Acquiring and Processing Electron, X-ray, and CL images

1
Electron probe microanalysisEPMA

• Acquiring and Processing Electron, X-ray,
  and CL images

2
Whats the point?

• A picture is worth a thousand words.
• The more we know about how images are acquired
  and processed, the better we can present research
  results graphically.
• Additionally, 2 or 3 dimensional information
  about specimens can be extracted from some
  images.

3
Image Acquisition

• Secondary electron images
• Backscatter electron images
• X-ray maps (WDS, EDS)
• Dot maps
• Counter maps
• Cathodoluminescence images
• Microscope (camera) images
• MicroImage vs Matrox framegrabber

4
Image Processing Analysis

• Image acquisition
• Image storage
• Image defects/correction
• Image enhancement
• Segmentation and thresholding
• Processing in frequency space
• Processing binary images
• Image measurements
• Image presentation

5
Resources

• Software
• MicroImage (interfaces with SX51)
• Matrox Intellicam (interfaces with SX51 video
  display)
• NIH/Scion Image for a manual-article-tutorial
  , go to rsb.info.nih.gov/nih-image/more-docs/Tutor
  ial/Contents.html
• Adobe Photoshop
• Image Processing Tool Kit (Russ/Reindeer Games)
  plug-ins for Photoshop
• Graphic Converter (Mac)
• Books
• The Image Processing Handbook by John C. Russ,
  3rd Ed, 1999, CRC Press (he teaches a week-long
  short course at North Carolina State University)
• Quick Photoshop for Research, A guide to digital
  imaging for Photoshop 4xd, 5x,6x,7x by Jerry
  Sedgewick, 2002, Kluwer Academic/Plenum Publishers

6
Secondary electron images
Everhart-Thornley detector low-energy secondary
electrons are attracted by 200 V on grid and
accelerated onto scintillator by 10 kV bias
light produced by scintillator (phosphor surface)
passes along light pipe to external
photomultiplier (PM) which converts light to
electric signal. Back scattered electrons also
detected but less efficiently because they have
higher energy and are not significantly
deflected by grid potential. (image and text
from Reed, 1996, p. 37)
SE imaging the signal is from the top 5 nm in
metals, and the top 50 nm in insulators. Thus,
fine scale surface features are imaged. The
detector is located to one side, so there is a
shadow effect one side is brighter than the
opposite.
7
BSE images
A solid-state (semi-conductor) backscattered
electron detector (a) is energized by incident
high energy electrons (90 E0), wherein
electron-hole pairs are generated and swept to
opposite poles by an applied bias voltage. This
charge is collected and input into an amplifier
(gain of 1000). (b) It is positioned directly
above the specimen, surrounding the opening
through the polepiece. In our BSE detector, we
can modify the amplifier gain BSE GMIN or BSE
GMAX.
BSE imaging the signal comes from the top .1 um
surface solid-state detector is sensitive to
light (and red LEDs). Above, 5 phases stand out
in a volcanic ash fragment
Goldstein et al, 1992, Fig 4.24, p. 184
8
Variations on a theme
There are several alternative type SEM images
sometimes found in BSE or SE imaging (left)
channeling (BSE) and (right) magnetic contrast
(SE). I have found BSE images of single phase
metals with crystalline structure shown by the
first effect, and suspect the second effect may
be the cause of problems with some Mn-Ni phases.
Crystal lattice shown above, with 2 beam-crystal
orientations (a) non-channeling, and (b)
channelling.Less BS electrons get out in B, so
darker.
From Newbury et al, 1986, Advanced Scanning
Electron Microscopy and X-ray Microanalysis,
Plenum, p. 88 and 159.
9
EBSD
Electron backscatter diffraction is a relatively
new and specialized application whereby a
specimen (say single crystal) is tilted acutely
(70) in an SEM with a special detector
(camera). The electron beam interacts with the
crystal lattice and the lattice planes will
diffract the beam, with the backscattered
electrons striking the detector, yielding sets of
intersecting lines, which then can be indexed and
crystallographic data deduced.
Also referred to as Kossel X-ray diffraction,
and Kikuchi patterns.
(Left) EBSD pattern from marcasite (FeS2)
crystal. (Right) Diagram showing formation of
cone of diffracted electrons formed from a
divergent point source within a specimen.
Dingley and Baba-Kishi, 1990, Electron
backscatter diffraction in the scanning electron
microscope, Microscopy and Analysis, May.
10
BSE and SE Detectors on our SX51
Annular BSE detectors
Anti-contamination air jet
Plates for voltage for SE detector
View from inside, looking up obliquely (image
taken by handheld digital camera)
11
Cathodoluminescence

