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Part _ 1B
Emerging New Subjects and their applications
Monday, August 11, 2014PIAIP_NESPAK 2
Introduction to New Fields
Remote
Sensing (RS)
Geographic
Information
System (GIS)
Geomatics
Monday, August 11, 2014PIAIP_NESPAK 3
PART – 01B
Image Processing
Monday, August 11, 2014PIAIP_NESPAK 4
Introduction to Basics
Monday, August 11, 2014PIAIP_NESPAK 5
Image Processing
 Digital image processing is a technology of applying a number of computer
algorithms to process a digital image.
 Back in 1980’s, after computer gain enough speed and memory.
 It includes:
 Image acquisition
 Image processing
 The result can either:
 An image.
 Or a set of representative characteristic of original image.
 Like: Classified images
Monday, August 11, 2014PIAIP_NESPAK 6
Monday, August 11, 2014PIAIP_NESPAK 7
a) Original RGB Image
b) R-component
c) G-component
d) B-component
Why Image Processing?
Its Human erg to get from Better to Best 
 To have a high Quality images.
 To see beyond the human visionary.
 To have a precise interpretation.
 To extract the hidden information.
 To utilize the maximum of the available.
 To get a better idea before getting into real-time work-out, like surveying.
Monday, August 11, 2014PIAIP_NESPAK 8
Where to use Image Processing?
 Remote sensing (e.g. satellite imagery)
 Geographic Information System (e.g. image processing)
 Medical imaging (e.g. X-ray, CT Scan, MRI)
 Forensics (e.g. finger-prints)
 Military (e.g. detection, tracking)
Monday, August 11, 2014PIAIP_NESPAK 9
Extracted Information From Processed
Images
Type of information
extracted
Spatial Information
Geometric data Shape, size
Quantitative data Numbers, count
Spectral
Information
Radiometric data Tone, texture
Qualitative data
Sharpness,
enhancement
Monday, August 11, 2014PIAIP_NESPAK 10
Anomalies: Types and Examples
TypeofAnomalies
Systematic
Errors
Internal error
Geometric error
Non-systematic
Error
Platform error
(satellite)
Non-predictable
Monday, August 11, 2014PIAIP_NESPAK 11
ExamplesofAnomalies
Systematic
Distortion
Earth rotation
Earth curvature
Mirror scan
velocity
Non-systematic
Distortion
Altitude
Attitude
Monday, August 11, 2014PIAIP_NESPAK 12
REFERENCES
Monday, August 11, 2014PIAIP_NESPAK 13
1. Using Geographic Information System (GIS) to Manage Civil Engineering Projects By Asmaa Abdul
Jabbar
2. Longley et al (2005) Geographic Information Systems and Science. 2nd Edition. John Wiley and Sons
Ltd. (Chapter 14, pages 317-319)
3. www.esri.com/engineering
4. http://webhelp.esri.com/arcpad/8.0/userguide/index.htm#capture_devices/concept_intro.htm
Special Acknowledgement
Industrial partners: ESRI, Danish Hydraulic Institute, Camp, Dresser and McKee, Dodson and Associates
Government partners:
Federal: EPA, USGS, Corps of Engineers (Hydrologic Engineering Center)
State: Texas Natural Resource Conservation Commission, Texas Water Development Board
Local: Lower Colorado River Authority, City of Austin, Dept. of Watershed Protection
Academic Partners: University of Texas, Brigham Young University, Utah State University
Monday, August 11, 2014PIAIP_NESPAK 14

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Introduction to Digital Image Processing _ 2014

  • 2. Emerging New Subjects and their applications Monday, August 11, 2014PIAIP_NESPAK 2
  • 3. Introduction to New Fields Remote Sensing (RS) Geographic Information System (GIS) Geomatics Monday, August 11, 2014PIAIP_NESPAK 3
  • 4. PART – 01B Image Processing Monday, August 11, 2014PIAIP_NESPAK 4
  • 5. Introduction to Basics Monday, August 11, 2014PIAIP_NESPAK 5
  • 6. Image Processing  Digital image processing is a technology of applying a number of computer algorithms to process a digital image.  Back in 1980’s, after computer gain enough speed and memory.  It includes:  Image acquisition  Image processing  The result can either:  An image.  Or a set of representative characteristic of original image.  Like: Classified images Monday, August 11, 2014PIAIP_NESPAK 6
  • 7. Monday, August 11, 2014PIAIP_NESPAK 7 a) Original RGB Image b) R-component c) G-component d) B-component
  • 8. Why Image Processing? Its Human erg to get from Better to Best   To have a high Quality images.  To see beyond the human visionary.  To have a precise interpretation.  To extract the hidden information.  To utilize the maximum of the available.  To get a better idea before getting into real-time work-out, like surveying. Monday, August 11, 2014PIAIP_NESPAK 8
  • 9. Where to use Image Processing?  Remote sensing (e.g. satellite imagery)  Geographic Information System (e.g. image processing)  Medical imaging (e.g. X-ray, CT Scan, MRI)  Forensics (e.g. finger-prints)  Military (e.g. detection, tracking) Monday, August 11, 2014PIAIP_NESPAK 9
  • 10. Extracted Information From Processed Images Type of information extracted Spatial Information Geometric data Shape, size Quantitative data Numbers, count Spectral Information Radiometric data Tone, texture Qualitative data Sharpness, enhancement Monday, August 11, 2014PIAIP_NESPAK 10
  • 11. Anomalies: Types and Examples TypeofAnomalies Systematic Errors Internal error Geometric error Non-systematic Error Platform error (satellite) Non-predictable Monday, August 11, 2014PIAIP_NESPAK 11 ExamplesofAnomalies Systematic Distortion Earth rotation Earth curvature Mirror scan velocity Non-systematic Distortion Altitude Attitude
  • 12. Monday, August 11, 2014PIAIP_NESPAK 12
  • 13. REFERENCES Monday, August 11, 2014PIAIP_NESPAK 13 1. Using Geographic Information System (GIS) to Manage Civil Engineering Projects By Asmaa Abdul Jabbar 2. Longley et al (2005) Geographic Information Systems and Science. 2nd Edition. John Wiley and Sons Ltd. (Chapter 14, pages 317-319) 3. www.esri.com/engineering 4. http://webhelp.esri.com/arcpad/8.0/userguide/index.htm#capture_devices/concept_intro.htm Special Acknowledgement Industrial partners: ESRI, Danish Hydraulic Institute, Camp, Dresser and McKee, Dodson and Associates Government partners: Federal: EPA, USGS, Corps of Engineers (Hydrologic Engineering Center) State: Texas Natural Resource Conservation Commission, Texas Water Development Board Local: Lower Colorado River Authority, City of Austin, Dept. of Watershed Protection Academic Partners: University of Texas, Brigham Young University, Utah State University
  • 14. Monday, August 11, 2014PIAIP_NESPAK 14