To get rid of (an) object(s) at a picture or to restore a picture from scratches or holes, Criminisi at el. suggested an algorithm which is combied "texture synthesis" and "inpainting". I made the slide to present at a class to introduce this algorithm. I refered a slide http://bit.ly/1Ng7DNt. I wish this slide may help you to understand the algorithm. Thank you.
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Region filling and object removal by exemplar based image inpainting
1. Region Filling and Object Removal by
Exemplar-Based Image Inpainting
Criminisi, A., Perez, P., and Toyama, K. (2004)
Lee, Woonghee
M.S. student at the Big Data Mining Lab.
Department of computer science and engineering at the Hanyang University
October 4th, 2015
4. Prerequisite
To fill large image repetitively 2-D texture synthesis
inpainting
Exmaples from Ashikimin [1]
5. Prerequisite
Properties
• Cheap cost to generate image
• Effectively generating image
• Difficult to fill holes in photos
• A complex product of mutual
influences between different
boundaries
texture synthesis
inpainting
6. Prerequisite
To fill holes in images by
propagating linear structures
(called isophote)
texture synthesis
inpainting
7. Prerequisite
To fill holes in images by
propagating linear structures
(called isophote)
Depends on Gestalt Law of
Continuation
texture synthesis
inpainting
12. Prerequisite
Properties
• Effective to fill speckles,
scratches, and overlaid text
• Causes noticeable blur to fill
large regions
• Extremely slow (83’-158’ on a
384 X 256 image)
texture synthesis
inpainting
17. Key Observations
B. Filling Order is Critical
Onion peel(concentric-layer odering) causes
“over shooting” → To achieve balancing
between the structured regions and texture
regions.
21. Region Filling Algorithm
2) Propagating Texture and Structure Information
After computing priorities, setting the highest
priority Ψ 𝑝
To avoid diffusion, propagating image texture
from the source region
Ψ 𝑞 = arg 𝑚𝑖𝑛Ψ 𝑞∈Φ 𝑑(Ψ 𝑝, Ψ𝑞)
22. Region Filling Algorithm
3) Updating Confidence Values
After filling the patch Ψ 𝑝, the confidence term
is updated
𝐶 𝑝 = 𝐶 𝑝 , ∀ 𝑝∈ Ψ 𝑝 ∩ Ω
It does not require additional parameter to
specify image.
24. Region Filling Algorithm
Properties of the region filling algorithm
Recall 𝑃 𝑝 = 𝐶 𝑝 𝐷 𝑝
The priority equation achieves balance of
effects and an organic synthesis
25. Region Filling Algorithm
Properties of the region filling algorithm
𝑃 𝑝 = 𝐶 𝑝 𝐷 𝑝
• avoids an arbitrary fill order.
• eliminates the risk of “broken-structure”
artefacts.
• propagates strong edges.
• reduces blocky and misalignment artefacts
without additional step.
26. Region Filling Algorithm
Implementation Details
The target 𝛿Ω is manually selected.
The normal direction 𝑛 𝑝 is computed as
1) Contour’s “control” points are filtered via
2D Gaussian kernel
2) estimated as the orthogonal unit vector of
𝛿Ω
27. Region Filling Algorithm
Implementation Details
The gradient ∇𝐼 𝑝is computed as the MAX value
in Ψ𝑝 ∩ 𝐼
Pixels are classified as belonging to
• The target region Ω
• The source region
• The remainder
40. Results and Comparisons
Comparisons With Diffusion-Based Inpainting
priority function for before image
Priority function is 0 for inside and 1 for outside Final priorities made the continuation of the pole