• This is an optical phenomenon. CL occurs in
  semiconductors, be they man-made or natural
  (i.e., some minerals). Electrons in the valence
  band of these materials are excited into the
  conduction band for a brief time subsequently
  these electrons recombine with the holes left in
  the valence band. The energy difference is
  released as a photon of wavelength of light.
• Two commonly used applications are
• Locating strain (lattice mismatch) in
  semiconductors, and
• Evaluating minerals for heterogeneous growth
  (complex history, overgrowths, dissolution, crack
  infilling)
• There are two distinct methods to image this
  effect by SEM or microprobe, or by a small
  attachment to an optical microscope (static cold
  cathode electron source). Additionally, the light
  spectra can be quantified by a scanning
  monochronometer.

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CL in living color
CL captured on color film A Casserite,
SnO2 B Crinoidal limestone
C Red dolomite, orange calcite
dark grey baddeleyite (ZrO2)
D St Peter Sandstone mature quartz with zoned
authigenic quartz overgrowths (from
Marshall,1988, CL of Geological Materials)
A
B
D
C
The CL emitted is of varying wavelengths
(colors), and can be captured with the right
equipment. Various CL microscope attachments
have been built that fit on the stage of a
regular microscope one model is the Luminoscope.
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CL Microscope Attachments
Cold cathode gun

• CMAs are relatively inexpensive attachments to
  microscopes. A high voltage (10-30 keV) cold
  cathode gun discharges electrons in a low vacuum
  chamber (rough pump only). A plasma results that
  provides charge neutralization (no carbon coating
  necessary). A camera and/or monochrometer are
  attached to acquire images and/or wavelength
  scans of the light.

(From Marshall, 1993,The present stat of CL
attachments for optical microscopes, Scanning
Microscopy, Vol 7, p. 861)
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CL colors and eV

• The figure on the left demonstrates several
  different mechanisms whereby photons are emitted
  in the process of high voltage electrons
  promoting valence electrons to conduction band.
  The various band gap energies with their
  respective wavelengths and colors is shown to the
  right.

(Right image from Marshall, 1988, Fig 1.4, p. 4)
15
CL defects in GaAs
These and the following CL images are
mono-chromatic only the total light intensity at
each pixel is recorded by a photomultiplier.
This is a common (simple/cheap) attachment for an
SEM or microprobe.
GaAs on Si for optoelectronic devices can have
defects due to lattice mismatch between the film
and Si substrate. The defects are not seen in SE
image (top left). However, a CL image (bottom
left) shows the areas of reduced strain, where a
monochronometer collected 800 nm light. The right
figure shows the CL spectra of strained (top) vs
unstrained (bottom) material.
Peter Heard, 1996, Cathodoluminescence--Interestin
g phenomenon or useful technique? Microscopy and
Analysis, January, p. 25-27.
16
CL quartz, zircon
CL
BSE
CL

• Images acquired with the Cameca CL (PM) detector.
  Left quartz from Skye with complex history of
  growth or re-equilibration with hydrothermal
  system. Trace amounts of Al, Ti or Mn may be
  involved. Right CL image of zircon from
  Yellowstone tuff (false color) adjacent BSE
  image (no zonation obvious).

(from research of Valley, and Bindeman and Valley)
17
X-ray maps
Mg Ka (Olivines in basalt lava)

• There are two modes of X-ray mapping dot
  (digital) or counter (pulse). The top images
  are the grainy, coarse resolution dot maps,
  whereas the bottom images are the higher
  resolution counter maps.The later is more timely
  to acquire, but is worth the wait. Note the WDS
  defocusing.

