Thesis (PDF) - Signal & Image Processing Lab

More documents

Recommendations

Info

78 CHAPTER 6. EXTREMA-WATERSHED TREE EXAMPLE arbitrary, because v1 and v8 have identical sizes and same gray level difference. The resulting tree is depicted in Fig. 6.3. Algorithm 2 Compare 2 extremum regions for a merge candidate selection function CompareExtrema(e1,e2) ⊲ e1 = (V 1 extr, V 1 2 ), e2 = (V 2 extr, V 2 2 ) ⊲ return value 0 means e1 is smaller,value 1 means e2 is smaller if Size(V 1 extr) < Size(V 2 extr) then return 0 else if Size(V 2 extr) < Size(V 1 extr) then return 1 else ⊲ sizes are equal ∆1 1 GL = |GL(Vextr) − GL(V 1 2 )| 2 = |GL(V 2 )| ∆2 GL extr) − GL(V 2 if ∆1 GL < ∆2GL then return 0 else return 1 end if end if end function 6.2 Morphological operations on the extrema-watershed tree As described in the Chapter 5, once a tree transform is defined, morphological operations (such as erosion and opening) in the tree-domain can be obtained. In this section, we investigate the results of applying this technique to the extrema-watershed tree. 6.2.1 Erosion and opening Consider the erosion and opening operators derived from the extrema-watershed tree, using the general framework developed in Chapter 5. In the following examples the two operators: erosion and opening are applied on synthetic and natural noisy and not noisy images.
6.2. MORPHOLOGICAL OPERATIONS ON THE EXTREMA-WATERSHED TREE 79 Figure 6.2: Example of extrema watershed tree creation.
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 and 16:
Abstract This research addresses a
Page 18 and 19:
4 List of Abbreviations and Symbols
Page 20 and 21:
6 CHAPTER 1. INTRODUCTION the image
Page 22 and 23:
8 CHAPTER 1. INTRODUCTION disadvant
Page 24 and 25:
10 CHAPTER 1. INTRODUCTION 3. A gen
Page 26 and 27:
Chapter 2 Theoretical Background 2.
Page 28 and 29:
14 CHAPTER 2. THEORETICAL BACKGROUN
Page 30 and 31:
Page 32 and 33:
Page 34 and 35:
Page 36 and 37:
Page 38 and 39:
Page 40 and 41:
Page 42 and 43: 28 CHAPTER 2. THEORETICAL BACKGROUN
Page 52 and 53: 38 CHAPTER 3. IMPLEMENTATION OF BTV
Page 58 and 59: Chapter 4 The “trench” problem
Page 60 and 61: 46CHAPTER 4. THE “TRENCH” PROBL
Page 76 and 77: Chapter 5 Tree Semilattices In this
Page 78 and 79: 64 CHAPTER 5. TREE SEMILATTICES sec
Page 80 and 81: 66 CHAPTER 5. TREE SEMILATTICES Fig
Page 82 and 83: 68 CHAPTER 5. TREE SEMILATTICES tre
Page 84 and 85: 70 CHAPTER 5. TREE SEMILATTICES If
Page 86 and 87: 72 CHAPTER 5. TREE SEMILATTICES sam
Page 88 and 89: 74 CHAPTER 5. TREE SEMILATTICES rep
Page 90 and 91: 76 CHAPTER 6. EXTREMA-WATERSHED TRE
Page 114 and 115: 100 CHAPTER 6. EXTREMA-WATERSHED TR
Page 126 and 127: Chapter 7 Conclusions and further r
Page 128 and 129: Appendix A 114
Page 130 and 131: Bibliography [1] J. Serra, Image An
Page 132: 118 BIBLIOGRAPHY [21] Renato Keshet
show all

Thesis (PDF) - Signal & Image Processing Lab

Create successful ePaper yourself

Delete template?

Save as template?