Block wise Low rank Texture Characterization based Cartoon Texture Image decomposition || 2015-2016 IEEE MATLAB Project

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Block wise Low-Rank Texture Characterization
based Cartoon-Texture Image Decomposition

• Presented by
• IIS TECHNOLOGIES
• No 40, C-Block,First Floor,HIET Campus, North
  Parade Road,St.Thomas Mount, Chennai, Tamil Nadu
  600016.
• Landline044 4263 7391,mob9952077540.
• Emailinfo_at_iistechnologies.in,
• Webwww.iistechnologies.in

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ABSTRACT

• Using a novel characterization of texture, we
  propose an image decomposition technique that can
  effectively decomposes an image into its cartoon
  and texture components.
• The characterization rests on our observation
  that the texture component enjoys a blockwise
  low-rank nature with possible overlap and shear,
  because texture, in general, is globally
  dissimilar but locally well patterned.
• More specifically, one can observe that any local
  block of the texture component consists of only a
  few individual patterns.
• Based on this premise, we first introduce a new
  convex prior, named the block nuclear norm (BNN),
  leading to a suitable characterization of the
  texture component.
• We then formulate a cartoon-texture decomposition
  model as a convex optimization problem, where the
  simultaneous estimation of the cartoon and
  texture components from a given image or degraded
  observation is executed by minimizing the total
  variation and BNN.

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ABSTRACT

• In addition, patterns of texture extending in
  different directions are extracted separately,
  which is a special feature of the proposed model
  and of benefit to texture analysis and other
  applications.
• Furthermore, the model can handle various types
  of degradation occurring in image processing,
  including blur missing pixels with several types
  of noise.
• By rewriting the problem via variable splitting,
  the so-called alternating direction method of
  multipliers becomes applicable, resulting in an
  efficient algorithmic solution to the problem.
• Numerical examples illustrate that the proposed
  model is very selective to patterns of texture,
  which makes it produce better results than
  state-of-the-art decomposition models.

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EXISTING METHODS

• (isotropic) Total Variation
• G-norm
• Numerical implementations and applications

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PROPOSED METHOD

• A cartoon-texture decomposition model with a
  novel texture prior named the Block Nuclear Norm
  (BNN).
• Using BNN, our model interprets the texture
  compo- nent as the combination of blockwise
  low-rank matrices with possible overlap and
  shear, which leads to a suitable char-
  acterization of globally dissimilar but locally
  well-patterned nature of texture.
• The convex optimization problem associated with
  the proposed model is efficiently solved by ADMM.

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TOOLS AND SOFTWARE USED

• Operating system Windows XP/7.
• Coding Language MATLAB
• Tool MATLAB R 2010a

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OUTPUT

• SIMULATION

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Contact

• IIS TECHNOLOGIES
• No 40, C-Block,First Floor,HIET Campus, North
  Parade Road,St.Thomas Mount, Chennai, Tamil Nadu
  600016.
• Landline044 4263 7391,mob9952077540.
• Emailinfo_at_iistechnologies.in,
• Webwww.iistechnologies.in