Dot Maps
Counter Maps
EDS
WDS (TAP)
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X-ray map defocus
Enlarged representation of plan view of each
spectrometer crystal
Low mag (63x) WDS maps on metals Sp14Si Ka
(TAP), Sp35 Fe Ka (LIF), Sp2Fe La (PC1) also
EDS below
Birds Eye View of SX51
Large Area PC1
Note large solid angle of EDS above
Area of each crystal on Rowland Circle
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Mosaic Images

• There are occasions where the feature you wish to
  image is larger than the field of view acquirable
  by the rastered beam. A complete thin section
  (24x48 mm) can have a mosaic BSE image acquired
  in lt 1 hour (though an X-ray map could take a
  week, so only smaller areas are typically X-ray
  mapped.) This is achieved by tiling or mosaicing
  smaller images together. The software calculates
  how many smaller images are needed based upon the
  field of view at the magnification used, drives
  to the center of each rectangle, and then
  seemlessly stitches the images into one whole.
  The false colored BSE image of a cm-sized zoned
  garnet to the right was made by many (gt100) 63x
  scans (each scan 1.9 mm max width).

From research of Cory Clechenko and John Valley.
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X-ray maps . And the Clock
3 X-ray maps combined each element set to a
color, and then all merged together in Photoshop.
The maps took 8 hours to collect.
Reed, 1996, Fig 6.1, p. 102

• X-ray maps can provide useful information as well
  as attractive eye candy. However, due to the
  low count rate of detected X-rays, dwell times
  generally need to be hundreds of milli-seconds. A
  512x512 X-ray map at 100 msecs takes 8 hours to
  acquire. Large area maps that combine beam and
  stage movement require additional overhead
  (1-10) for stage activity. The recent
  improvements to our EDS system give us more
  leeway, as the larger solid angle of EDS and
  improved digital processing throughput lets us
  use 1-10 msec dwell times, as well as allowing
  low mag images (no need to worry about Rowland
  circle defocusing).

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X-ray maps Fully quantitative
3 X-ray maps combined each element set to a
color, and then all merged together in Photoshop.
The maps took 8 hours to collect.
The X-ray maps usually acquired are quantitative,
although not to the maximum extent possible,
i.e., the background is not subtracted, nor is
the matrix correction applied. These operations
can be applied, to make the X-ray map fully
quantitative, as the adjacent 5 maps are to
save time in this case, backgrounds were not
acquired, rather the MAN background technique was
applied, and peaks were counted for 10 secs,
within the Probe for Windows software, and the
results were then graphed with Surfer.
22
MicroImage digital scan

• BSE images 2 ways

Matrox Intellicam framegrabber
There are two different ways to save video (BSE,
SE, CL) image files (right) the MicroImage
software takes control of the beam and scans the
image, writing all the pixels to a file (left)
the native Cameca scan on the right Sony monitor
is stored by the Matrox framegrabber. Both images
here have 442x103 pixels, but the Matrox is much
quicker (10 seconds, vs gt4 minutes for the
MicroImage), though the frame grab is limited to
small regions that can be encompassed at 63x
(1.9 mm wide). The Matrox image is 768 x 576,
whereas the MicroImage can be any dimension and
can also be combined with stage movement to give
large mosaic images.
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Image Acquisition

• Consider
• What Image depth? 8 bit (SE,BSE,CL) or 16 bit
  (X-ray which translates into 256 vs 65536
  intensity (gray) levels
• Image size
• mm in x and y (rectangular vs square depends on
  machine/software)
• pixels in x and y
• Image resolution-- is it sufficient for the
  need? mm/pixel total pixels final printed
  size gt will determine whether or not it is
  pixelated
• Image size total kb or mb. Storage can become
  an issue when you have lots of large (gt 2 mb)
  images, but with todays storage options, this
  is less difficult, as students can afford 250 mb
  Zip disks.
• Time for acquisition SE,BSE,CL is rapid X-rays
  require much longer time
• EDS spectra sometimes a picture of two
  contrasting spectra is useful.
• Adjust conditions (brightness, contrast) for
  optimal image quality BEFORE you acquire. Be sure
  not to oversaturate the brightest phases.
• Record conditions (keV, nA, dwell time, mag) in
  your lab notebook (scale bar may NOT be
  necessarily saved on image)

