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Some morphological operators in graph spaces Jean Cousty , Laurent Najman, and Jean Serra Workshop Honouring Professor Jean Serra October 26, 2010 - Bangalore, India J. Cousty, L. Najman and J. Serra : Some morphological operators in graph spaces


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Some morphological operators in graph spaces

Jean Cousty, Laurent Najman, and Jean Serra Workshop Honouring Professor Jean Serra

October 26, 2010 - Bangalore, India

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Historical background

Digital image processing

Transformations on the subsets of Z2 (binary images) Transformations on the maps from Z2 to N (grayscale images)

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Historical background

Digital image processing

Transformations on the subsets of Z2 (binary images) Transformations on the maps from Z2 to N (grayscale images)

Mathematical morphology

Filtering and segmenting tools very useful in applications Formally studied in lattices (e.g., 2|E|)

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More recently

Structured digital objects:

Points and Elements between points telling how points are “glued” together

For instance: Graph Simplicial complex Cubical complex

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More recently

Cousty et al., Watershed cuts: minimum spanning forests and the drop

  • f water principle TPAMI (2009)

Cousty et al., Watershed cuts: Thinnings, shortest-path forests and topological watersheds TPAMI 2010 Couprie and Bertrand, New characterizations of simple points in 2D, 3D and 4D discrete spaces, TPAMI (2009) Najman, Ultrametric Watersheds, ISMM (2009) Levillain et al., Milena: Write Generic Morphological Algorithms Once, Run on Many kinds of Images, ISMM (2009)

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Previous work: morphology on vertices of a graphs

Vincent, Graphs and Mathematical Morphology, SIGPROC 1989 Heijmans & Vincent, Graph Morphology in Image Analysis, in Mathematical Morphology in Image Processing, Marcel-Dekker, 1992

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Previous work: morphology on vertices of a graphs

Vincent, Graphs and Mathematical Morphology, SIGPROC 1989 Heijmans & Vincent, Graph Morphology in Image Analysis, in Mathematical Morphology in Image Processing, Marcel-Dekker, 1992

X (red & blue vertices)

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Previous work: morphology on vertices of a graphs

Vincent, Graphs and Mathematical Morphology, SIGPROC 1989 Heijmans & Vincent, Graph Morphology in Image Analysis, in Mathematical Morphology in Image Processing, Marcel-Dekker, 1992

X (red & blue vertices) δ(X) (red & blue vertices)

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Morphology in graphs

Problem The workspace being a graph

What morphological operators on subsets of its vertex set? What morphological operators on subsets of its edge set? What morphological operators on its subgraphs?

Relation between them?

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Outline

1 Lattice of graphs 2 Dilations and erosions 3 Filters

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Lattice of graphs

Ordering on graphs

A graph is a pair X = (X •, X ×) where X • is a set and X × is composed of unordered pairs of distinct elements in X • Definition Let X and Y be two graphs. If Y • ⊆ X • and Y × ⊆ X ×, then:

Y is a subgraph of X we write Y ⊑ X we say that Y is smaller than X and that X is greater than Y

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Lattice of graphs

Hereafter, the workspace is a graph G = (G•, G×) We consider the families G•, G× and G of respectively all subsets

  • f G•, all subsets of G× and all subgraphs of G.
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Lattice of graphs

Lattice of graphs

Property The set G of the subgraphs of G form a complete lattice The infimum and the supremum of any family F = {X1, . . . Xℓ}

  • f elements in G are given by:

⊓F = (

i∈[1,ℓ] Xi

  • ,

i∈[1,ℓ] Xi ×)

⊔F = (

i∈[1,ℓ] Xi

  • ,

i∈[1,ℓ] Xi ×)

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Lattice of graphs

Lattice of graphs

Property The set G of the subgraphs of G form a complete lattice The infimum and the supremum of any family F = {X1, . . . Xℓ}

  • f elements in G are given by:

⊓F = (

i∈[1,ℓ] Xi

  • ,

i∈[1,ℓ] Xi ×)

⊔F = (

i∈[1,ℓ] Xi

  • ,

i∈[1,ℓ] Xi ×)

G is sup-generated

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Lattice of graphs

Lattice of graphs

Property The set G of the subgraphs of G form a complete lattice The infimum and the supremum of any family F = {X1, . . . Xℓ}

