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系統識別號 U0026-2707201119102700
論文名稱(中文) 空照影像陰影區塊之偵測和色彩修復之研究
論文名稱(英文) A Study on Detection and Color Restoration of Shadowed Areas in Aerial Images
校院名稱 成功大學
系所名稱(中) 測量及空間資訊學系碩博士班
系所名稱(英) Department of Geomatics
學年度 99
學期 2
出版年 100
研究生(中文) 張志瑋
研究生(英文) Chih-Wei Chang
學號 p6697111
學位類別 碩士
語文別 英文
論文頁數 94頁
口試委員 指導教授-蔡展榮
口試委員-吳究
口試委員-陳良健
口試委員-蔡榮得
中文關鍵字 陰影偵測  色彩修復  主成分 
英文關鍵字 shadow detection  color restoration  principal component 
學科別分類
中文摘要 光照和地面反射被視為影像中每個像元的強度值的函數。事實上,當光線照射到像是建物、樹木等地表物時,會產生陰影和遮蔽,很難有效修復陰影區原本的紋理和色彩資訊,也很難妥善移除陰影,許多細部的資訊因此變得隱密或是遺失,更甚者,錯誤的色調、形狀變形、陰影區內部精確的影像匹配,在在都影響著影像的辨識。然而,部分陰影區中的亮度或色彩仍可以提供有效的色彩回復資訊,降低或補償陰影所造成的影響並取得所需的陰影區內部的資訊,具有一定的必要性。主成分分析法被廣泛地運用在影像或區域的描述上,本研究利用R、G、B以及NIR四個波段作為輸入資料,利用主成分差值法,在大部分的區域中,發現陰影偵測可以得到超過90%的精確度。除此之外,比較了直方圖匹配法和局部統計法分別在RGB和IHS波段下所得到的色彩修復效果,發現在RGB波段下進行直方圖匹配得到的結果具有最好的視覺效果。
英文摘要 The illumination and ground reflection are considered as functions of the variable of the intensity value on each image pixel. In fact, light cast on terrain objects such as buildings and trees would cause shadows and occlusion. It is hard to recover original textures and color information in shadowed region or eliminate shadows. Many detail information is hidden or lost due to such problems. Moreover, false color tone, shape distortion and inaccurate image matching within shadowed areas also infect image recognition. However, the brightness and color information is sufficient to offer color restoration in some shadow areas. It is necessary to reduce or compensate the effect caused by shadow, and get information needed. Therefore, it’s important to figure out a useful and practical method to improve the efficiency and accuracy. Principal component analysis has been widely used for images or region’s description. In this thesis, the experiments show the effectiveness of the principal component differential method with input data R, G, B, and NIR bands. In most cases, the overall accuracy can reach better than 90%. Besides, this research also compares the results of color restoration that applied histogram matching and local statistics methods to shadow areas in RGB and HSI channels. The results show that histogram matching with RGB channels can provide the best visual quality.
論文目次 摘要 I
Abstract II
Acknowledgement III
Content IV
List of Figures VI
List of Tables X
Chapter 1 Introduction 1
1.1 Motivation and Purpose 1
1.2 Related Work 3
1.2.1 Shadow Detection 3
1.2.2 Color Restoration in Shadowed Areas 5
1.3 Frame of Thesis 6
Chapter 2 Formation and Properties of Shadow 8
2.1 Illumination Model 8
2.2 Color Model 9
2.2.1 RGB Color Model 10
2.2.2 HSI Color Model 11
2.3 Properties of Shadow 14
Chapter 3 Algorithms for Shadow Detection and Color Restoration in Shadow Areas 16
3.1 Shadow Detection Methods 16
3.1.1 Principal Component (PC) Differential Method 16
3.1.2 Spectral Ratioing Technique 25
3.2 Color Restoration in Shadow Areas 25
3.2.1 Histogram Matching 26
3.2.2 Local Statistics Method 27
3.3 Post Processing Methods 28
3.3.1 Accuracy Evaluation 28
3.3.2 Quality Assessment (Texture Descriptors) 30
3.4 Workflow 31
Chapter 4 Experimental Result and Analysis 34
4.1 Study Areas 34
4.2 Results of Shadow Detection 39
4.2.1 Subjective Evaluation 39
4.2.2 Objective Evaluation 40
4.3 Results of Color Restoration in Shadow Areas 65
Chapter 5 Conclusions 88
References 91

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