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Histogram Stretching Before BSE Acquistion
Using MicroImage
While beam is scanning, adjust contrast (gain)
as well as brightness (offset) if necessary to
achieve desired contrast and brightness. Then set
to final image size (512 or anything) and collect
1 image.
We want to do some rapid scans and watch the
histogram improve. Set to small size image and to
continuous image refreshing
First try contrast could be better. Need to
tweak gain
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SX51Microscope Images

• The Cameca Cassegrainian objective lens optics
  are excellent, as seen in these images (left
  reflected right transmitted light) captured
  with the Matrox framegrabber. There are
  occasional instances where there is value in
  preserving the reflected light image (e.g.,
  locations of beam preserved as carbon
  contamination spots cathodoluminescence).
  (scale 400x, 300 microns across)

26
Image Storage

• Best if software saves file automatically (not
  always the case) you always should save
  originals before you start to play with the
  images always fiddle with copies, not originals
• Use clear, descriptive names for your images
• Original format sometimes is not a choice by
  user (i.e.,proprietary format may be default, or
  quasi-generic with a specialized header taking up
  the first 1000 bytes though most software
  today are versatile)
• If format choice is possible, TIFF is a good
  choice for storage keeps maximum amount of
  information (not lossy compressed)
• You particularly want to keep the original 16
  bit data of the X-ray image, to be able to
  extract actual counts. However, to display images
  you need to rescale (normalize) to 8 bits.
  Thus, you will commonly have 2 versions of each
  X-ray map.
• It is acceptable to reformat as smaller jpeg
  format for use in presentations (e.g.,
  powerpoint, illustrator) and publications
• Transfer your images to your own computer in a
  timely manner (they will remain on probe lab
  computer for a limited period (1-3 years?)

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Some Image Formats

• TIFF currently most universal, well suited for
  large images. Lossless compression (image does
  not degrade with repeated opening/closing).
  Photoshop gives option of LZW compression, best
  not used. (Tagged Information File Format)
• JPEG Name refers to a compression method that
  is Lossy there is some loss of exact pixel
  values square subregions are processed with
  cosine transform operation compression of 101
  to 1001 is possible (Joint Photography Experts
  Group)
• Photoshop (psd) layered image must flatten if
  to be used elsewhere.
• Adobe Acrobat (pdf) non-Lossy compression

Graphic Converter (Mac) is a Swiss Army tool
program that can open about any format you can
think of, and save to anything else.
(Share/cheapware)
Lossy compression throws away some data to better
compress the image size different schemes focus
on different features, i.e. JPEG is based on fact
that human eye is more sensitive to changes in
brightness than in color, and more sensitive to
gradations of color than to rapid variations
within that gradation. JPEG keeps most brightness
info and drops some color info.
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Image Defects

• Correct conditions beforehand! It is best not to
  modify your images.
• Two possible defects in BSE images
• horizontal lines in BSE images comes from 50
  cycle AC of lights, esp at high contrast. Best to
  turn off the light
• uneven shading in large area mosaic images
  (bright upper left corner) due to BSE detector
  picking up light from stage LEDs. It may be
  possible to apply a correction in Photoshop.
  Alternatively put a dummy thin section there and
  image thin sections in other positions in holder.
• SE images have brighter right side due to
  detector being there. As far as I know, there is
  nothing we can do about it.
• Watermarks etc. Sometimes artifacts occur. If
  small, they do not detract just include a note.
  If large, best to acquire another image.

29
Image Enhancement - by Machine

• A major negative feature of images can be
  noise, i.e., the features are not as sharp as
  they could/should be. The prime reason is the
  scan rate is very fast and the time paid to each
  pixel is microseconds. The top image is at the
  normal mode TV rate.
• This can be addressed by acquiring multiple
  images and averaging them, to reduce the random
  noise. Or better to utilize a scanning mode that
  goes slower, acquires longer counts on each
  pixel, averaging each pixel on the fly. The
  bottom image is at the Nice image (sxgtmode user
  1 1 line) rate, taking 10 seconds.

