博碩士論文 100623010 詳細資訊




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姓名 林成峯(Cheng-Feng Lin)  查詢紙本館藏   畢業系所 太空科學研究所
論文名稱 利用MHE對多光譜影像輻射校正並 應用於土石流變遷偵測
(Landslide Detection with Multi-Dimensional Histogram Equalization for Multispectral Remotely Sensed Imagery)
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摘要(中) 台灣位在地震活躍區,東臨環太平洋火山帶,西臨菲律賓海板塊,其以每年平均82mm朝西北碰撞歐亞板塊,因此地震頻繁,且台灣每年夏秋兩季會有數個颱風經過,然而伴隨颱風所帶來的大雨以及地震都可能會造成嚴重的土石流或是山崩等自然災害,因此,土石流的變遷偵測對於災後重建或是災害評估就顯得非常有用。
變遷偵測是遙測科技中一項應用相當廣泛的技術,除了應用在變遷偵測之外,都市發展或是農業管理也常使用,通常我們可以比較兩張不同時期相同位置的多光譜影像就能得知前後的差異,然而不同時期拍攝的影像,他們的大氣條件並不完全相同,大氣條件可能包括太陽照度、大氣輻射和大氣灰霾等等,而這些差異可能會使相同位置影像中相同的物質卻有不同的光譜,造成後續影像處理增加誤差,因此在進行變遷偵測之前須要對影像作輻射校正,本文中我們提出利用多維的直方圖均值法對影像作前處理,目的在於修正多光譜影像中不同的大氣條件,讓不同時期相同位置的多光譜影像中相同的物質能有近似的光譜。
研究中採用SPOT的多光譜影像進行前處理的步驟,接著再利用非監督式分類法對影像分類,比較修正前後的影像是否可以成功降低分類的錯誤率,得到更精確的變遷結果。
摘要(英) Taiwan is located at Circum-Pacific seismic zone; therefore there are a lot of earthquakes in this region. Besides, in this subtropical region, there are usually several typhoons pass through each year. These two natural phenomena may cause serious landslides in the mountainous regions. For landslides hazard assessment, change detection with remote sensing images is an efficient and effective approach.
Change detection is one of the most important applications of remote sensing technique, and it provides useful information for various applications, including disaster monitoring, urban development and agriculture management. Compare two images collected at different time from same located, the ground surface change can be detected. However, the difference in spectrum may not solely result from the changes on the ground. The spectrum of the same material in two remote sensing images may not be the same due to the different condition of solar illumination and atmosphere condition while the images were obtained. Therefore, radiometric calibration is required before applying the change detection algorithm and comparing the spectrum.
In this study, we propose a multi-dimensional histogram equalization algorithm as a pre-process step for relative calibration. It modifies multispectral images collected under different atmospheric conditions to have similar spectrum for the same land cover. A set of SPOT images is adopted for experiments and results show the proposed method can reduce the misclassification rate.
關鍵字(中) ★ 輻射效正
★ 變遷偵測
★ 影像分類
關鍵字(英) ★ Radiometric Calibration
★ Change Detection
★ Classification
論文目次 Contents
摘要 i
Abstract ii
Contents iii
List of Tables v
List of Figures vi
Chapter 1 Introduction 1
1.1 Motivation 2
1.2 Flowchart 3
1.3 These Organization 4
Chapter 2 Review 5
2.1 Linear radiometric calibration methods 5
2.1.1 Mean and variance method (MV) 6
2.1.2 Whitening/dewhitening transform (WD) 7
2.2 Nonlinear radiometric calibration method 8
2.2.1 Histogram processing 9
Chapter 3 Method 10
3.1 Multi-dimensional histogram equalization 10
3.2 Rotation matrix 13
3.3 Kullback-Leibler distance 14
3.4 Unsupervised Classification 15
3.5 Image difference 17
Chapter 4 Experiment Result 18
4.1 Data source 18
4.2 Image pre-processing 23
4.3 Experiment results 23
Chapter 5 Conclusions and Future work 39
References 41
參考文獻 [1] Richards, J.A. and X.P. Jia, Remote Sensing Digital Image Analysis: An Introduction, 4th edition, 2005.
[2] Chang, C.I., Hyperspectral Imaging: Techniques for Spectral Detection and Classification, 2003.
[3] Lillesane, T.M., R.W. Kiefer, and J.W. Chipman, Remote Sensing and Image Interpretation, 5th edition, 2003.
[4] Heo, J. and T. W. Fitzhugh, “A standardized radiometric normalization method for change detection using remotely sensed imagery”, Photogramm. Eng. Remote Sens., vol. 66, no. 2, pp. 173–181, Feb. 2000.
[5] 梁維真, 基於色彩校正的遙測影像變遷偵測. 國立中央大學碩士論文, 2011.
[6] Mayer, R., F. Bucholtz, D. Scribner, and M. Kruer, “A Family of Spectral Target Signature Transforms: Relationship to the Past, New Transforms, and Sensitivity Tests”, IEEE Trans. Geosci. Remote Sensing Lett., vol. 1,pp.26-30, Jan. 2004.
[7] Mayer, R. and F. Bucholtz, “Object Detection by Using Whitening/Dewhitening to Transform Target Signature in Multitemporal Hyperspectral and Multispectral Imagery”, IEEE. Trans. Geosci. Remote Sensing, vol. 40, no. 4, pp.831-840, Apr. 2002.
[8] Gonzalez, R. and Woods, R., Digital Image Processing, 2nd edition, 2002.
[9] Chen, H.T. and H. Ren, “Using Multidimensional Histogram Equalization As Relative Radiometric Calibration for Change Detection in Remote Sensing Imagery”, Oral session at Asian Conference on Remote Sensing, Colombo, Sri Lanka, 2008.
[10] Inamdar, S., F. Bovolo, L. Bruzzone and S. Chaudhuri, “Multidimensional probability density function matching for preprocessing of multitemporal remote sensing images”, IEEE Trans. Geosci. Remote Sens., vol. 46, pp.1243-1252, April 2008.
[11] Pitié, F., A. Kokaram, and R. Dahyot, “Automated colour grading using colour distribution transfer”, Comput. Vis. Image Underst., vol. 107, no. 1/2, pp. 123–137, Jul./Aug 2007.
[12] Pitié, F., A. Kokaram, and R. Dahyot, “N-dimensional probability function transfer and its application to color transfer”, in Proc. IEEE Int. Conf. Comput. Vis., 17–21, vol. 2, pp. 1434–1439, Oct 2005.
[13] Aguilera, A. and R. Perez-Aguila, “General n-dimensional rotations”, in Proc. WSCG SHORT Commun. Papers., pp. 1–8, February 2004
[14] SHLENS, J, “Notes on Kullback-Leibler Divergence and Likelihood Theory”, Systems Neurobiology Laboratory, Salk Institute for Biological Studies, La Jolla, CA 92037, 2007.
指導教授 任玄(Hsuan Ren) 審核日期 2013-7-29
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