spill accidents occur more frequently, and the pollution to marine environment is undoubtedly destructive. After the accident, airborne hyperspectral remote sensing monitoring can provide oil area and oil film thickness information in time, which provides a powerful basis for oil spill estimation and risk assessment. However, most of the current segmentation algorithms are not very ideal for the classification of hyperspectral oil spill images, so it is necessary to further study them. Based on the existing region growth algorithm, combining the hyperspectral technology and the characteristics of oil spill image, this paper starts the research from the following aspects. (1) considering the characteristics of oil spill image itself, the idea of unsupervised end element extraction is used to obtain seed points automatically. After that, the hyperspectral oil spill image is unmixed and the abundance map corresponding to the hyperspectral image is obtained. The abundance is taken as the distance scale. (2) because the images obtained on the sea surface are seriously affected by the waves and solar flares, a large number of abnormal points are produced in the oil spill images. They are neighborhood mean growth mode, neighborhood extremum growth mode and mean growth mode after throwing outliers in the neighborhood. These three growth modes are combined with the original growth mode, and the experimental results are compared with the results obtained by using the threshold segmentation method and the clustering segmentation method. The effectiveness of the proposed method is verified. (3) finally, in the aspect of threshold selection in the process of regional growth, the model is constructed with the average gradient of the regional boundary point and the variance within the region as the parameters to realize the optimal selection of the automatic threshold. Make sure you get the best segmentation results. In this paper, the AVIRIS hyperspectral image data obtained from a mixed agricultural and forestry test site in Indiana, USA, and the oil spill remote sensing image of Penglai 19-3C platform are used as experimental data, and the experimental results are compared. The experimental results show that the proposed method is effective and feasible. This method alleviates the phenomenon of false and missing points, improves the accuracy of segmentation, and reduces the running time.
【學(xué)位授予單位】：大連海事大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：TE88;TP751

【參考文獻】

相關(guān)期刊論文 前4條

1 吳建;;基于區(qū)域生長算法的彩色遙感圖像分割[J];廣西大學(xué)學(xué)報(自然科學(xué)版);2011年06期

2 惠巍巍;衣德萍;廖彩霞;曲林;;混合像元分解研究綜述[J];林業(yè)科技情報;2007年01期

3 張文杰;張鈞萍;張曄;;基于區(qū)域活動輪廓模型的高光譜圖像分割方法[J];遙感技術(shù)與應(yīng)用;2008年03期

4 李二森;朱述龍;周曉明;余文杰;;高光譜圖像端元提取算法研究進展與比較[J];遙感學(xué)報;2011年04期

相關(guān)博士學(xué)位論文 前1條

1 陳進;高光譜圖像分類方法研究[D];國防科學(xué)技術(shù)大學(xué);2010年

，

本文編號：2051675