  • f elements in G are given by:

⊓F = (

i∈[1,ℓ] Xi

  • ,

i∈[1,ℓ] Xi ×)

⊔F = (

i∈[1,ℓ] Xi

  • ,

i∈[1,ℓ] Xi ×)

G is sup-generated But G is not complemented

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Dilations and erosions

Edge-vertex correspondences: the building blocks

Definition We define the operators δ•, ǫ•, ǫ×, and δ× as follows:

G× → G• G• → G×

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Dilations and erosions

Edge-vertex correspondences: the building blocks

Definition We define the operators δ•, ǫ•, ǫ×, and δ× as follows:

G× → G• G• → G× Provide a graph X × → δ•(X ×) such that (δ•(X ×), X ×) = ⊓GX ×

where GX × (resp. GX •) is the set of graphs with edge-set X × (resp. vertex-set X •)

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Dilations and erosions

Edge-vertex correspondences: the building blocks

Definition We define the operators δ•, ǫ•, ǫ×, and δ× as follows:

G× → G• G• → G× Provide a graph X × → δ•(X ×) such that (δ•(X ×), X ×) = ⊓GX ×

where GX × (resp. GX •) is the set of graphs with edge-set X × (resp. vertex-set X •)

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Dilations and erosions

Edge-vertex correspondences: the building blocks

Definition We define the operators δ•, ǫ•, ǫ×, and δ× as follows:

G× → G• G• → G× Provide a graph X × → δ•(X ×) such that (δ•(X ×), X ×) = ⊓GX ×

where GX × (resp. GX •) is the set of graphs with edge-set X × (resp. vertex-set X •)

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Dilations and erosions

Edge-vertex correspondences: the building blocks

Definition We define the operators δ•, ǫ•, ǫ×, and δ× as follows:

G× → G• G• → G× Provide a graph X × → δ•(X ×) such that (δ•(X ×), X ×) = ⊓GX × X • → ǫ×(X •) such that (X •, ǫ×(X •)) = ⊔GX •

where GX × (resp. GX •) is the set of graphs with edge-set X × (resp. vertex-set X •)

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Dilations and erosions

Edge-vertex correspondences: the building blocks

Definition We define the operators δ•, ǫ•, ǫ×, and δ× as follows:

G× → G• G• → G× Provide a graph X × → δ•(X ×) such that (δ•(X ×), X ×) = ⊓GX × X • → ǫ×(X •) such that (X •, ǫ×(X •)) = ⊔GX •

where GX × (resp. GX •) is the set of graphs with edge-set X × (resp. vertex-set X •)

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Dilations and erosions

Edge-vertex correspondences: the building blocks

Definition We define the operators δ•, ǫ•, ǫ×, and δ× as follows:

G× → G• G• → G× Provide a graph X × → δ•(X ×) such that (δ•(X ×), X ×) = ⊓GX × X • → ǫ×(X •) such that (X •, ǫ×(X •)) = ⊔GX •

where GX × (resp. GX •) is the set of graphs with edge-set X × (resp. vertex-set X •)

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Dilations and erosions

Edge-vertex correspondences: the building blocks

Definition We define the operators δ•, ǫ•, ǫ×, and δ× as follows:

G× → G• G• → G× Provide a graph X × → δ•(X ×) such that (δ•(X ×), X ×) = ⊓GX × X • → ǫ×(X •) such that (X •, ǫ×(X •)) = ⊔GX • Provide the comple- ment with a graph X × → ǫ•(X ×) such that (ǫ•(X ×), X ×) = ⊓GX ×

where GX × (resp. GX •) is the set of graphs with edge-set X × (resp. vertex-set X •)

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Dilations and erosions

Edge-vertex correspondences: the building blocks

Definition We define the operators δ•, ǫ•, ǫ×, and δ× as follows:

G× → G• G• → G× Provide a graph X × → δ•(X ×) such that (δ•(X ×), X ×) = ⊓GX × X • → ǫ×(X •) such that (X •, ǫ×(X •)) = ⊔GX • Provide the comple- ment with a graph X × → ǫ•(X ×) such that (ǫ•(X ×), X ×) = ⊓GX ×

where GX × (resp. GX •) is the set of graphs with edge-set X × (resp. vertex-set X •)

