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Digital camera technology has recently seen substantial
improvements in image quality while lower prices have made
it affordable to the average consumer. Camera manufacturers,
however, are not taking full advantage of this new medium
for image capture. By filtering the already digitized image
produced by these cameras through on-board image processing
algorithms we can dramatically increase the power of digital
cameras. For example, according to experts in the
photographic industry, most people simply take bad
pictures. Classic examples of this phenomenon are
photographs taken indoors with a point-and-shoot style
camera using its built-in flash. The subjects of these
photographs often seem to have a spotlight on them, making
them look bright and washed out while the rest of the
photograph is dark and indistinct. This can primarily be
accounted for by a well known property of point light
sources: falloff in brightness is inversely proportional to
the square of the distance between the light and the object
being illuminated. A technique first introduced in the field
of computer vision has been shown to successfully recover
information about the distance between the light source and
objects in the world. We propose using this technique, which
is readily implementable in hardware, to correct for a
variety of poorly illuminated digital images.
Undergraduate Honors Thesis.
Advisor: Hany Farid
Bibliographic citation for this report: [plain text] [BIB] [BibTeX] [Refer]
Or copy and paste:
David B. Martin, "Depth from Flash." Dartmouth Computer Science Technical Report TR2000-373, June 2000.
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