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Report
Chapter 14
Landsat 7 image of the retreating Malaspina Glacier, Alaska
• Earth science is a very visual discipline
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Graphs
Maps
Field Photos
Satellite images
Landsat image of Death Valley, CA
• Because of this, all Earth scientists
should have:
Cathodoluminescence image
of granite
• Basic knowledge about graphics file types
• Pros/cons of different graphics file types
Siccar Point: The first recognized angular unconformity by James Hutton
Image: Chris Rowan @ Highly Allochthonous Blog
Photomicrograph of peridotite (mantle rock)
Sediment
Core
NED Dataset
• Made of pixels
• When you scale it, quality changes (finite # pixels)
• Common formats: jpg, png, gif, tif, bmp
• Made of vector objects (not pixel-based)
• Can scale to any size
• Common Formats: ai, eps, ps, svg, wmf, pdf
• For example, ai, pdf, eps, ps, wmf
• How can you tell? Zoom in on the image
Which is better?
• Depends on use
• For graphs/plots: typically
vector (unless data set is HUGE)
• For photos: raster
• MATLAB provides functions that read raster images
• Each pixel’s value (color) is stored as a number in matrix
• MATLAB also has an image processing toolbox with TONS of
image processing options.
• In this class, we will only use the image functions that are part of the
standard MATLAB libraries
• imread, image, imagesc, colormap,
Landsat false-color image examples…
Yukon River delta, Alaska
Mississippi River meanders & oxbows near
Memphis, TN
Novarupta Volcano, Aleutian Islands, Alaska
Purples/Reds: Volcanic ash from 1912 Eruption
Blues: Snow/Ice
• Before we start processing
images, we need to talk about
how computers represent colors
as numbers
• Three common color models
• RGB: An additive model
• works like light
• CMYK: A subtractive model
• works like ink
• HSV: A cone-shaped model
• useful for shading colors
• For variables of class uint8 (and 8-bit images)
• 0-255 are the possible integer values (same for the uint8 class!)
• 0 is minimum for any RGB color
• 255 is max for any RGB color
• To define any color, you must specify the Red (R), Green (G),
and Blue (B) values
• Wait, color can be a vector!
• Grayscale images only need one value (0=black, 255=white)
[000]
[ 255 255 255 ]
[ 75 75 75 ]
[ 200 200 200]
[ 255 0 0]
[ 100 0 0]
[ 0 255 0]
[ 0 100 0 ]
[ 0 0 255 ]
[ 0 0 100 ]
[ 255 255 0]
[ 0 255 255]
[ 255 0 255]
[ 237 125 49]
• Just to annoy us, MATLAB requires colormap RGB values
to be values between 0 and 1 for variables of class double
• 0 is minimum for any RGB color
• 1 is max for any RGB color
• To define any color, you must specify the Red (R), Green (G),
and Blue (B) values
• To convert from the 0-255 system, just divide by 255! Or cast as uint8
• Grayscale images really only need one value (0=black, 1=white)
[0 0 0]
[1 1 1]
[ 0 0.39 0 ]
[0 0 1]
[ 0.29 0.29 0.29 ] [ 0.78 0.78 0.78]
[ 0 0 0.39 ]
[ 1 1 0]
[ 1 0 0]
[ 0.39 0 0]
[ 0 1 0]
[ 0 1 1]
[ 1 0 1]
[ 0.93 0.49 0.19]
MATLAB can represent color in images in two basic ways
1) True Color or RGB
• The three color components are stored in a m x n x 3 matrix. I.e.
a 3D matrix.
(:, :, 1) R-values;
(:, :, 2) G-values;
(:, :, 3) B-values
2) Indexed to a Colormap
• Colors are stored as a single integer value that corresponds to a
row in a colormap matrix.
• Colormap stores the RGB values
4 Pixel Image
Colormap Matrix
1
0
0
1
0
1
0
1
0
0
1
1
Image Matrix
1 3
2 4
• ‘image’ plots a matrix
as an image
• Don’t forget to specify
the colormap
• If not, you get the
default 64 color ‘jet’
colormap
• MATLAB provides several built-in colormaps
• The command colormap is rather useful
• It can set the current colormap
• Can be a built-in map or a custom n x 3 matrix
• Built-in colormaps can be easily scaled
• E.g. “jet(256)” returns a 256 x 3 matrix that follows
the color scheme of the built-in “jet” colormap.
If ‘image’ is passed a 3D matrix
• It is assumed to be a true color
image
• 1st level R-values
• 2nd level G-values
• 3rd level B-values
If ‘image’ is passed a 2D matrix
• It is assumed to be an colormap
indexed image
• If you exceed the color
map values, you get either
the min or max color
Why does MATLAB offer two ways to
store image colors?
1) Flexibility. It is always good to give
users options
2) Grayscale vs Color Images
• These images are typically read in
MATLAB in different ways
• Grayscale: Indexed Color
• Color image: True Color or RGB image
• ‘imread’ can read in most
standard grayscale raster image
types
• .jpg .gif .png, etc…
• Stores image as a rectangular
matrix
• Each entry represents one pixel’s
grayscale value
•
Cropped grayscale image of dendrites
0-255 (black to white)
• Let’s read this image into MATLAB
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•
The image is 814 x 531 pixels
Matrix will be 531 x 814
• Try to automate detection of the
dendrites
Increased contrast (using Photoshop)
• If ‘image’ is given a 2D
matrix, it assumes the
image is indexed color
• ‘imread’ can read in most
standard RGB raster image types
Landsat image of Yukon River delta
• .jpg .gif .png, etc…
• Stores image as a 3D matrix
• Each entry represents one pixel’s R,
G, or B value
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•
•
•
0-255 (min/max)
1st z-slice = Red values
2nd z-slice = Green values
3rd z-slice = Blue values
• Let’s read this image into MATLAB
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The image is 1000 x 1001 pixels
Matrix will be 1001 x 1000 x 3
• Try to automate detection of the
water
Google Earth Image (aerial photo)

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