Thesis (PDF) - Signal & Image Processing Lab

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2 ABSTRACT arises, when applying erosion and opening based on the semilattice, is studied. Possi- ble solutions for the trench problem are proposed. Moreover, the trenches are used in order to exploit the implicit segmentation property of the Extrema-Watershed Tree.
Page 1 and 2: SELF-DUAL MORPHOLOGICAL OPERATORS B
Page 3 and 4: The Research Thesis was done under
Page 5 and 6: iv CONTENTS 3 Implementation of BTV
Page 7 and 8: List of Tables 2.1 The BTV transfor
Page 9 and 10: viii LIST OF FIGURES 2.9 An example
Page 11 and 12: x LIST OF FIGURES 4.17 A Simba imag
Page 13 and 14: xii LIST OF FIGURES 6.20 A Lena ima
Page 15: Abstract This research addresses a
Page 19 and 20: Chapter 1 Introduction 1.1 Self-Dua
Page 21 and 22: 1.2. BACKGROUND AND MOTIVATION 7 (a
Page 23 and 24: 1.4. SUMMARY AND THESIS ORGANIZATIO
Page 25 and 26: 1.4. SUMMARY AND THESIS ORGANIZATIO
Page 27 and 28: 2.2. KNOWN TREE REPRESENTATIONS 13
Page 33 and 34: 2.3. THEORETICAL BACKGROUND ON SEMI
Page 35 and 36: 2.3. THEORETICAL BACKGROUND ON SEMI
Page 37 and 38: 2.4. SHAPE TREE SEMILATTICE BACKGRO
Page 45 and 46: 2.5. ALTERNATING SEQUENCES SEMILATT
Page 51 and 52: Chapter 3 Implementation of BTVT In
Page 53 and 54: 3.2. TOPOGRAPHIC DISTANCE TREE IMPL
Page 55 and 56: 3.3. IMPLEMENTATION OF THE BTV TRAN
Page 57 and 58: 3.3. IMPLEMENTATION OF THE BTV TRAN
Page 59 and 60: (a) (b) Figure 4.1: Result of BTV-b
Page 61 and 62: the number of gray levels is high,
Page 63 and 64: 4.1. FILTERING USING AN ADAPTIVE ST
Page 65 and 66: 4.1. FILTERING USING AN ADAPTIVE ST
Page 67 and 68:
4.2. FILTERING USING MULTIPLE MINIM
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4.3. FILTERING USING A COMBINED MET
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4.4. RESULTS COMPARISON 57 (a) (b)
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4.4. RESULTS COMPARISON 59 (a) (b)
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4.4. RESULTS COMPARISON 61 Figure 4
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5.1. THE COMPLETE INF-SEMILATTICE O
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5.2. IMAGE PROCESSING ON TREE SEMIL
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5.2. IMAGE PROCESSING ON TREE SEMIL
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5.4. SUMMARY AND DISCUSSION 73 by t
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Chapter 6 Extrema-Watershed Tree ex
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6.1. EXTREMA WATERSHED TREE DESCRIP
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6.2. MORPHOLOGICAL OPERATIONS ON TH
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6.3. STUDY OF EWT PROPERTIES 89 (a)
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6.3. STUDY OF EWT PROPERTIES 97 Fig
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6.4. APPLICATION EXAMPLES 99 6.4 Ap
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6.4. APPLICATION EXAMPLES 101 Figur
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6.4. APPLICATION EXAMPLES 103 Figur
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6.4. APPLICATION EXAMPLES 105 6.4.3
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6.4. APPLICATION EXAMPLES 107 (a) (
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6.4. APPLICATION EXAMPLES 109 (a) (
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6.5. EWT CONCLUSIONS 111 6.5 EWT co
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7.2. FURTHER RESEARCH TOPICS 113 us
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Algorithm 4 RAG image representatio
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BIBLIOGRAPHY 117 [10] Philippe Sale
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