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Dilations and erosions

Edge-vertex correspondences: the building blocks

Definition We define the operators δ•, ǫ•, ǫ×, and δ× as follows:

G× → G• G• → G× Provide a graph X × → δ•(X ×) such that (δ•(X ×), X ×) = ⊓GX × X • → ǫ×(X •) such that (X •, ǫ×(X •)) = ⊔GX • Provide the comple- ment with a graph X × → ǫ•(X ×) such that (ǫ•(X ×), X ×) = ⊓GX ×

where GX × (resp. GX •) is the set of graphs with edge-set X × (resp. vertex-set X •)

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Dilations and erosions

Edge-vertex correspondences: the building blocks

Definition We define the operators δ•, ǫ•, ǫ×, and δ× as follows:

G× → G• G• → G× Provide a graph X × → δ•(X ×) such that (δ•(X ×), X ×) = ⊓GX × X • → ǫ×(X •) such that (X •, ǫ×(X •)) = ⊔GX • Provide the comple- ment with a graph X × → ǫ•(X ×) such that (ǫ•(X ×), X ×) = ⊓GX × X • → δ×(X •) such that (X •, δ×(X •)) = ⊔GX •

where GX × (resp. GX •) is the set of graphs with edge-set X × (resp. vertex-set X •)

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Dilations and erosions

Edge-vertex correspondences: the building blocks

Definition We define the operators δ•, ǫ•, ǫ×, and δ× as follows:

G× → G• G• → G× Provide a graph X × → δ•(X ×) such that (δ•(X ×), X ×) = ⊓GX × X • → ǫ×(X •) such that (X •, ǫ×(X •)) = ⊔GX • Provide the comple- ment with a graph X × → ǫ•(X ×) such that (ǫ•(X ×), X ×) = ⊓GX × X • → δ×(X •) such that (X •, δ×(X •)) = ⊔GX •

where GX × (resp. GX •) is the set of graphs with edge-set X × (resp. vertex-set X •)

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Dilations and erosions

Edge-vertex correspondences: the building blocks

Definition We define the operators δ•, ǫ•, ǫ×, and δ× as follows:

G× → G• G• → G× Provide a graph X × → δ•(X ×) such that (δ•(X ×), X ×) = ⊓GX × X • → ǫ×(X •) such that (X •, ǫ×(X •)) = ⊔GX • Provide the comple- ment with a graph X × → ǫ•(X ×) such that (ǫ•(X ×), X ×) = ⊓GX × X • → δ×(X •) such that (X •, δ×(X •)) = ⊔GX •

where GX × (resp. GX •) is the set of graphs with edge-set X × (resp. vertex-set X •)

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Dilations and erosions

Adjunctions: reminder

Let (L1, ≤1) and (L2, ≤2) be two lattices

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Dilations and erosions

Adjunctions: reminder

Let (L1, ≤1) and (L2, ≤2) be two lattices Two operators ǫ : L1 → L2 and δ : L2 → L1 form an adjunction (ǫ, δ) if:

∀X ∈ L2, ∀Y ∈ L1, we have δ(X) ≤1 Y ⇔ X ≤2 ǫ(Y )

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Dilations and erosions

Adjunctions: reminder

Let (L1, ≤1) and (L2, ≤2) be two lattices Two operators ǫ : L1 → L2 and δ : L2 → L1 form an adjunction (ǫ, δ) if:

∀X ∈ L2, ∀Y ∈ L1, we have δ(X) ≤1 Y ⇔ X ≤2 ǫ(Y )

If (ǫ, δ) is an adjunction, then ǫ is an erosion and δ is a dilation:

ǫ preserves the infimum δ preserves the supremum

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Dilations and erosions

Edge-vertex adjunctions

Property

1 Both (ǫ×, δ•) and (ǫ•, δ×) are adjunctions

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Dilations and erosions

Edge-vertex adjunctions

Property

1 Both (ǫ×, δ•) and (ǫ•, δ×) are adjunctions 2 Operators δ• and δ× are dilations 3 Operators ǫ• and ǫ× are erosions

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Dilations and erosions

Edge-vertex adjunctions

Property

1 Both (ǫ×, δ•) and (ǫ•, δ×) are adjunctions 2 Operators δ• and δ× are dilations 3 Operators ǫ• and ǫ× are erosions

Important idea To obtain operators acting on the lattices G•, G× and G, we will compose the operators of these basic adjunctions

