5th Intensive Course on Soil Micromorphology

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5th Intensive Course on Soil Micromorphology
Naples 2001
12th - 14th September Image Analysis
Lecture 10 Advanced Image Restoration Other
Methods - Batch Processing
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5th Intensive Course on Soil Micromorphology -
Naples 2001 Image Analysis - Lecture 10
Advanced Image Restoration
Image Restoration.

• All Imaging involves imperfection
• - no matter how good the optics are
• Non-standard illumination lecture 5
• Blurring from defects in lenses
• Specimen Beam interactions in SEM

• Other Methods
• Optical Diffraction and Convolution
• Photogrammetry

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5th Intensive Course on Soil Micromorphology -
Naples 2001 Image Analysis - Lecture 10 Image
Restoration
Example from Lecture 5
Though not perfect, the background illumination
has been suppress making thresholding much easier.
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5th Intensive Course on Soil Micromorphology -
Naples 2001 Image Analysis - Lecture 10
Advanced Image Restoration
Image Restoration.

• SEM
• electron beam hits specimen and spreads through
  specimen
• information about specimen comes from an area
  larger than beam
• Problem
• Sharp edges will become blurred
• loss of resolution

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5th Intensive Course on Soil Micromorphology -
Naples 2001 Image Analysis - Lecture 10
Advanced Image Restoration
Specimen Beam interaction in SEM
Specimen Beam Spreads within specimen. Two
different areas are represented by blue and green
areas.
The idealised output is degraded as information
comes from both parts of the specimen.
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5th Intensive Course on Soil Micromorphology -
Naples 2001 Image Analysis - Lecture 10
Advanced Image Restoration
Image Restoration.

• If the intensity at the point x,y is a function
  f(x,y)
• and the spreading function is similarly defined
  as h(x,y)
• Then the actual image obtained g(x,y) is given by

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5th Intensive Course on Soil Micromorphology -
Naples 2001 Image Analysis - Lecture 10
Advanced Image Restoration
Image Restoration.
Image 1 Rosette Diagram Diffraction Pattern
(Fourier Transform) Note high frequency peaks
at large Fourier Spacings
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5th Intensive Course on Soil Micromorphology -
Naples 2001 Image Analysis - Lecture 10
Advanced Image Restoration
In reality, there will always be noise
present. i.e.
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5th Intensive Course on Soil Micromorphology -
Naples 2001 Image Analysis - Lecture 10 Batch
Processing

• Determination of Point Spread Function in SEM
• use an object with a sharp edge - of comparable
  BSE reflectivity to objects to be viewed and in
  similar matrix.
• e.g. glass / resin boundary
• capture image (preferably several)
• determine the distance that the intensity takes
  to go from say 90 to 10 across the boundary and
  this indicates the spreading.
• Ideally, several different images at different
  orientation should be taken.

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5th Intensive Course on Soil Micromorphology -
Naples 2001 Image Analysis - Lecture 10 Batch
Processing
Some Results of consolidated Kaolin and Silt/Clay
Mixtures
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5th Intensive Course on Soil Micromorphology -
Naples 2001 Image Analysis - Lecture 10
Advanced Image Restoration
Image 1
Note that though the contrast is less, the detail
and resolution is much better in restored image.
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5th Intensive Course on Soil Micromorphology -
Naples 2001 Image Analysis - Lecture 10
Advanced Image Restoration
Image 2
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5th Intensive Course on Soil Micromorphology -
Naples 2001 Image Analysis - Lecture 10
Advanced Image Restoration
Image 3
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5th Intensive Course on Soil Micromorphology -
Naples 2001 Image Analysis - Lecture 10
Advanced Image Restoration
Image 4
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5th Intensive Course on Soil Micromorphology -
Naples 2001 Image Analysis - Lecture 10
Advanced Image Restoration
Image 5
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5th Intensive Course on Soil Micromorphology -
Naples 2001 Image Analysis - Lecture 10
Advanced Image Restoration
Image 6
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5th Intensive Course on Soil Micromorphology -
Naples 2001 Image Analysis - Lecture 10
Advanced Image Restoration
Image 7 - Consolidated Silt (Quartz) / Kaolin
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5th Intensive Course on Soil Micromorphology -
Naples 2001 Image Analysis - Lecture 10
Advanced Image Restoration
Image 8 - Consolidated Silt (Quartz) / Kaolin
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5th Intensive Course on Soil Micromorphology -
Naples 2001 Image Analysis - Lecture 10
Advanced Image Restoration
Image 9 - Consolidated Silt (Quartz) / Kaolin
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5th Intensive Course on Soil Micromorphology -
Naples 2001 Image Analysis - Lecture 10
Objective Thresholding

• best possible that can be achieved.
• No OPERATOR involvement (no subjectivity).

Objective Thresholding
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5th Intensive Course on Soil Micromorphology -
Naples 2001 Image Analysis - Lecture 10
Objective Thresholding
Case with Several Phases
For objective segmentation - the peaks must be
identified and these are used to set threshold
level.
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5th Intensive Course on Soil Micromorphology -
Naples 2001 Image Analysis - Lecture 10
Objective Thresholding
Thesholding Interactive selection of threshold
will be unreliable and may well differ
significantly from one person to another.
Data from 2nd and 3rd Intensive Courses
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5th Intensive Course on Soil Micromorphology -
Naples 2001 Image Analysis - Lecture 10
Objective Thresholding
Binary Segmentation with and without image
reconstruction. Porosity is approximately the
same in both cases. But Void Size / Particle
Size distribution is very different
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5th Intensive Course on Soil Micromorphology -
Naples 2001 Image Analysis - Lecture 10
Objective Thresholding
Stages in Analysis

• Original Image
• Restored Image
• Objective Threshold
• Combination with Domain-Segmentation

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5th Intensive Course on Soil Micromorphology -
Naples 2001 Image Analysis - Lecture 10
Objective Thresholding
Image 1
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5th Intensive Course on Soil Micromorphology -
Naples 2001 Image Analysis - Lecture 10
Objective Thresholding
Image 3
Surprisingly horizontal domains are more porous
than vertical ones
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5th Intensive Course on Soil Micromorphology -
Naples 2001 Image Analysis - Lecture 10
Objective Thresholding
The advantages of Image Restoration are seen in
binary images
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5th Intensive Course on Soil Micromorphology -
Naples 2001 Image Analysis - Lecture 10
Objective Thresholding
Summary
Image Restoration provides a best estimate of
what image would be without degradation from
optics/recording system resolution is
significantly improved important for void /
particle size distribution Objective thresholding
is possible using Relative Contrast Histogram
Method consistent results - avoid
subjectivity Can be combined with domain
segmentation to examine porosity in different
domain