30
Image Enhancement - Done Later

• Histogram normalization crunching from 16 to 8
  bit. This usually is a first step for visual
  presentation purposes, as most software packages
  only operate on 8 bit images. However, this does
  not apply for measuring absolute values of pixel
  intensity, such as X-ray counts.
• Brightness/contrast (and importantly, gamma)
  adjusting histogram levels
• Histogram equalization divide intensities into
  equal/weighted number of categories
• Kernels/Rank operators modify each pixel by
  some operation upon it and nearest neighbors
• Image math background subtraction ratio 2
  elements
• Processing in frequency space (Fourier
  transform) removing periodic noise
• Applying alternate lookup tables (LUTs) for
  improved presentation

31
Intensities, Histograms, LUTs

• All images we are concerned with (e.g.,
  BSE, CL, X-ray) contain one channel of
  information, where each constituent pixel has a
  value from 0 to 255 (28) or 65535 (216). These
  can be ordered in a histogram of intensities,
  with the spread defining the contrast, and the
  absolute values defining how bright or dark the
  image is. These INPUT intensities are mapped onto
  an OUTPUT grayscale or color table known as a
  Look Up Table (LUT).
• The transfer function is known as gamma.
  A gamma of 1.00 indicates a linear relationship
  between pixel intensities and grayscales. A gamma
  gt1 is a non-linear function where the darker
  pixels are made preferentially brighter, whereas
  gamma lt1 has the very bright pixels
  preferentially darkened somewhat.
• Adjusting only brightness and
  contrast controls (highlighted in many image
  packages) generally give poorer results compared
  to tweaking the gamma as part of histogram
  adjustment.

LUT
32
Brightness and Contrast or How I Learned to Love
the Histogram
Adjust gLevels
Photoshop
The original histogram is too bunched up poor
contrast. Notice the top (input) left and right
sliders are not close to the min/max brightness.
So we move the top (input) left and right sliders
in to the min/max brightness levels.And we move
the bottom (output) sliders to 10 and 254.
A last (important) step is to adjust the gamma,
the top middle slider. To left (higher) increases
brightness of mid grays (normally the best
option).
33
Gamma Processing
Goldstein et al, 1992, Fig. 4.53, p. 238
The traditional imaging medium, photographic
paper, has a non-linear response to light
exposure through the overlying negative. Skilled
darkroom technique used this to bring out subtle
features in the shadows, or enhance bright
features that tend to wash out. For digital
images, such nonlinear processing, gamma
processing, provides selective contrast
enhancement at either the black or white end of
the gray scale, while preventing saturation or
clipping of the resulting image. The signal
transfer function is defined as
where g is an integer (1, 2, 3,
4) or a fraction (1/2, 1/3, 1/4) and K is a
linear amplification constant. For g2, a small
range of input signals at the dark end of the
gray scale are distributed over a larger range of
output gray levels, enhancing the contrast here
signals at the white end are compressed into
fewer gray levels. For g 1/2, expansion occurs
at the bright end, enhancing bright features.
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Histogram Levels Equalization
One alternative/complementary procedure to manual
adjust of brightness/contrast is equalization,
which can be applied to the raw image. It
stretches out the histogram, with the distinction
that it separates the intensities into weighted
bins, so that if there are a lot of pixels piled
in a few bins, these bins (intensities) will have
a larger number of new intensities mapped onto
them i.e., there will be spaces between them
on the histogram, meaning those intensities will
be stretched out. At the same time, bins with not
many pixels in them may be squeezed together, as
there is less total information relative to the
high populated pixels.
Russ, 1999, Fig. 4.11, p. 238.
35
Kernels/Rank Operators

• Noisy images sometimes occur for a variety of
  reasons, some avoidable, some not. Noise refers
  to some randomness added to pixel intensity
  values, with noise worse where count rates are
  low. The simplest procedure to reduce noise is
  to take the average of the pixel and its
  surrounding neighbors, and put this new average
  value in as the new pixel intensity. You can
  create a matrix with values for the coefficient
  by which you weigh (multiply) each pixel and
  adjoining neighbors. For example, one such matrix
  could be
• 1 1 1 and 1 2 1
• 1 1 1 another 2 4 2 1 1 1 1 2 1
• These are called kernels, or rank operators.
• Say there was a noisy pixel with a value of
  100, when all the adjoining values were 10. The
  first kernel would return a new value of 20, and
  the noise would be drastically reduced.

