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 Scope All of NCUIR College of Electrical Engineering & Computer Science    Graduate Institute of Computer Science and Information Engineering       --Electronic Thesis & Dissertation Tips: please add "double quotation mark" for query phrases to get precise resultsplease goto advance search for comprehansive author search Adv. Search

 Please use this identifier to cite or link to this item: `http://ir.lib.ncu.edu.tw/handle/987654321/8580`

 Title: 遙測影像處理與地貌辨識;Remote-sensing image processing and recognition using wavelet transform and Hausdorff distance Authors: 鄧宜珍;Yi-Chen Teng Contributors: 資訊工程研究所 Keywords: 邊線擷取;影像比對;影像強化;小波轉換;遙測影像;影像處理;line-feature;wavelet transform;Hausdorff distance;remote-sensing image;image matching;image enhancement Date: 2002-06-27 Issue Date: 2009-09-22 11:30:59 (UTC+8) Publisher: 國立中央大學圖書館 Abstract: 如何從遙測影像中擷取有用的資訊來完成地貌辨識是本論文的研究主題。因此我們的研究內容共分為三大部分：(i) 影像強化，我們利用小波轉換的多重解析度特性，分別針對不同解析度的高頻係數，以小波收縮 (wavelet shrinkage) 去除雜訊，同時以Teager能量運算 (Teager energy operator) 強化較大區塊的邊線對比。(ii) 邊線擷取，主要在於邊線追蹤 (edge tracking) 與小波轉換的結合，利用多重解析度的高頻資訊作邊線追蹤，有效解決雜訊及邊線不連續的問題。 (iii) 以線段為特徵的影像比對，將線段轉換到不同的向量空間，以Hausdorff distance作為比對的方法，解決影像的旋轉、大小變化及位移等問題，達到可靠且有效的比對結果。 In this study, approaches of image enhancement, edge extraction, and line-based image matching for remote sensing images are proposed. The image enhancement includes noise reduction and contrast enhancement. We apply wavelet shrinkage techniques to suppress noise while preserving the sharpness of large-scale edges based on a Teager energy operator. The edge extraction contains wavelet-based edge detection and tracking. Wavelet transform provides multiresolution representation of images for robust tracking. The proposed edge detector consists of three modules: (i) starting point extraction and purgation for tracking, (ii) multiresolution gradient image generation, and (iii) multiresolution edge tracking. The image recognition approach matches line-based features using invariant Hausdorff distance. This approach matches two images and solves the problems of rotation, scaling, and translation transformations between these two images by applying the process of minimizing Hausdorff distance twice on the two sets of feature vectors. Appears in Collections: [Graduate Institute of Computer Science and Information Engineering] Electronic Thesis & Dissertation

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