Download - Parallel Controllable Texture Synthesis Sylvain Lefebvre, Hugues Hoppe SIGGRAPH 2005 24(3), 777-786
Parallel Controllable Texture Synthesis
Sylvain Lefebvre, Hugues Hoppe
SIGGRAPH 2005
24(3), 777-786
Parallel Controllable Texture Synthesis
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Outline
• Introduction• Parallel synthesis method• Synthesis control• Result
Parallel Controllable Texture Synthesis
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Introduction
• Sample-based texture synthesis analyzes a given exemplar to create visually similar images.– tiling methods are the fastest – patch optimization methods produce some of the best results– neighborhood-matching algorithms allow greater fine-scale ada
ptability
• Our interest is in applying synthesis to define infinite, aperiodic, deterministic content from a compact representation. we present a new neighborhood-matching method.
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Parallel synthesis method –Basic scheme
• E[u]=E[S[p]]– E: m×m exemplar image– S: synthesized image– p Z∈ 2
– u Z∈ 2
• image pyramid
S0, S1, …, (SL=S) in coarse-to-fine order, where L=log2m.
(Figure 2)
Parallel Controllable Texture Synthesis
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Parallel synthesis method –steps
Parallel Controllable Texture Synthesis
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Parallel synthesis method – Upsampling & Jitter
– hl regular output spacing : 1 for pyramid, 2L-1 for a stack
– Hash Function H: Z2 -> [-1,+1]2
– per-level randomness parameter rl : [0,1]
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Parallel synthesis method –Correction
• For each pixel p, we gather the pixel colors of its 5×5 neighbor-hood at the current level, represented as a vector NSl(p) . This neighborhood is compared with exemplar neighborhoods NEl(u) to find the L2 best matching one.
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Parallel synthesis method – Gaussian image stack
• traditional Gaussian image pyramid often results in synt
hesized features that align with a coarser “grid”.
• because ancestor coordinates in the synthesis pyramid are snapped to the quantized positions of the exemplar pyramid.
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Parallel synthesis method – Gaussian image stack
• augment the exemplar image on all sides to have size 2m×2m:– an actual larger texture– a tiling if the exemplar is toro
idal– reflected copies of the exem
plar
• Gaussian filtering each level, without subsampling.
• Reassign hl = 2L-l.
Synthesis control –Multiscale randomness control
• The randomness parameters r
l set the jitter amplitude at each level, and thus provide a form of “spectral variation control” .
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Synthesis control –Spatial modulation over source
• preserving the integrity of selected texture elements in nonstationary textures.
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Synthesis control –Spatial modulation over output
• to roughen a surface pattern in areas of wear or damage.
Synthesis control –Feature drag-and-drop
• Sl[p]:=((uF)+(p-pF)) mod m
if ||p-pF|| < rF
– pF : the desired exemplar coordinate
– rF : exemplar radius
– uF : circle center
• rF = ril/L + ro(L-l)/L
– ri : inner radius
– ro : outer radius
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Result
• additional results