1. Maryia Kazakevich “Texture Synthesis by Patch-Based Sampling” Texture Synthesis by Patch-Based Sampling Real-Time Texture Synthesis By Patch-Based Sampling, LinLiang, Ce-Liu, Yingqing Xu, Baining Guo, Heung-Yeng Shum, 2001. Presented by: Maryia Kazakevich Dec.3, 2004

2. Maryia Kazakevich “Texture Synthesis by Patch-Based Sampling” Outline Background to Texture Synthesis Patch-based sampling Algorithm outline Some details Summary of the method Results Maryia Kazakevich

3. “Texture Synthesis by Patch-Based Sampling” Background Want output texture to appear perceptually similar to input Several techniques possible: –Similar: pixel-based sampling Neighbourhood match Texture mapping: simple tiling might be unacceptable

4. Maryia Kazakevich “Texture Synthesis by Patch-Based Sampling” Patch-Based Sampling Select next patch from the input image based on the boundary zone match

5. Maryia Kazakevich “Texture Synthesis by Patch-Based Sampling” Outline of Algorithm 1.Randomly select first texture patch. 2.Choose the next patch from the input image to paste in the output. 3.Repeat previous step until output image is fully covered. 4.Blend pixels in the boundary zones.

6. Maryia Kazakevich “Texture Synthesis by Patch-Based Sampling” Algorithm in detail To select the next patch: 1.Construct a set of possible texture patches with boundary zone matching the output: 2.If the set is empty, chose the patch with minimum d(E Bk, E k out ) Otherwise randomly select a patch from  b as next texture patch to paste into the output image

7. Maryia Kazakevich “Texture Synthesis by Patch-Based Sampling” Algorithm in detail (constructing  b ) Boundary zone matching: A – number of pixels in the boundary zone Pi – i-th pixel of the boundary zone E Bk, E k out – boundary zone of the next patch and output image  – relative matching error between boundary zones

8. Maryia Kazakevich “Texture Synthesis by Patch-Based Sampling” Boundary zone blending To smooth the transition between adjacent patches, blend them using feathering: d(x) – distance to the border pixel w – monotonic function (used w (d(x)) = d(x)) I – original intensity C – output intensity

9. Maryia Kazakevich “Texture Synthesis by Patch-Based Sampling” Summary Paste random patch in one of the corners. Select next best suited patch and paste it in the next spot in the output image. Blend the overlap regions between patches.

10. Maryia Kazakevich “Texture Synthesis by Patch-Based Sampling” Input parameters Patch size – how well local characteristics of input texture are captured Larger boundary zone width – stronger statistical constraint, more natural transition between boundaries Relative matching error – controls similarity of overlapping boundary zones

11. Maryia Kazakevich “Texture Synthesis by Patch-Based Sampling” Influence of the parameters Input: 32x32, Output: 64x64 Checkers: Patch size:16x16; 8x8 boundary: 2; 8 Relative matching error: 0.6; 0.2 Dots: Patch size:16x16; 6x6 boundary: 2; 10 Relative matching error: 0.2; 0.2

12. Maryia Kazakevich “Texture Synthesis by Patch-Based Sampling” My interface Not shown: –Input fields for the output texture size –Buttons for selecting a different input picture and for synthesizing

13. Maryia Kazakevich “Texture Synthesis by Patch-Based Sampling” Results Patch size:16x16, boundary: 2 Relative matching error: 0.2 Input: 32x32, Output: 64x64 Input: 32x32, Output: 84x84