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Gradient-Based Image Editing

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Gradient-Based Image Editing Extensions to Poisson Editing 3D mesh editing Guided vector field Image matting Good boundary finding Poisson Image Editing Drag-and-Drop ... – PowerPoint PPT presentation

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Title: Gradient-Based Image Editing


1
Gradient-Based Image Editing
2
Poisson Image Editing
  • Patrick Perez, Michel Gangnet and Andrew Blake
  • Microsoft Research UK

3
Outline
  • Introduction
  • Poisson solution to guided interpolation
  • Guided Interpolation
  • Discrete Poisson solver
  • Seamless cloning
  • Importing gradients
  • Mixing gradients
  • Selection editing
  • Texture flattening
  • Local illumination change
  • Local color change
  • Seamless tiling
  • Conclusion

4
Introduction
  • A generic interpolation machinery based on
    solving Poisson equations
  • A variety of novel tools for seamless editing of
    image regions
  • Import the source image region to a target region
  • Modify appearance seamless in selected image
    region illumination, color, texture, etc.

5
Introduction
  • Image editing
  • Global changes (color/intensity corrections,
    Filters, deformations)
  • Local changes confined to a selection
  • Selected region
  • Seamless
  • Changes slight distortion -gt complete
    replacement

Seams partly hidden by feathering
6
Introduction
  • Seamless editing and cloning of a selection
    region
  • Mathematical tool
  • Poisson partial differential equation
  • Laplacian of unknown function over the domain of
    interest
  • Dirichlet boundary conditions
  • Known function value along the boundary

7
Boundary Conditions
  • Dirichlet boundary condition
  • It specifies the values of a solution needs to
    take on the boundary of the domain
  • Neumann boundary condition
  • It specifies the values of the derivative of a
    solution is to take on the boundary of the domain

8
Poisson Equation
  • Second-order variations extracted by Laplacian
    operator are the most significant perceptually
  • Scalar function on a bounded domain is uniquely
    defined by its values on the boundary and its
    Laplacian in the interior
  • Poisson equation therefore has a unique solution

9
Poisson Equation
  • Solving Poisson equation interpretation as
    minimization problem
  • Gradient of the function is the closest (in
    L2-norm) to some prescribed vector field
    (Guidance vector field) under given boundary
    conditions
  • Possible choice of guidance vector filed
  • Source image
  • Mixing suitably gradient of source and target
    image
  • Modify a region of the image

10
Related Work
  • Poisson equation has been used extensively in
    computer vision
  • Rescale gradient field of High Dynamic Range
    (HDR) image
  • Solving Poisson equation with Neumann boundary
  • Edit image via a sparse set of edge elements
  • Solving a Laplace equation with Dirichlet
    boundary
  • Spot removing
  • Replace the brightness by harmonic interpolation
    (solving a Laplace equation)

11
Poisson Solution to Guided Interpolation
  • Guided Interpolation

S Image domain
Closed subset of S
Guidance vector field
fDestination function f Unknown function
Gradient field of a source function
12
Guided Interpolation
  • Membrane interpolant

The minimizer must satisfy the associated
Euler-Lagrange equation
13
Guided Interpolation
  • Guidance filed a vector field v

The fundamental machinery of Poisson editing of
color images independently solve the three
color channels
14
Guided Interpolation
  • With a conservative vector field v (it is the
    gradient of some gradient function)
  • Correction function
  • Poisson equation -gt Laplace equation

Membrane interpolant
15
Discrete Poisson solver
  • Can be discretized and solved in a number of ways
  • S, become finite point sets defined on a
    discrete grid
  • For each pixel p in S, Np is its 4-connectd
    neighbors in S
  • The boundary
  • Pixel pair
  • The task is to compute the pixel values over
    the region

16
Discrete Poisson solver
  • Dirichlet boundary conditions defined on a
    boundary of arbitrary shape, so discrete the
    problem directly rather than the Poisson equation

17
Discrete Poisson solver
  • Solution linear equations
  • For all pixels p interior to , no boundary
    terms

A classical, sparse, symmetric, positive-definite
system
18
Discrete Poisson solver
  • Arbitrary shape of boundary , use
    iterative solvers
  • Gauss-Seidel iteration
  • V-cycle multigrid
  • Both are fast enough for interactive editing

19
Seamless Cloning
  • Importing gradients
  • Gradient field directly from source image g

20
Seamless Cloning
  • Very simple user interaction by drawing outlines

21
Feature Exchange
  • Draw precise boundary for specific object

22
Seamless Cloning
  • Transfer only part of the source content

23
Inserting object with holes
Seamless cloning
Color-based cut-and-paste
Seamless cloning and destination averaged
Mixed seamless cloning
24
Mixing gradients
  • Linear combination of source and destination
    gradient fields
  • Non-conservative guidance fields

25
Mixing gradients
  • Transparent object

26
Mixing Graidents
Source/destination Seamless cloning
mixed seamless cloning
27
Selection Editing
  • Modify one image in its gradient domain
  • Texture flattening
  • Spatially selective illumination changes
  • Background and foreground color modification
  • Seamless titling

Non-linear modification of the original gradient
field
Modify the original image, provide a new source
image or new boundary
28
Texture Flattening
  • M a binary mask tuned on at a few locations of
    interest
  • Preserve main structure

29
Local Illumination Changes
  • Modify the gradient of original image then use it
    as a new guided vector field
  • Modify locally the apparent illumination
  • Highlight under-exposed foreground object
  • Reduce specular reflections

30
Local Color Changes
  • Given a source color image g
  • The destination image f is set to be the
    luminance channel from g,
  • The user selects a region containing the
    object, and this may be some what bigger than the
    actual object
  • Modify the colors of background or in the
    selected region as new destination/source image
  • The Poisson equation is solved in each color
    channel.

31
Local Color Changes
new source image by multiplying the RGB channels
by 1.5, 0.5, 0.5
Original Image
Decolorization f is the luminance of g

32
Seamless tiling
  • Seamless tiling by enforcing periodic boundary
    conditions with Poisson solver
  • Use original image as source image, set identical
    boundary from opposite sides of the original
    boundary

33
Conclusion
  • A Generic framework of guided interpolation
  • A series of tools to edit in a seamless and
    effortless manner the contents of an image
    selection
  • The modification can be
  • Replacement by
  • Mixing with other images
  • Alternations of some aspects of the original
    image, such as texture, illumination or color
  • No need for precise object delineation

34
Extensions to Poisson Editing
  • 3D mesh editing
  • Guided vector field
  • Image matting
  • Good boundary finding

35
Drag-and-Drop Pasting
  • http//www.cse.cuhk.edu.hk/leojia/all_project_web
    pages/ddp/drag-and-drop_pasting.html

36
(No Transcript)
37
Detail Preserving Shape Deformation in Image
Editing
  • http//graphics.cs.uiuc.edu/huifang/deformation.h
    tm

38
photomontage
  • http//grail.cs.washington.edu/projects/photomonta
    ge/

39
Efficient Gradient Domain Editing
  • http//agarwala.org/efficient_gdc/comparisons
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