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Dilations and erosions

Vertex-dilation, vertex-erosion

Definition We define δ and ǫ that act on G• (i.e., G• → G•) by:

δ = δ• ◦ δ× and ǫ = ǫ• ◦ ǫ×

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Dilations and erosions

Vertex-dilation, vertex-erosion

Definition We define δ and ǫ that act on G• (i.e., G• → G•) by:

δ = δ• ◦ δ× and ǫ = ǫ• ◦ ǫ×

Property The pair (ǫ, δ) is an adjunction

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Dilations and erosions

Vertex-dilation, vertex-erosion

Definition We define δ and ǫ that act on G• (i.e., G• → G•) by:

δ = δ• ◦ δ× and ǫ = ǫ• ◦ ǫ×

Property The pair (ǫ, δ) is an adjunction They correspond exactly to the operators defined by Vincent

X• δ(X•)

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Dilations and erosions

Edge-dilation, edge-erosion

Definition (edge-dilation, edge-erosion) We define ∆ and E that act on G× by:

∆ = δ× ◦ δ• and E = ǫ× ◦ ǫ•

Property The pair (E, ∆) is an adjunction

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Dilations and erosions

Graph-dilation, graph-erosion

Definition We define, for any X ∈ G, the operators δ ∆ and ǫ E by:

δ ∆(X) = (δ(X •), ∆(X ×)) and ǫ E(X) = (ǫ(X •), E(X ×))

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Dilations and erosions

Graph-dilation, graph-erosion

Definition We define, for any X ∈ G, the operators δ ∆ and ǫ E by:

δ ∆(X) = (δ(X •), ∆(X ×)) and ǫ E(X) = (ǫ(X •), E(X ×))

Theorem The lattice G is closed under the operators δ ∆ and ǫ E

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Dilations and erosions

Graph-dilation, graph-erosion

Definition We define, for any X ∈ G, the operators δ ∆ and ǫ E by:

δ ∆(X) = (δ(X •), ∆(X ×)) and ǫ E(X) = (ǫ(X •), E(X ×))

Theorem The lattice G is closed under the operators δ ∆ and ǫ E The pair (ǫ E, δ ∆) is an adjunction

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Dilations and erosions

Graph-dilation, graph-erosion

Definition We define, for any X ∈ G, the operators δ ∆ and ǫ E by:

δ ∆(X) = (δ(X •), ∆(X ×)) and ǫ E(X) = (ǫ(X •), E(X ×))

Theorem The lattice G is closed under the operators δ ∆ and ǫ E The pair (ǫ E, δ ∆) is an adjunction The operators δ ∆ and ǫ E are respectively a dilation and an erosion acting on the lattice (G, ⊑)

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Dilations and erosions

Graph-dilation: example

X (red & blue)

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Dilations and erosions

Graph-dilation: example

X (red & blue) δ ∆(X) (red & blue)

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Filters

Filters: reminder

A filter is an operator α acting on a lattice L, which is

1 increasing: ∀X, Y ∈ L, α(X) ≤ α(Y ) whenever X ≤ Y ; and 2 idempotent: ∀X ∈ L, α(α(X)) = α(X)

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Filters

Filters: reminder

A filter is an operator α acting on a lattice L, which is

1 increasing: ∀X, Y ∈ L, α(X) ≤ α(Y ) whenever X ≤ Y ; and 2 idempotent: ∀X ∈ L, α(α(X)) = α(X)

A closing on L is a filter α on L which is:

extensive: ∀X ∈ L, X ≤ α(X)

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SLIDE 47

Filters

Filters: reminder

A filter is an operator α acting on a lattice L, which is

1 increasing: ∀X, Y ∈ L, α(X) ≤ α(Y ) whenever X ≤ Y ; and 2 idempotent: ∀X ∈ L, α(α(X)) = α(X)

A closing on L is a filter α on L which is:

extensive: ∀X ∈ L, X ≤ α(X)

An opening on L is a filter α on L which is anti-extensive

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Filters

Filters: reminder

A filter is an operator α acting on a lattice L, which is

1 increasing: ∀X, Y ∈ L, α(X) ≤ α(Y ) whenever X ≤ Y ; and 2 idempotent: ∀X ∈ L, α(α(X)) = α(X)

