本文爲意大利特倫託大學（作者：Massimo Zanetti）的博士論文，共198頁。
新一代遙感衛星的多光譜圖像越來越多，爲地球觀測和監測提供了前所未有的信息來源。現在，多光譜圖像可以以高分辨率（幾乎）覆蓋所有陸地表面，而且回訪時間極短（最多幾天），這使得繪製全球變化圖成爲可能。從如此龐大的數據中提取有用的信息需要在幾乎所有的應用環境中系統地使用自動技術。在某些情況下，嚴格的應用要求迫使實踐者在處理鏈的研究中開發強大的數據驅動方法。因此，所採用的理論模型與求解的物理意義之間的確切關係有時隱藏在數據分析技術中，或者根本不清楚。儘管這並不是應用程序本身成功的限制，但它使得從一個特定問題學到的知識很難轉移到另一個問題。
本文主要針對這一問題，提出了多光譜圖像表示與分析的一般數學框架。然後將所提出的模型應用於變化檢測的應用環境中。這裏所提出模型的普遍性使我們能夠：（1）對現有的變化檢測方法提供數學解釋，並且（2）將它們擴展到更一般的情況，以解決日益複雜的問題。上一代多光譜圖像的典型空間/光譜特性強調了需要有更靈活的模型來表示圖像。事實上，在前幾代多光譜圖像上運行良好的經典變化檢測方法，由於其對上一代產品中所有複雜光譜/空間細節的建模能力較差，只是提供了次優結果。本文提出的理論模型旨在爲圖像的表示提供更多的自由度。通過對合成數據集和真實多光譜圖像的實驗，證明了所提出的新方法和相關技術的有效性。這裏所採用模型的改進靈活性允許更好地表示數據，並使變化檢測性能得到實質性改進。
The increasing availability of newgeneration remote sensing satellite multispectral images provides anunprecedented source of information for Earth observation and monitoring.Multispectral images can be now collected at high resolution covering (almost)all land surfaces with extremely short revisit time (up to a few days), makingit possible the mapping of global changes. Extracting useful information fromsuch huge amount of data requires a systematic use of automatic techiques inalmost all applicative contexts. In some cases, the strict applicationrequirements force the pratictioner to develop strongly data-driven approachesin the development of the processing chain. As a consequence, the exactrelationship between the theoretical models adopted and the physical meaning ofthe solutions is sometimes hidden in the data analysis techniques, or not clearat all. Altough this is not a limitation for the success of the applicationitself, it makes however difficult to transfer the knowledge learned from onespecific problem to another. In this thesis we mainly focus on this aspect andwe propose a general mathematical framework for the representation and analysisof multispectral images. The proposed models are then used in the applicativecontext of change detection. Here, the generality of the proposed models allowsus to both: (1) provide a mathematical explanation of already existingmethodologies for change detection, and (2) extend them to more general casesfor addressing problems of increasing complexity. Typical spatial/spectralproperties of last generation multispectral images emphasize the need of havingmore flexible models to image representation. In fact, classical methods tochange detection that have worked well on previous generations of multispectralimages provide sub-optimal results due to their poor capability of modeling allthe complex spectral/spatial detail available in last generation products. Thetheoretical models presented in this thesis are aimed at giving more degrees offreedom in the representation of the images. The effectiveness of the proposednovel approaches and related techniques is demonstrated on several experimentsinvolving both synthetic datasets and real multispectral images. Here, theimproved flexibility of the models adopted allows for a better representationof the data and is always followed by a substantial improvement of the changedetection performance.
- 引言
- 項目背景
- 變分泛函圖像逼近的數值最小化
- 向量值圖像和曲線的變分逼近
- 背景介紹
- 用於二元變化檢測的Rayleigh-Rice混合模型
- 一種用於變化檢測的複合多類混合模型
- 基於自由間斷模型的多光譜圖像變化檢測的類空間上下文方法
- 結論與未來展望
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