本文選題：高光譜遙感　切入點(diǎn)：填圖算法　出處：《成都理工大學(xué)》2015年碩士論文

【摘要】：遙感技術(shù)的發(fā)展和廣泛應(yīng)用已經(jīng)使得人們不需要直接接觸地表目標(biāo)和區(qū)域就能獲取相關(guān)數(shù)據(jù),然后分析處理后得到所需信息。20世紀(jì)80年代以來(lái),高光譜遙感技術(shù)的出現(xiàn)和發(fā)展讓人們通過(guò)遙感技術(shù)觀測(cè)和認(rèn)識(shí)事物的能力又進(jìn)步了一個(gè)臺(tái)階。高光譜遙感技術(shù)又稱為成像光譜遙感技術(shù),它是以光譜學(xué)為基礎(chǔ),,在400~2500nm波長(zhǎng)范圍內(nèi),獲取光譜分辨率小于10nm的影像數(shù)據(jù),其數(shù)據(jù)往往包含了空間、輻射和光譜三種信息。高光譜圖像同時(shí)具有光學(xué)特性和光譜識(shí)別能力,其蘊(yùn)含的豐富波譜數(shù)據(jù)使得地物的定量測(cè)量成為了可能,從而逐漸成為遙感領(lǐng)域研究與應(yīng)用的前沿?zé)狳c(diǎn),并已經(jīng)廣泛應(yīng)用在環(huán)境調(diào)查與監(jiān)測(cè)、礦產(chǎn)探測(cè)、海洋大氣土地動(dòng)態(tài)監(jiān)測(cè)、軍事應(yīng)用等廣泛領(lǐng)域。高光譜遙感蝕變礦物填圖方法是高光譜數(shù)據(jù)處理的關(guān)鍵,直接影響填圖結(jié)果的使用精度和要求,文章主要圍繞填圖算法機(jī)理和應(yīng)用進(jìn)行了研究:(1)文章首先從地物光譜特征的機(jī)理入手,歸納了常見(jiàn)的蝕變礦物光譜特征形成原因,可根據(jù)地物不同的組成成分判斷該種地物的光譜特征,并總結(jié)了常見(jiàn)的碳酸鹽化、粘土化和二價(jià)鐵等蝕變礦物波譜曲線。(2)詳細(xì)介紹了當(dāng)前常用的幾類高光譜填圖算法的概念和原理,總結(jié)了光譜特征提取的方法。通過(guò)實(shí)驗(yàn)構(gòu)建模擬數(shù)據(jù)評(píng)估了光譜角填圖法(SAM),光譜信息散度法(SIDM)和混合調(diào)制匹配濾波法(MTMF)的性能和精度。經(jīng)對(duì)比分析,數(shù)據(jù)的噪聲會(huì)對(duì)幾種方法的填圖精度產(chǎn)生較大的影響。因此,針對(duì)噪聲較多的影像在填圖之前需要進(jìn)行降噪處理。(3)闡述了高光譜數(shù)據(jù)處理流程與主要方法,以研究區(qū)SASI高光譜數(shù)據(jù)為例,基于油氣烴類微滲漏理論,提出了基于“特征光譜掩膜+MTMF”填圖方法。實(shí)現(xiàn)了對(duì)研究區(qū)的烴類、粘土類和碳酸鹽類等蝕變異常信息的提取,并有效的剔除了干擾因素。結(jié)合已有地質(zhì)資料和野外實(shí)測(cè)光譜驗(yàn)證,取得了良好的效果。
[Abstract]:The development and wide application of remote sensing technology has made it possible to obtain the relevant data without direct contact with surface targets and regions, and then analyze and process to obtain the required information since the 1980s. With the emergence and development of hyperspectral remote sensing technology, the ability of people to observe and understand things through remote sensing technology has been further improved. Hyperspectral remote sensing technology, also known as imaging spectral remote sensing technology, is also known as imaging spectral remote sensing technology. It is based on spectroscopy, in the 400~2500nm wavelength range, the spectral resolution is less than 10nm image data, its data often contain three kinds of information, space, radiation and spectrum. The hyperspectral image has both optical properties and spectral recognition ability. The rich spectral data made it possible to measure ground objects quantitatively, which has gradually become a hot spot in the field of remote sensing research and application, and has been widely used in environmental investigation and monitoring, mineral exploration, Hyperspectral remote sensing mapping of altered minerals is the key of hyperspectral data processing, which directly affects the accuracy and requirements of mapping results. This paper mainly focuses on the mechanism and application of mapping algorithm. Firstly, starting with the mechanism of spectral characteristics of ground objects, the causes of spectral characteristics of common altered minerals are summarized. The spectral characteristics of the ground objects can be judged according to their different components, and the common carbonation can be summarized. The concept and principle of several commonly used hyperspectral mapping algorithms are introduced in detail. The methods of spectral feature extraction are summarized. The performance and accuracy of spectral angle mapping method (SAM), spectral information divergence method (SIDM) and mixed modulation matched filtering method (MTMF) are evaluated by constructing simulated data. The noise of the data will have a great influence on the mapping accuracy of several methods. Therefore, the process and main methods of hyperspectral data processing are expounded for the noisy images which need to be de-noised before mapping. Taking the SASI hyperspectral data in the study area as an example, based on hydrocarbon microleakage theory, a mapping method based on "characteristic spectral mask MTMF" is proposed. The information of hydrocarbon, clay and carbonate alteration anomalies in the study area is extracted. The interference factors are eliminated effectively, and good results are obtained by combining the existing geological data and field measurement spectra.
【學(xué)位授予單位】：成都理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：P627

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