隨著測量技術的發展，衛星影像在觀測地球表面相關應用方面一直都是相當重要的資料之一，近年來已廣泛的應用在自然科學、環境探測、軍事監控、土地利用與規畫等領域，然而，衛星影像各波段會受到雲層阻擋，使得影像無法呈現完整的地表資訊，因此雲遮蔽是目前衛星影像在使用上的一大問題。本文提出一衛星影像雲層遮蔽區域之移除與填補演算法，一張有雲遮蔽的衛星影像，藉由其前後相鄰時間的影像資訊進行套合填補，產生一無雲遮蔽的衛星影像。本研究首先使用監督式分類(supervised classification)方法尋找雲遮蔽區，接著以本研究所提出的無縫鑲嵌技術，以不同時期衛星影像資訊對遮蔽區域進行資訊填補，在多時期衛星影像選取方面，藉由影像品質評估方法，選取適合的候選影像以進行資料填補，在資料填補方面，本文提出解帕森方程式(poisson equation)的自動化無縫遮蔽區域填補演算法，最後依影像品質，評估填補區域的相似度，以提供後續資料使用上的一項參考指標。本研究的實驗影像為Landsat 7衛星影像，實驗過程中，對於各種不同類型的地區進行測試，並且測試本方法是否可處理含有高覆蓋率雲量之影像，根據實驗結果顯示，本方法可應用在不同特性之區域，並且可成功處理大量的雲層遮蔽之衛星影像。

With the development of surveying technique, satellite images play a key role in surveying earth surface and recently have a widespread use in many applications such as natural science, environment detection, military monitoring, land use and land planning. However, the cloud cover will be a problem in the usage of optical images. The ground information in the regions covered by cloud will miss. Thus, cloud detection and removing is a fundamental and important research issue with many applications in the field of geodesic and remote sensing. In this thesis, a novel cloud removing algorithm is introduced to generate cloud-free and even cloud shadow-free images from multi-temporal remote-sensing images. The basic idea of the proposed approach is to seamless replace the cloud-covered regions by other images. First, a supervised classification approach is adopted to detect clouds. To replace the regions with clouds, an image quality assessment is adopted to select a corresponding and cloud-free region from the temporal images. The problem of seamless replacement is regarded as an optimization problem and modeled by a Poisson equation. By minimizing the Poisson equation, a seamless replacement which minimizes the difference between the cloud region and cloud-free corresponding region can be obtained. Moreover, an index of quality assessment of replacement regions is provided for the users using the generated cloud-free data. In the experiments, the Landsat-7 satellite images with various types of lands are tested. The experiment results show that, the proposed approach can work well on images with persistent and extensive cloud covers.

Akaike H.. Information theory and an extension of the maximum likelihood principle, in B.N. Petrov and F. Csaki, Eds., Second International Symposium on Information Theory, Akademiai Kiado, (Budapest, Hungary), 267-281, 1973.
Chuang Y.-Y., Curless B., Salesin D. H. and Szeliski R.. A bayesian approach to digital matting, Proc. of CVPR2001, Vol. II, pp. 264-271, 2001.
Feng C., Ma J.-W., Dai Q. and Chen X.. An improved method for cloud removal in ASTER data change detection, Proc. IEEE Int. Geoscience and Remote Sensing Sym., Vol. 5, pp. 3387-3389, 2004.
Gotoh, Kazuo and Fujii Y.. A Fractal Dimensional Analysis on the Cloud Shape Parameters of Cumulus over Land. Journal of Applied Meteorology, Vol. 37(10), pp. 1283-1292, 1998.
Gonzalez R.C. and Woods R.E.. Digital Image Processing. 2nd Edition. Prentice-Hall, Upper Saddle River, NJ, 2002.
Gabarda S. and Cristóbal G.. Cloud covering denoising through image fusion, Image Vision Comput, Vol. 25, pp. 523-530, 2007.
Haralick R.M., Sternberg S.R., and Zhuang X.. Image Analysis Using Mathematical Morphology, IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 9, no. 4, pp. 532-550, 1987.
Hu Y.H., Lee H.B. and Scarpace F.L.. Optimal linear spectral unmixing, IEEE Trans. Geosci. Remote Sens., Vol. 37, pp. 639-644, 1999.
Helmer E.H. and Ruefenacht B.. Cloud-free satellite image mosaics with regression trees and histogram matching, Photogram. Eng. Remote Sens, Vol. 71 (9) ,pp. 1079-1089, 2005.
Jiao. Q., Luo. W., Liu. X. and Zhang. B.. Information reconstruction in the cloud removing area based on multitemporal. Proc. Remote Sensing and GIS Data Processing and Applications, SPIE Vol. 6790, 679029-1. , 2007.
Liew S.C., Li M. and Kwoh L.K., Chen P., Lim H.. Cloud-free multi-scene mosaics of SPOT images, Proc. 1998 IEEE Int’l Geoscience and Remote Sensing Sym., 1998.
Liew S.C., Li M. and Kwoh L.K.. Generating cloud free and cloud-shadow free mosaic for SPOT panchromatic images, Proc. IEEE Int’l Geoscience and Remote Sensing Sym., 2002.
Lillesand. T.M. and Kiefer. R. W.. Remote Sensing and Image Interpretation, Fourth Edition, John Wiley and Sons, ISBN 9971-51-427-3, 2002.
Liew S.C., Li M. and Kwoh L.K.. Producing cloud free and cloud-shadow free mosaic from cloudy IKONOS images, Proc. 2003 IEEE Int’l Geoscience and Remote Sensing Sym., 2003.
Otsu, N.. A threshold selection method from gray-level histograms, IEEE Transactions on System, Man, and Cybernetic, Vol. 9, pp. 62-69., 1979.
Perez. P., Gangnet. M. and Blake.A.. Poisson Image Editing. ACM Transactions on Graphics, Vol. 22(3), pp. 313-318, 2003.
Tseng D. C., Tseng H. T. and Chien C. L.. Automatic cloud removal from multi-temporal SPOT images, Applied Mathematics and Computation, Vol. 205, pp. 584-600, 2008.
Wang Z., Bovik A. C., Sheikh H. R. and Simoncelli E. P.. Image Quality Assessment: From Error Visibility to Structural Similarity. IEEE Transactions on Image Processing, Vol. 13(4), pp. 1-14, 2004.
Wang Z., Jin J., Liang J., Yan K. and Peng Q.. A new cloud removal algorithm for multi-spectral images, Proc. SAR and Multispectral Image Processing (MIPPR), SPIE Vol. 6043, 2005.
Zhang Y., Rossow W. B., Lacis A. A., Oinas V. and Mishchenko M. I. Calculation of radiative fluxes from the surface to top of atmosphere based on ISCCP and other global data sets: Refinements of the radiative transfer model and the input data, J. Geophys. Res., Vol. 109, No. 19, 2004.
王寶貫。雲物理學，渤海堂文化事業公司，1995。
李建成。一覽無遺─衛星遙測影像，科學發展，390，p. 14-17，2005。
徐百輝。大地的辨識密碼 高光譜影像，科學發展，416，p.13-19，2007。
陳繼藩。地理資訊系統(GIS)與遙感探測(RS)之整合應用，內政部國土資訊系統-教育訓練-國土資訊系統技術人員研討會，2007。
曾忠一。大氣衛星遙測學，渤海堂文化事業公司，1988。
曾忠一。大氣遙測原理與應用。中央氣象局，1983。
葉精國。自動化衛星影像雲及雲陰影遮蔽區偵測及復原之研究，國立中興大學土木工程學系碩士論文，2006。