Welcome to EECS107 Fundamentals of Digital Image Processing

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Welcome toEECS107Fundamentals ofDigital Image
Processing
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What is this?
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What is this?
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What is this?
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What is this?
Map centre 3338'N 11750'W, width 15 degrees
7amJan. 9, 2003
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What is this?
View from 1,000,000km above 3338'N 11750'W
7amJan. 9, 2003
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Applications
Weather satellite (22,300 miles above the Earth)
Geostationary Operational Environmental Satellite
(GOES)White and grey areas cloud cover.Useful
in tracking the movement of storm systems,
particularly where radar data is not available.
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Applications
Weather satellite
East AsiaWhite and grey areas cloud cover.
Color cloud temperatureUseful in tracking the
movement of storm systems, particularly where
radar data is not available.
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Applications
Weather satellite
East AsiaWhite and grey areas cloud
cover.Useful in tracking the movement of storm
systems, particularly where radar data is not
available.
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Applications
Weather satellite
IndiaWhite and grey areas cloud cover.Useful
in tracking the movement of storm systems,
particularly where radar data is not available.
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Applications
Cloud radar
Northern California
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Applications
Cloud radar
New York Area
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Applications
Cloud radar
Southern California
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Applications
US Temperatures
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Applications
US Current Surface Winds
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Digital Image Processing

• Image
• Statistical Info
• Data

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Applications
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What is this?
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What is this?
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Image Acquisition
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Image Acquisition
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CT Scanner
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Rhesus Monkey Brain

• High-resolution large-scale image data
• RGB image series (real-color, dyed), 5037 x 3871
  x 1400, 76 GB
• (data courtesy of Edward G. Jones, Center for
  Neuroscience, UC Davis)

• Resolution 2666dpi
• Pixel spacing 9 mm
• Enables zoomingdown to the cell level.
• Total data size76 GB

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2-D Cross-sections
Cryosection of a human brain
Segmented human brain
CT scan
Cancer cell
Cross-sections of VOL format data sets stored on
HPSSextracted using VisTools
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2-D Cross-sections
Sample cross-sections of aCT scan of a human
skull
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2-D Cross-sections
Sample cross-sections of a human
skull(cryo-section)
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Image Segmentation

• RGB image series (real-color, human brain), 1472
  x 1152 x 753, 3.57 GB
• (data courtesy of Arthur W. Toga, Dept. of
  Neurology, UCLA School of Medicine)

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3-D Reconstruction

• 3-D Volume Rendering of a Human Brain

RGB image series (real-color, human brain), 1472
x 1152 x 753, 3.57 GB (data courtesy of Arthur W.
Toga, Dept. of Neurology, UCLA School of
Medicine, image courtesy of Eric B. Lum, Ikuko
Takanashi, CIPIC, UC Davis)
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3-D Reconstruction

• 3-D Volume Rendering of a Human Brain

RGB image series (real-color, human brain), 1472
x 1152 x 753, 3.57 GB (data courtesy of Arthur W.
Toga, Dept. of Neurology, UCLA School of
Medicine, image courtesy of Eric B. Lum, Ikuko
Takanashi, CIPIC, UC Davis)
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From 2-D Cross-sections to 3-D
?
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From 2-D Cross-sections to 3-D
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From 2-D Cross-sections to 3-D
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3-D Reconstruction
CT head (512 cross-sections, 1024
planes)rendered with different transparency
transfer functions
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3-D Reconstruction
Cancer cell (256 cross-sections,512
planes)
Human brain(128 cross-sections,220 planes)
Ice Block(Human brain)(128 cryo-sections,256
planes)
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3-D Reconstruction
MRI scan of a human skull
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3-D Reconstruction
CT scan of a human skull
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3-D Reconstruction
CT scan of a human skull
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How to scale down large-scale data?
M
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0 5 3 2
5 9 7
100k polygons
120 CD-ROMs
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Progressive Reconstruction




Initial stage
Second level of detail






Third level of detail Final
reconstructed image
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Application Areas

• Cancer Research
• Image processing (segmentation, classification)
• Multi-modal imaging (CT/MRI/cryosection/confocal)
• Neuroscience
• Rhesus Macaque Monkey Brain Atlas (NIMH)
• Scalable Visualization Toolkits for Bays to
  Brains (NPACI)
• Cell Physiology
• Connectivity in Leech Giant Glial Cells
• Correspondence Analysis in Time-variant
  Microscopic3D Image Data
• Molecular Diagnostics
• Genomics, Proteomics, Phylogenetic Trees

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Application Areas

• Satellite Imaging
• Geospatial Data
• Tactical Data
• Weather Forecast
• Material Sciences
• Structural Analysis (non-destructive)
• Properties of New Compound Materials
• Others
• Image Enhancement
• Feature Extraction

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Image Representation
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Image Representation
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Image Representation
Intensity Profile (Histogram)
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Image Representation
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Image Representation
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Image Representation
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Image Representation
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Image Representation
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Image Representation
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Image Representation
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Questions?

• Joerg Meyer
• University of California, Irvine
• EECS/BME Department
• 4223 Engineering Hall
• Irvine, CA 92697-2625
• jmeyer_at_uci.edu
• http//imaging.eng.uci.edu/jmeyer