Poisson Image Editing & Terrain Synthesis Howard Zhou Jie Sun

Table of Contents 1. Introduction / motivation 2. Poisson Image Editing 3. Terrain Synthesis (Texture based methods) 4. Future work 5. Conclusion

Table of Contents 1. Introduction / motivation 2. Poisson Image Editing 3. Terrain Synthesis (Texture based methods) 4. Future work 5. 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

Contrast can be globally fixed But how?

Seamless tiling Seams not good Cannot be fixed

Table of Contents 1. Introduction / motivation 2. Poisson Image Editing 3. Terrain Synthesis (Texture based methods) 4. Future work 5. 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 + piecewise seamless tiling 3. Graph cut / seamless tiling 4. Separating the details

Data: height map

Display height map

Image analogy : :: : AA'BB' A. Hertzmann, C. Jacobs, N. Oliver, B. Curless, D. Salesin. SIGGRAPH 2001

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

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. Introduction (motivation) 2. Re-illumination 3. Changing viewpoint 4. Future work 5. 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 ?