A closing on L is a filter α on L which is:

extensive: ∀X ∈ L, X ≤ α(X)

An opening on L is a filter α on L which is anti-extensive Composing the two operators of an adjunction yields an

  • pening or a closing depending on the composition order
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Filters

Openings, closings: the classical ones

Definition We define

1 γ1 and φ1, G• → G•, by γ1 = δ ◦ ǫ and φ1 = ǫ ◦ δ

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Filters

Openings, closings: the classical ones

Definition We define

1 γ1 and φ1, G• → G•, by γ1 = δ ◦ ǫ and φ1 = ǫ ◦ δ 2 Γ1 and Φ1, G× → G×, by Γ1 = ∆ ◦ E and Φ1 = E ◦ ∆

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Filters

Openings, closings: the classical ones

Definition We define

1 γ1 and φ1, G• → G•, by γ1 = δ ◦ ǫ and φ1 = ǫ ◦ δ 2 Γ1 and Φ1, G× → G×, by Γ1 = ∆ ◦ E and Φ1 = E ◦ ∆ 3 γ Γ1 and φ Φ1 by respectively γ Γ1(X) = (γ1(X •), Γ1(X ×))

and φ Φ1(X) = (φ1(X •), Φ1(X ×)), for any graph X in G

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Filters

Openings, closings: the classical ones

Definition We define

1 γ1 and φ1, G• → G•, by γ1 = δ ◦ ǫ and φ1 = ǫ ◦ δ 2 Γ1 and Φ1, G× → G×, by Γ1 = ∆ ◦ E and Φ1 = E ◦ ∆ 3 γ Γ1 and φ Φ1 by respectively γ Γ1(X) = (γ1(X •), Γ1(X ×))

and φ Φ1(X) = (φ1(X •), Φ1(X ×)), for any graph X in G Theorem (graph-openings, graph-closings) The operators γ1 and Γ1 are openings. The operators Φ1 and φ1 are closings The operator γ Γ1 is an opening. The operator φ Φ1 is a closing

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Filters

Openings, closings: the half ones

Definition We define

1 γ1/2 and φ1/2, G• → G•, by γ1/2 = δ• ◦ ǫ× and φ1/2 = ǫ• ◦ δ×

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Filters

Openings, closings: the half ones

Definition We define

1 γ1/2 and φ1/2, G• → G•, by γ1/2 = δ• ◦ ǫ× and φ1/2 = ǫ• ◦ δ× 2 Γ1/2 and Φ1/2, G× → G×, by Γ1/2 = δ× ◦ ǫ• and Φ1/2 = ǫ× ◦ δ•

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Openings, closings: the half ones

Definition We define

1 γ1/2 and φ1/2, G• → G•, by γ1/2 = δ• ◦ ǫ× and φ1/2 = ǫ• ◦ δ× 2 Γ1/2 and Φ1/2, G× → G×, by Γ1/2 = δ× ◦ ǫ• and Φ1/2 = ǫ× ◦ δ• 3 γ Γ1/2 and φ Φ1/2 by γ Γ1/2(X) = (γ1/2(X •), Γ1/2(X ×))

and φ Φ1/2(X) = (φ1/2(X •), Φ1/2(X ×)), for any graph X in G

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Openings, closings: the half ones

Definition We define

1 γ1/2 and φ1/2, G• → G•, by γ1/2 = δ• ◦ ǫ× and φ1/2 = ǫ• ◦ δ× 2 Γ1/2 and Φ1/2, G× → G×, by Γ1/2 = δ× ◦ ǫ• and Φ1/2 = ǫ× ◦ δ• 3 γ Γ1/2 and φ Φ1/2 by γ Γ1/2(X) = (γ1/2(X •), Γ1/2(X ×))

and φ Φ1/2(X) = (φ1/2(X •), Φ1/2(X ×)), for any graph X in G Theorem (half-openings, half-closings) The operators γ1/2 and Γ1/2 are openings. The operators φ1/2 and Φ1/2 are closings The operator γ Γ1/2 is an opening. The operator φ Φ1/2 is a closing.

