本文選題：遙感數(shù)據(jù)　切入點：影像修復　出處：《武漢大學》2016年博士論文

【摘要】：隨著衛(wèi)星和傳感器技術的不斷創(chuàng)新,越來越多的遙感衛(wèi)星觀測數(shù)據(jù)得以獲取。其中,遙感時間序列數(shù)據(jù)被廣泛應用于區(qū)域以及全球環(huán)境變化研究中。隨著研究的深度開展,對遙感時間序列數(shù)據(jù)時空連續(xù)性和完整性的要求越來越高。但是由于在數(shù)據(jù)獲取的過程中,不可避免的會受到觀測條件和傳感器故障等因素的影響造成大量信息缺失,使得遙感時間序列數(shù)據(jù)呈現(xiàn)時間不連續(xù)、空間不完整狀態(tài),嚴重的阻礙了數(shù)據(jù)的進一步應用。如何在現(xiàn)有觀測條件下,利用已有的遙感時間序列數(shù)據(jù)重建出高質(zhì)量的時空連續(xù)的、完整的遙感時間序列數(shù)據(jù)促進了時域濾波和時域重建技術的發(fā)展。本文以提高遙感時間序列數(shù)據(jù)的時空連續(xù)性和完整性為主線,針對遙感時間序列數(shù)據(jù)產(chǎn)品中存在的問題和當下現(xiàn)有的時域濾波和時域重建方法的缺陷與不足,提出新的時域濾波和時域重建算法,以重建出高質(zhì)量的遙感時間序列數(shù)據(jù)。本文主要工作總結(jié)為以下幾方面：(1)以提高遙感時間序列數(shù)據(jù)的時間連續(xù)性和空間完整性為主線,分析了當下遙感時間序列數(shù)據(jù)產(chǎn)品存在的問題和遙感影像修復方法的研究現(xiàn)狀,總結(jié)了它們在實際應用中存在的缺陷與不足,提出本文的研究目標。并且具體介紹了當前的時域濾波和時域重建算法以及論文中用到的評價方法與指標。(2)提出移動加權(quán)諧波分析的NDVI時域濾波方法。為了改善諧波分析方法(HANTS)重建結(jié)果出現(xiàn)過度擬合或過度平滑的現(xiàn)象,本文在原方法的基礎上引入移動支持域,對時間序列數(shù)據(jù)進行移動加權(quán)局部處理。在每一個移動支持域中,通過三次樣條法為每個數(shù)據(jù)點分配權(quán)值。在每個移動支持域中對數(shù)據(jù)進行擬合,并且通過權(quán)值分配控制參考數(shù)據(jù)對重建數(shù)據(jù)的影響程度：同時由于在移動支持域內(nèi)待擬合數(shù)據(jù)少,使得諧波個數(shù)更加容易確定。此外,本文針對NDVI時間序列數(shù)據(jù)的特點設計四步處理流程對其進行處理,使得重建數(shù)據(jù)逼近原始NDVI的上包絡線,從而更精確的獲得植被的真實變化趨勢。實驗證明,該方法不僅可以很好的識別噪聲點并且使得重建結(jié)果逼近NDVI時間序列的上包絡線；還能夠正確的估計植被休眠期的NDVI值,很好的處理NDVI時間序列中出現(xiàn)連續(xù)波動的現(xiàn)象,在絕大多數(shù)情況下魯棒性強。(3)提出了諧波分析與泊松方程協(xié)同的地表反射率時域重建方法。針對已有方法無法有效的實現(xiàn)對每天數(shù)據(jù)的重建這一缺陷,本文提出的時域重建方法不僅可以重建每天的反射率時間序列數(shù)據(jù),而且在保留未缺失區(qū)域原始值的前提下只對缺失區(qū)域進行填補,實現(xiàn)了真正意義的時域重建。主要思想是首先通過多年數(shù)據(jù)間的聯(lián)合加權(quán)平均對待重建年份的缺失數(shù)據(jù)進行初步填補,為時間域重建提供足夠的初始值；基于這些初始值通過時域濾波算法對第一步未填補的區(qū)域進行填補,同時對已經(jīng)填補的區(qū)域進行調(diào)整；最后通過泊松圖像編輯對修復區(qū)域的值進行調(diào)整,實現(xiàn)重建數(shù)據(jù)的空間無縫。實驗結(jié)果表明該方法可以重建出每天的時空連續(xù)的地表反射率產(chǎn)品,不僅能夠保持數(shù)據(jù)時域的連續(xù)性,也能保證數(shù)據(jù)空間的完整性,同時,重建的地表反射率數(shù)據(jù)也保持了光譜的完整性。(4)提出了顧及物理約束的地表溫度時域重建方法�？紤]到云層會對地表溫度產(chǎn)生影響,本論文提出在地表溫度數(shù)據(jù)的重建過程中充分考慮到云層對地表溫度的影響,耦合能表現(xiàn)反映影響程度的物理量,通過物理約束手段重建出更符合真實情況的地表溫度產(chǎn)品。該方法首先依據(jù)遙感時間序列產(chǎn)品時間上的依存性重建出晴空條件下高質(zhì)量產(chǎn)品,然后建立物理約束輔助數(shù)據(jù)與待重建數(shù)據(jù)之間的關系,通過對關系模型參數(shù)進行高精度訓練,將云覆蓋區(qū)域的信息進行重建。實驗結(jié)果表明該方法不僅可以提高晴空條件下質(zhì)量低的像元的質(zhì)量,而且可以對云覆蓋區(qū)域的像元進行高精度的重建,最終重建出高質(zhì)量的每天的地表溫度數(shù)據(jù)。
[Abstract]:With the continuous innovation of satellite and sensor technology, remote sensing satellite data to get more and more. Among them, the remote sensing data of time series is widely used in regional and global environmental change research. With the depth of research carried out on the data of time series remote sensing, spatial continuity and integrity of the increasingly high demand. But in due process the data acquisition, will be influenced by the observation condition and sensor fault caused by a large number of factors such as lack of information, showing the time discontinuous remote sensing data of time series, space is not complete, seriously hinder the further application of data. How the existing observation condition, using the remote sensing data of time series reconstruction in time and space the high quality of the continuous, remote sensing time series data integrity and promote the development of time domain filtering and time domain reconstruction technology. In this paper. High spatial remote sensing data of time series continuity and integrity as the main line, aiming at the existing defects of remote sensing data products in time series and the existing time-domain filtering and time domain reconstruction method and the insufficiency, proposed time-domain filtering and time domain reconstruction algorithm of the remote sensing data of time series to reconstruct high quality. This paper the work summarized as follows: (1) to improve the remote sensing data of time series time continuity and spatial integrity as the main line, analyzes the research status of the existing remote sensing data of time series products and remote sensing image restoration method, summarizes their shortcomings in the practical application and the insufficiency, puts forward the research target in this paper. And