image inpainting

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Image Inpainting M. Bertalmio, A.L. Sapiro, V. Caselles, C. Ballester M. Bertalmio, A.L. Bertozzi & G. Sapiro presented by Roman Stanchak Navier Stokes, Fluid Dynamics and Image and Video Inpainting Navier Stokes, Fluid Dynamics and Image and Video Inpainting

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M. Bertalmio, A.L. Sapiro, V. Caselles, C. Ballester M. Bertalmio, A.L. Bertozzi & G. Sapiro presented by Roman Stanchak. Image Inpainting. Navier Stokes, Fluid Dynamics and Image and Video Inpainting. Navier Stokes, Fluid Dynamics and Image and Video Inpainting. Goal. - PowerPoint PPT Presentation

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Page 1: Image Inpainting

Image InpaintingM. Bertalmio, A.L. Sapiro, V. Caselles,

C. Ballester

M. Bertalmio, A.L. Bertozzi & G. Sapiro

presented byRoman Stanchak

Navier Stokes, Fluid Dynamics and Image and

Video Inpainting

Navier Stokes, Fluid Dynamics and Image and

Video Inpainting

Page 2: Image Inpainting

Goal

● Given image with significant portions missing or damaged

● Reconstitute missing regions with data consistent with the rest of the image

Page 3: Image Inpainting
Page 4: Image Inpainting
Page 5: Image Inpainting

Cracks in Photos

Page 6: Image Inpainting

Scratches in Film

Page 7: Image Inpainting

Add or remove elements

Page 8: Image Inpainting

Professional Inpainters Approach

● Goal: – Subjectively restore unity to artwork

● General Approach:– Structure of surrounding area continued

into gap– Color of surrounding area is continued

into gap– Texture is added

Page 9: Image Inpainting

Gestalt Law of Continuation

● Principle holding that there is an innate tendence to perceive a line as continuing its established direction

Page 10: Image Inpainting

General Algorithm

● Iteratively– Continue structure of surrounding area

into gap– Continue color of surrounding area into

gap

Page 11: Image Inpainting

Algorithm

● Define image update as follows:● It(i,j) = dL(i,j) . N(i,j)

– It(i,j) is change in intensity to used to update the image

– L(i,j) is the information to propagate – N(i,j) is the propagation direction– dL(i,j) . N(i,j) is the change in information

along the propagation direction

Page 12: Image Inpainting

Propagation Direction

● Want to preserve angle of 'arrival'● Propagate along isophotes

– lines of equivalent intensity levels

Isophotes

Page 13: Image Inpainting

Propagation Direction

● More formally:– Image gradient

● largest change– Perpindicular

● smallest change● this is the isophote

Isophote is this boundary

= N(i,j)

Page 14: Image Inpainting

Algorithm

● What information to propagate?– 'smoothness'

● Laplacian == Ixx(i,j) +Iyy(i,j) = L(i,j)

Page 15: Image Inpainting

Algorithm

● Repeat this image update step to restore image

● When to stop?– Stop when update value is negligible

● i.e. It(i,j) < epsilon for all i,j– Stop after n iterations

Page 16: Image Inpainting

Some results

Page 17: Image Inpainting

Some results

Page 18: Image Inpainting

Some results

Page 19: Image Inpainting

More results

Page 20: Image Inpainting

More results

Page 21: Image Inpainting

More results

Page 22: Image Inpainting

Navier-Stokes equations

● Nonlinear partial differential equations● Describe the flow of fluids such as

liquids and gases– Air currents– Ocean currents– Water flow in a pipe

Page 23: Image Inpainting

Navier-Stokes equations

Page 24: Image Inpainting

Relation to Inpainting

● Inpainting– Propagation of intensity along isophote

according to smoothness● Fluid mechanics

– Convection of fluid along velocity field according to vorticity

Page 25: Image Inpainting

Relation to Inpainting

● Mapping– Image intensity == Stream function– Isophote direction == fluid velocity– Smoothness == vorticity

● Propels inpainting into an established field with a wealth of theoretical and numerical literature!

Page 26: Image Inpainting

Super Resolution Result

Up scaled image Bicubic sampled Navier-Stokes inpainting