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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/11038

Title: 應用干涉雷達影像的多重解析度地形特徵萃取重建台灣西南地區新構造應力應變場
Neotectonic Stress/Strain Reconstruction by Means of Multi-resolution Lineament Feature Extraction of IFSAR Images---A Case Study at Southwest Taiwan
Authors: 吳宗達;陳錕山;張翠玉
Contributors: NTOU:Department of Electrical Engineering
國立臺灣海洋大學:電機工程學系
Keywords: 干涉合成孔徑雷達;線狀構造;小波轉換;多重解析度
IFSAR;Coefficient of variation detector;Hough transform;Dilation and erosion
Date: 2005-08
Issue Date: 2011-06-28T08:08:14Z
Abstract: 摘要:空載干涉合成孔徑雷達同時提供了地表散射影像以及數值地形模型,且影像解析度 與高層精度頗佳,對於地質構造中褶皺、斷層等等主要的地形特徵都能提供相當多的資 訊。然而要做到整體性觀察地質現象,除了觀測大尺度(巨觀)的山脈與山脊的延伸走向 外,亦有必要觀測小尺度(微觀)的區域性地質變形與褶曲,如此才能系統化的瞭解該區 新構造發育的情形,亦更能瞭解整體地質特性的全貌。本計劃即是使用台灣西南地區的 空載干涉雷達資料,透過多重解析度(multi-resolution)的影像處理技術,觀測不同尺度下 的地質褶皺與斷層特徵。再將不同尺度下所觀測到的資訊加以統計與分析,對應變形與 應力作用的物理模式,評估地殼內部應力應變的特性。本計劃將可以提供台灣西南地區 新構造應力應變的觀察資訊。 透過雷達影像處理的技術尋找大型山脊線狀構造時,小區域的褶曲結構往往成為影 像線形特徵萃取處理的干擾與雜訊。此時若合理的降低解析度且能保留大型邊緣特徵, 不但可以濾除干擾與雜訊,而且可以提升影像處理的速度。而在觀測局部系統性的地質 變形時,影像的小區域紋理結構就變得非常重要,在濾除雷達影像的斑駁雜訊(Speckle) 時盡量避免被破壞。本計劃將採用小波轉換(wavelet transform)做為多重解析度影像處理 技術,在不同解析度下強化應有的邊緣偵測以及線形特徵萃取能力,並達到自動化地質 線狀構造搜尋的目標。
ABSTRACT: Modern SAR interferometry (IFSAR) sensors delivering intensity images and corresponding digital terrain model (DTM) allow for a thorough surface lineament interpretation with the allweather day-night applicability. In this paper, an automatic linear-feature detection algorithm for high-resolution SAR images acquired in Taiwan is proposed. Methodologies to extract linear features consist of several stages. First, the image denoising techniques are used to remove the speckle noise on the raw image. In this stage, the Lee filter has been chosen because of its superior performance. After denoising, the Coefficient of Variation Detector is performed on the result images for edge enhancements and detection. Dilation and erosion techniques are used to reconnect the fragmented lines. The Hough transform, which is a special case of a more general transform known as Radon transform, is a suitable method for line detection in our analysis. Finally, linear features are extracted from the binary edge image. The last stage contains many substeps such as edge thinning and curve pruning.
Relation: NSC94-2116-M019-001
URI: http://ntour.ntou.edu.tw/ir/handle/987654321/11038
Appears in Collections:[電機工程學系] 研究計畫

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