Wikipedia Collage Project IMAGE DOWNSCALING
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Wikipedia Collage Project IMAGE DOWNSCALING Gavi Levy Haskell
Transcript of Wikipedia Collage Project IMAGE DOWNSCALING
Wikipedia Collage Project
IMAGE DOWNSCALING Gavi Levy Haskell
Outline ! A Little History of Collage ! The Project Overall ! The Project at Hand ◦ Previous Work ◦ The Choices Made ◦ What’s Being Tested
! A Few Results ! Further Possibilities
Image Downscaling
A HISTORY OF COLLAGE
A Little History of Collage ! High art—early 20th c. ◦ Georges Braque ◦ Pablo Picasso
Collage History
Overall Project
Image Downsizing Previous Work My Choices The Test
Initial Results
Thinking Ahead
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—19
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Picasso—Bottle of Vieux Marc, Glass, Guitar and Newspaper—1913
http://facweb.cs.depaul.edu/sgrais/collage.htm
A Little History of Collage ! Scrapbooking—19th c. ◦ Women and children
Collage History
Overall Project
Image Downsizing Previous Work My Choices The Test
Initial Results
Thinking Ahead Kate Edith Gough—late 1870s http://www.metmuseum.org/exhibitions/listings/2010/victorian-photocollage
A Little History of Collage ! Paper cutting—18th c., earlier ◦ Mary Delany
Collage History
Overall Project
Image Downsizing Previous Work My Choices The Test
Initial Results
Thinking Ahead Mary Delany—Passiflora laurifolia: bay leaved—1777 Mary Delany—Physalis, Winter Cherry—1772–1788 http://www.britishmuseum.org/explore/highlights/highlights_search_results.aspx?RelatedId=11742
A Little History of Collage ! Collage as data visualization ◦ 365 Days of Light in Norway
Collage History
Overall Project
Image Downsizing Previous Work My Choices The Test
Initial Results
Thinking Ahead Steven Kay, based on video by Eirik Solheim http://www.flickr.com/photos/stevefaeembra/5349017221/
Image Downscaling
THE WIKIPEDIA PROJECT
The Project Overall
Collage History
Overall Project
Image Downsizing Previous Work My Choices The Test
Initial Results
Thinking Ahead
! Displaying lots of images
! Probably don’t just want to use the original sizes
! Opening and modifying images (even automatically) is slow
Image Downscaling
THE PROJECT AT HAND
Downscaling Research
Collage History
Overall Project
Image Downsizing Previous Work My Choices The Test
Initial Results
Thinking Ahead
! Lots done on beautification ◦ Samadani, et al., of HP labs " “Honest” thumbnails
◦ Kopf, et al. " Content-based adaptive resizing
◦ Suzuki, et al. " Thin line preservation
◦ Avidan and Shamir " Content-aware resizing with seams
Downscaling Research
Collage History
Overall Project
Image Downsizing Previous Work My Choices The Test
Initial Results
Thinking Ahead
! Less done on speed ◦ Parkinnen, et al. " Store some data to hasten
calculations
The Choices Made
Collage History
Overall Project
Image Downsizing Previous Work My Choices The Test
Initial Results
Thinking Ahead
! Two algorithms ◦ Nearest neighbor interpolation ◦ Bilinear interpolation
! ImageMagick
! Parallel for multiple images ◦ C application using MPI ◦ Multithreaded Java
Testing
Collage History
Overall Project
Image Downsizing Previous Work My Choices The Test
Initial Results
Thinking Ahead
! Speed of each of the six implementations ◦ Images resized by a variety of
randomly-generated scalars
! Visual comparison of results of different algorithms ◦ At several different sizes
Image Downscaling
THE RESULTS (FOR NOW)
Initial Results
Collage History
Overall Project
Image Downsizing Previous Work My Choices The Test
Initial Results
Thinking Ahead
! For one image, in Java, scaled by .6834:
(average of three runs)
◦ Nearest Neighbor: 2.333 s. ◦ ImageMagick: 2.429 s. ◦ Bilinear: 3.110 s.
Initial Results
Collage History
Overall Project
Image Downsizing Previous Work My Choices The Test
Initial Results
Thinking Ahead
! May well be different in C
Initial Results
Collage History
Overall Project
Image Downsizing Previous Work My Choices The Test
Initial Results
Thinking Ahead Bilinear Nearest Neighbor
Image Downscaling
FURTHER POSSIBILITIES
Further Possibilities
Collage History
Overall Project
Image Downsizing Previous Work My Choices The Test
Initial Results
Thinking Ahead
! Multi-image adaptive scaling ◦ Smaller sizes need less quality
! Implementing a blur
