Poisson Image Editing
& Terrain Synthesis
Howard Zhou
howardz@cc.gatech.edu
Jie Sun
sun@cc.gatech.edu
2003 . 4.29
Table of Contents
1.
2.
3.
4.
5.
Introduction / motivation
Poisson Image Editing
Terrain Synthesis (Texture based methods)
Future work
Conclusion
Table of Contents
1.
2.
3.
4.
5.
Introduction / motivation
Poisson Image Editing
Terrain Synthesis (Texture based methods)
Future work
Conclusion
Introduction / motivation
 Poisson Image Editing
 Seamless
 Texture based terrain synthesis




Current method based on fractals
Very limited control
Terrain style adjusted by parameter tuning
What if the user draws a rough sketch and supply a
height map and says: “I want this to be like this”
Poisson Image Editing
 Review
Our implmentation
 Matlab
 Sparse matrix PDF solver
 Use conjugate gradient solver supplied

by Matlab
Can be faster if …
Seamless insertion
Inserting objects with holes
Inserting transparent objects
Texture flattening
Result directly related to Edge detection result
Local illumination changes
alpha = 0.05
beta = 0.2
alpha = 0.05
beta = 0.4
Seamless
tiling
 Good when seam is not significant
 Often needs to increase the contrast of the
result
 but don’t an automatic way, maybe use
histogram of the original image
Seamless
tiling
Good when
the seam is
not significant
Seamless
tiling
Show some
more
Seamless
tiling
Seamless
tiling
Seamless
tiling
Contrast can be
globally fixed
But how?
Seamless
tiling
Seams not good
Cannot be fixed
Table of Contents
1.
2.
3.
4.
5.
Introduction / motivation
Poisson Image Editing
Terrain Synthesis (Texture based methods)
Future work
Conclusion
Previous approach
Texture based terrain synthesis
 Current method based on fractals
 Very limited control
 Terrain style adjusted by parameter

tuning
What if the user draws a rough sketch
and supply a height map and says: “I
want this to be like this”
Texture based terrain synthesis
1. Image analogy
2. Texture synthesis on laplacian +
3.
4.
piecewise seamless tiling
Graph cut / seamless tiling
Separating the details
Data: height map
Display height map
Image analogy
:
A
::
A'
:
B
B'
A. Hertzmann, C. Jacobs, N. Oliver, B. Curless, D. Salesin.
SIGGRAPH 2001
Texture by number
Texture
by number
How do we get (A) automatically
 Blurring (filtering)
 Texture flattening using edge detection
result or contour
Image analogy +
(texture flattening + blurring)
Laplacian Synthesis
 Regard laplacian as a particular
texture
 Texture synthesis
 Integrate
Results
Terrain
Terrain
Problems & possible solutions
 Depend on the boundary conditions
 Use the boundary attached to the
Laplacian
 There is only one unique solution of
this linear system
 Lost the power of Poisson editing
 Should use a non-conservative gradient
field
Graph cut +
seamless tiling
Laplacian removing boundary
(since the boundary is known)
Image smoothing edge (1 D)
Using Poisson Solver
Terrain Analysis
 The detail of the terrain differs at
different altitude
 Terrain = f ( altitude )
 Altitude = g ( style )
Example: Terrain map
Low Frequency - Altitude
High Frequency – as a function of Altitude
Proposed Algorithm
 Use “Copy & Paste” methods to
generate an altitude map
 Add high frequency probabilistically
as indexed by the altitude map
 Graph cuts/Image Quilting to make it
seamless
Table of Contents
1.
2.
3.
4.
5.
Introduction (motivation)
Re-illumination
Changing viewpoint
Future work
Conclusion
Future Work
 Other texture methods (Graph cut, stocastic?)
 Stylized map generation from real map
 Real map from stylized map
Map vs. terrain
Conclusion
 Implemented poisson image editing
 Tried several texture based terrain
synthesis methods
 Lots to be done!
Questions ?