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DTSTART:19700308T020000
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DTSTAMP:20181221T160727Z
LOCATION:D168
DTSTART;TZID=America/Chicago:20181111T155800
DTEND;TZID=America/Chicago:20181111T160100
UID:submissions.supercomputing.org_SC18_sess165_ws_eduhpca105@linklings.co
 m
SUMMARY:Optimization of an Image Processing Algorithm: Histogram Equalizat
 ion
DESCRIPTION:Workshop\nDiversity, Education, Workshop Reg Pass\n\nOptimizat
 ion of an Image Processing Algorithm: Histogram Equalization\n\nGutierrez,
  Kaeli, Previlon\n\nMany textbooks rely on classical linear algebra exampl
 es to illustrate best practices in parallel programming (e.g., matrix mult
 iplication and vector add). Despite their common use in class, these examp
 les lack sophistication of a complete application. We have found that stud
 ents seem to be more motivated to work with imaging processing algorithms,
  where the student can view the before and after image, visually inspectin
 g the results of their processing.\n\nThis assignment focuses on improving
  the performance of the histogram equalization algorithm applied to an ima
 ge. Histogram equalization is a popular image processing algorithm used to
  increase the contrast of an image to better highlight its features. It is
  a common algorithm used in many scientific applications such as x-ray ima
 ging, thermal imaging and as a pre-processing task for multiple computer v
 ision/deep learning algorithms.
URL:https://sc18.supercomputing.org/presentation/?id=ws_eduhpca105&sess=se
 ss165
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