36
Neighborhood averaging
Results of applying one kernel
a) A noisy original image,
b) each 4x4 block of pixels is
averaged (less noise, but too coarse),
c) each pixel replaced by average of
3x3 neighbor-hood ( pretty nice),
d) each pixel replaced by average of
11x11 neighborhood ( less noise, but too big,
causing blurring)
Russ, 1999, The Image Processing Handbook (3rd
edition), Fig 3.3, p. 166
37
Image Math
The values of each pixel can be operated on (e.g.
multiplied, divided, added or subtracted relative
to some constant), or different elements of the
same image can be operated on. The most common
operations are division and subtraction. Two
elements that vary together (e.g. Ca and Na in
feldspar) can be divided to yield an optimized
zonation map. Subtraction is useful for removing
the continuum contribution, particularly for
minor or trace elements.
Goldstein et al, 1992, Fig 10.6, p. 535
Above is an example of false compositional
contrast, an artifact of the background being a
function of Z (MAN). Specimen is Al-Cu eutectic
X-ray maps are (a) Al, (b) Cu, (c) Sc. The
contrast in (c) suggests Sc is present in the
Cu-rich phase. However, there is no Sc, only the
background in the Cu-rich phase is elevated
relative to the background in the Al-rich phase.
If image math is used subtracting an additional
X-ray map acquired at an off-peak (background) Sc
position a true map of Sc is seen in (d), where
it is clear there is no Sc present.
38
2 Dimensional Histograms
Another mining of X-ray images utilizes both
the elemental information as well as the spatial
(X,Y) coordinates. Micro-Image includes a unique
histogram-histogram plotting feature for
unambiguous identification of numerous phases. In
this screen shot, the lower right image displays
a histogram-histogram plot which shows the
presence of at least 6 phases including a solid
solution
component. The upper right image display a
"traceback" of one selected phase cluster which
provides black and white mask of spatial
information. (From the Advanced Microbeam Inc
webpage)
39
Processing in Frequency Space
Examples from Russ, Image ProcessingTool Kit
Tutorial, Part 4, Fig 4.C.1, page 8.
If there periodic noise in an image (e.g., the 2
frequencies on top of the clown image), the image
can be processing by a Fast Fourier Transform
(FFT) of it, as is done in the small subregion in
the left frame. The 2 frequencies of noise show
up as 2 pairs of dots (the clown features are the
NS, EW lines and center dot). If 4 small solid
circles are placed upon the
4 dots and then the resulted inverted, a mask is
made (center), which is then subtracted from the
left FFT image. Then an inverse FFT operation is
done on this image, and the result is the right
image, where the noise is removed. These
operations must be done on square images, using
NIH Image or Russs Image Toolkit with Photoshop.
40
Look Up Tables

• The mapping of intensites (e.g., BSE voltages or
  X-ray counts) to a displayed image uses a Look Up
  Table, the most common one being a gray scale.
  The default with MicroImage is the thermal LUT.
  There are many others, and you can make up your
  own. It is a good idea to display the LUT as a
  bar next to the image if they might be some
  confusion as to what color means what intensity.