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Illustration: openings

A graph X (red)

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Illustration: openings

A graph X (red, blue) γ Γ1/2(X) (red)

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Illustration: openings

A graph X (red, blue, green) γ Γ1/2(X) (red, green) γ Γ1(X) (red)

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Building hierarchies

Definition Let λ ∈ N. Let i and j be the quotient and the remainder in the integer division of λ by 2. We set:

γ Γλ/2 = (δ ∆)i ◦ (γ Γ1/2)j ◦ (ǫ E)i φ Φλ/2 = (ǫ E)i ◦ (φ Φ1/2)j ◦ (δ ∆)i

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Building hierarchies

Definition Let λ ∈ N. Let i and j be the quotient and the remainder in the integer division of λ by 2. We set:

γ Γλ/2 = (δ ∆)i ◦ (γ Γ1/2)j ◦ (ǫ E)i φ Φλ/2 = (ǫ E)i ◦ (φ Φ1/2)j ◦ (δ ∆)i

Property The families {γ Γλ/2 | λ ∈ N} and {φ Φλ/2 | λ ∈ N} are granulometries:

∀λ ∈ N, γ Γλ/2 is an opening on G and φ Φλ/2 is a closing on G ∀µ, ν ∈ N and ∀X ∈ G, µ ≤ ν implies γ Γν/2(X) ⊑ γ Γµ/2(X) and φ Φµ/2(X) ⊑ φ Φν/2(X)

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Iterated filters

Definition We define ASFλ/2

by the identity on graphs when λ = 0 by ASFλ/2 = γ Γλ/2 ◦ φ Φλ/2 ◦ ASF(λ−1)/2 otherwise

Property The family {ASFλ/2 | λ ∈ N} is a family of alternate sequential filters:

∀µ, ν ∈ N, µ ≥ ν implies ASFµ/2 ◦ ASFν/2 = ASFµ/2

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ASF: illustration for binary image filtering

Original Noisy

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ASF: illustration for binary image filtering

graph ASF Classical ASF

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ASF: illustration for binary image filtering

graph ASF Classical ASF of double size

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ASF: illustration for binary image filtering

graph ASF Classical ASF (double resolution)

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ASF: illustration for 3D binary image filtering

Original Noisy

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ASF: illustration for 3D binary image filtering

graph ASF Classical ASF

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ASF: illustration for 3D binary image filtering

graph ASF Classical ASF of double size

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ASF: illustration for 3D binary image filtering

graph ASF Classical ASF (double resolution)

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Other adjunctions on graphs

1 (α1, β1) such that ∀X ∈ G, α1(X) = (G•, X ×) and

β1(X) = (δ•(X ×), X ×)

2 (α2, β2) such that ∀X ∈ G, α2(X) = (X •, ǫ×(X •)) and

β2(X) = (X •, ∅)

α1 and α2 are both a closing and an erosion; β1 and β2 are both an opening and dilation

3 (α3, β3) such that ∀X ∈ G, α3(X) = (ǫ•(X ×), ǫ× ◦ ǫ•(X ×)) and

β3(X) = (δ• ◦ δ×(X •), δ×(X •))

α3 depends only on the edge-set; β3 only on the vertex-set

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Perspectives

Extension to node and edge-weighted graphs

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Perspectives

Extension to node and edge-weighted graphs Study of levellings in this framework

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Perspectives

Extension to node and edge-weighted graphs Study of levellings in this framework

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Perspectives

Extension to node and edge-weighted graphs Study of levellings in this framework Relation with connexion and hyper-connexion

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Perspectives

Extension to node and edge-weighted graphs Study of levellings in this framework Relation with connexion and hyper-connexion Embedding of the vertices in a metric space

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Perspectives: simplicial/cubical complexes

How to filter according to the dimension of objects?

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Perspectives: simplicial/cubical complexes

How to filter according to the dimension of objects? Graphs?

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Perspectives: simplicial/cubical complexes

  • How to filter according to the dimension of objects?

Graphs? NO Cubical complexes!

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Paper of the talk

  • J. Cousty, L. Najman and J. Serra Some morphological operators in

graph spaces, Mathematical Morphology and its Applications to Signal and Image Processing - ISMM 2009, LNCS 5720, pp. 149-160 Download at www.esiee.fr/˜ coustyj/CV.htm#publis

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