introduces the specific evaluation methods and indicators used in the time domain and time domain filtering and reconstruction algorithm in this paper. (2) proposed moving weighted harmonic analysis ND VI time domain filtering method. In order to improve the harmonic analysis method (HANTS) reconstruction results over fitting or over smoothing phenomenon, this paper introduces the mobile support domain on the basis of the original method, the time series data of mobile weighted local processing. In each mobile support domain, through the three spline method for each data point distribution weights. In each mobile support for data fitting in the domain, and the distribution of weight control reference data impact on the reconstruction data. At the same time because in the mobile support domain to fit the data, the number of harmonic is more easily determined. In addition, the four step process to process it according to the characteristics of NDVI time sequence data design, making the reconstruction of data envelope approximation of the original NDVI, so as to obtain more accurate vegetation real trend. The experimental results show that this method not only can be very good On the envelope of noise and the reconstruction results approach NDVI time series; also can estimate the correct vegetation dormancy period NDVI, continuous wave phenomena appear NDVI time series well, in most cases robust. (3) proposed the surface reflectance time domain reconstruction method for harmonic coordination wave analysis and Poisson equation. Because the existing methods can not effectively realize the reconstruction of the defect data every day, the time domain reconstruction method proposed in this paper can not only reflectance time series data reconstruction every day, and keeping the original value under the missing regions not only to fill the missing regions, realize the true meaning of the time domain reconstruction the main idea is the lack of data. Firstly, combined with weighted data between the average years of reconstruction years were preliminarily treated filled, for the time domain reconstruction early enough Initial value; these initial values of the first step of filling the area filled by temporal filtering algorithm based on simultaneous adjustment on the fill area; finally, Poisson image editing to adjust the value of the repair area, realize the reconstruction of data space seamlessly. Experimental results show that this method can reconstruct the continuous time every day the surface reflectance products, not only can maintain the continuity of data in the time domain, but also to ensure the integrity of the data space, at the same time, the surface reflectance data reconstruction also maintain the integrity of the spectrum. (4) the surface temperature time domain reconstruction method and Gu physical constraints. Considering the clouds will affect the surface temperature. The paper proposes the reconstruction process of surface temperature data in full consideration of the effect of clouds on the surface temperature, the coupling can reflect the influence degree of physical quantity, through physical ca. Beam means to rebuild more in line with the surface temperature product in the real situation. The method based on remote sensing time series on the time dependence of the reconstruction of high quality products under the clear sky condition, and then the relationship between the establishment of physical constraints and auxiliary data to be reconstructed data, through high precision training parameters of the relationship model, will rebuild information the cloud coverage area. The experimental results show that this method can not only improve the quality of low quality of the pixels under the clear sky condition, but also can be used for high precision reconstruction of pixel cloud coverage, finally reconstruct the surface temperature data of high quality every day.

【學位授予單位】：武漢大學
【學位級別】：博士
【學位授予年份】：2016
【分類號】：P237
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本文編號：1655225