Poisson Image Editing& Terrain Synthesis

Howard Zhou Jie Sunhowardz@cc.gatech.edu sun@cc.gatech.edu

2003 . 4.29

Table of Contents

1. Introduction / motivation2. Poisson Image Editing3. Terrain Synthesis (Texture based methods)

4. Future work5. Conclusion

Table of Contents

1. Introduction / motivation2. Poisson Image Editing3. Terrain Synthesis (Texture based methods)

4. Future work5. 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 = 0.05beta = 0.2

alpha = 0.05beta = 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. Introduction / motivation2. Poisson Image Editing3. Terrain Synthesis (Texture based methods)

4. Future work5. Conclusion

Previous approachTexture 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 analogy2. Texture synthesis on laplacian +

piecewise seamless tiling3. Graph cut / seamless tiling4. 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 synthesisIntegrate

Results

Terrain

Terrain

Problems & possible solutions

Depend on the boundary conditionsUse the boundary attached to the

Laplacian

There is only one unique solution of this linear system

Lost the power of Poisson editingShould 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. Introduction (motivation)2. Re-illumination3. Changing viewpoint4. Future work5. 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 editingTried several texture based terrain

synthesis methodsLots to be done!

Questions ?