Gray scale Fire 1 Fire 2 Rainbow Ice
Some LUTs from NIH Image
41
Processing binary images

• When we acquire images, we are in essence
  acquiring information about features defined as
  compositions, or sizes or shapes, of phases or
  boundaries or whatever. Our eyes brains are
  sorting out features constantly, such as in the
  process of sorting out the black lines and shapes
  against the white background here, translating
  into words and then into meanings.
• We can apply similar binary operations to our
  images focusing on one characteristic and
  ignoring the rest for the moment. This is known
  as thresholding, where we set upper and lower
  thresholds of intensity (e.g., BSE) and then
  define as a feature (e.g., one phase) the
  intensities that fall in between. Software can
  then be applied to such a binary image to do many
  things, e.g., count the number of pixels (thus,
  determine phase area).
• Boolean (logical) operations can be done on sets
  or images, taking two element maps and create a
  third one that shows the regions where features
  containing both elements are present, or only one
  without the other. Morphological operations can
  be done to modify individual pixels within an
  imageapply erosion and dilation operators to
  separate touching phases and then count total
  number of separate phases or measure the
  dimensions or orientation of each.

42
Thresholding
NIH Image provides an easy way to threshold
images, shown here. You double click the little
up/down icon (6th from top, right column) which
gives you a red sliding palette that you use to
color in the phase you are selecting. You then
click Measure under the Analyze menu and the
total number of pixels is shown in the Info Box.
If you do this for all the phases
Cr-spinel 57208/44222512.9, Mg-rich
clay 215634/442225 48.8, Diopside
153904/44222534.8, Cracks
14947/4422253.4 Total (without fudging!)
99.9
Present, you should be able to get a total of
1005 easily.
43
Making an Image into a Binary
Besides being able to determine area percentages,
you use the thresholded region to make a binary
image of that one feature/phase. In NIH Image it
is simple Process gt Binary gt Make Binary. The
result of that operation is shown in the center
image. Note that there are some outliers,
mainly in cracks. You need to
make some reasoned judgements about whether or
not to include them. Here, I decided not to
include them, so I then did 2 consecutive erode
operations (under Binary menu), and then 2
consecutive dilate operations, to yield the
final image on the right. Of course there could
well be cases where you would not do the erodes.
44
Boolean Operations
Binary images consist of groups of pixels
selected on the basis of some common property.
Logical or Boolean operations can be applied,
pixel by pixel, to sets of images. The logical
operations typically are AND, OR, XOR (exclusive
or), NOT. The logical operator looks at each
pixel to see if it is on or off. AND
requires both pixels be ON to be ON in the
result. OR if either pixel is ON, it will be ON
in the result. XOR turns a pixel ON in the
result only if it is ON in only one, not both, of
the images. All 3 require 2 images. The NOT
operator only requires one, and it reverses the
meaning of each pixel.
Original X-ray maps (top) c) Si, d) Fe These
have been smoothed and thresholded to make binary
images. The thresholded Fe image is shown below
left (a), with Fe black. The Fe and Si images
have been combined as Fe AND NOT Si, to yield the
right (b) image of the Fe-oxide phase, excluding
the Fe-silicate phase.
From the symbolic logic developed by George
Boole, British mathematician, 1815-1864
Russ, The Image Processing Handbook, 1999, Figs
7.5, 7.6, p. 436.
45
Color Superposition of Elemental Maps
While not strictly a Boolean operation (not
binary images), by defining each elemental map
with hues of either R, G or B, and then combining
(flattening) the image in Photoshop, phase
information can be extracted. Images from
research of Josh Kearns and Jill Banfield sand
from Tanana River, central Alaska
46
Erosion/Dilation
Sometimes you want to measure features but the
binary image isnt unambiguous, as shown in the
example to the right. Here, you are attempting to
measure the area of the middle gray phase (a),
but when you threshold it, there are outlines of
the bright phase (b). The outline is only 1 pixel
wide, so you can apply an erode operation, which
will remove the outlines that you want to get rid
of, but also it will remove the outer layer of
pixels from all of the features you are
interested in (c). No problem.
Just apply the dilate operation, and where there
are any existing pixels, there will be added a
layer of pixels (d), and now you can do your
measurement.
Russ, The Image Processing Handb ook, 1999, Fig.
7.36, p. 462
47
Image measurements
Geology 777
ImageJ 1.28
NIH Image 1.63
Features in images lend themselves to measurement
without too much difficulty
48
Conclusion

• Imaging covers a wide range of topics and we have
  just skimmed the surface here.