Difference between revisions of "Dealing with image data"

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== Class 9: Dealing with image data for product appearance monitoring (04 November) ==
{{ClassSidebarYouTube
| date = 04 November 2011
| vimeoID1 = 4wUxhUfrUGk
| vimeoID2 = PLSnbQ8IiOg
| vimeoID3 = HptF1ZE5W_Q
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| vimeoID5 =
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| course_notes_PDF =
| course_notes_alt = Course notes
| overheads_PDF =
| overheads_PDF_alt = Projector notes
| assignment_instructions =  
| assignment_solutions =
| video_download_link_MP4 = http://learnche.mcmaster.ca/media/LVM-2011-Class-09A.mp4
| video_download_link2_MP4 = http://learnche.mcmaster.ca/media/LVM-2011-Class-09B.mp4
| video_download_link3_MP4 = http://learnche.mcmaster.ca/media/LVM-2011-Class-09C.mp4
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| video_download_link_MP4_size = 183 Mb
| video_download_link2_MP4_size = 255 Mb
| video_download_link3_MP4_size = 287 Mb
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}}__NOTOC__


* If you have MATLAB on your laptops, please [[Media:Maccmia-1.9.zip | download and install MACCMIA]] for the next class (not too serious if you can't get it installed).
== Class 9: Dealing with image data for product appearance monitoring (04 November 2011) ==


[[Image:Nuvola_mimetypes_pdf.png|20px|link=Media:Lvm-class-9.pdf]] [[Media:Lvm-class-9.pdf|Download the class slides]] (PDF)


== Class 10: Batch systems: troubleshooting and monitoring ==


''Notes coming soon''
== MIA exercise ==
 
===Background ===
If you have MATLAB, please [[Media:Maccmia-1.9.zip | download and install MACCMIA]] for to complete the questions below.
 
* Data file: [[Media:Landsat7DC.mat | a 7-channel Landsat image]] of Washington D.C.  and the corresponding [http://g.co/maps/p8j2a Google map].
** The image is a 1024 x 1026 x 7 cube, using 7.3 Mb of storage
** Channel 1 = blue/green [450 to 520 nm]
** Channel 2 = mainly green [520 to 600 nm]
** Channel 3 = red [630 to 690 nm]
** Channel 4 = Near infrared [760 to 900 nm]
** Channel 5 = Moisture and vegetation sensitive mid infrared [1550 to 1750 nm]
** Channel 6 = Thermal infrared [10400 to 12500 nm]
** Channel 7 = Mineral-sensitive mid infrared [2085 to 2350 nm]
 
* You can [https://en.wikipedia.org/wiki/Landsat_program read more about the Landsat program]
 
=== Questions ===
# Identify some water pixels from the Potomac river in the score plot. Where are they located?
# Mask these water pixels to highlight the entire river. Notice how you have to adjust the mask to get both the shallow and the deep water pixels.
# Notice how the pixels from half of the [http://g.co/maps/njb7n Georgetown Reservoir] show up with the Potomac River's pixels, and the other half show up entirely different (sediment has settled out).
# Continue investigating features from the [http://g.co/maps/p8j2a Google map] and try to locate them in the satellite map and score space. For example:
#* The Reflecting Pool
#* Forests in The National Arboretum
#* The network of roads and highways

Latest revision as of 14:07, 17 September 2018

Class date(s): 04 November 2011
Video material (part 1)
Download video: Link (plays in Google Chrome) [183 Mb]
Video material(part 2)
Download video: Link (plays in Google Chrome) [255 Mb]
Video material (part 3)
Download video: Link (plays in Google Chrome) [287 Mb]

Class 9: Dealing with image data for product appearance monitoring (04 November 2011)

Nuvola mimetypes pdf.png Download the class slides (PDF)


MIA exercise

Background

If you have MATLAB, please download and install MACCMIA for to complete the questions below.

  • Data file: a 7-channel Landsat image of Washington D.C. and the corresponding Google map.
    • The image is a 1024 x 1026 x 7 cube, using 7.3 Mb of storage
    • Channel 1 = blue/green [450 to 520 nm]
    • Channel 2 = mainly green [520 to 600 nm]
    • Channel 3 = red [630 to 690 nm]
    • Channel 4 = Near infrared [760 to 900 nm]
    • Channel 5 = Moisture and vegetation sensitive mid infrared [1550 to 1750 nm]
    • Channel 6 = Thermal infrared [10400 to 12500 nm]
    • Channel 7 = Mineral-sensitive mid infrared [2085 to 2350 nm]

Questions

  1. Identify some water pixels from the Potomac river in the score plot. Where are they located?
  2. Mask these water pixels to highlight the entire river. Notice how you have to adjust the mask to get both the shallow and the deep water pixels.
  3. Notice how the pixels from half of the Georgetown Reservoir show up with the Potomac River's pixels, and the other half show up entirely different (sediment has settled out).
  4. Continue investigating features from the Google map and try to locate them in the satellite map and score space. For example:
    • The Reflecting Pool
    • Forests in The National Arboretum
    • The network of roads and highways
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