thesis
Stereoscopic high dynamic range imaging
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Abstract
Two modern technologies show promise to dramatically increase immersion in
virtual environments. Stereoscopic imaging captures two images representing
the views of both eyes and allows for better depth perception. High dynamic
range (HDR) imaging accurately represents real world lighting as opposed to
traditional low dynamic range (LDR) imaging. HDR provides a better contrast
and more natural looking scenes. The combination of the two technologies in
order to gain advantages of both has been, until now, mostly unexplored due to
the current limitations in the imaging pipeline. This thesis reviews both fields,
proposes stereoscopic high dynamic range (SHDR) imaging pipeline outlining the
challenges that need to be resolved to enable SHDR and focuses on capture and
compression aspects of that pipeline.
The problems of capturing SHDR images that would potentially require two
HDR cameras and introduce ghosting, are mitigated by capturing an HDR and
LDR pair and using it to generate SHDR images. A detailed user study compared
four different methods of generating SHDR images. Results demonstrated that
one of the methods may produce images perceptually indistinguishable from the
ground truth.
Insights obtained while developing static image operators guided the design
of SHDR video techniques. Three methods for generating SHDR video from an
HDR-LDR video pair are proposed and compared to the ground truth SHDR
videos. Results showed little overall error and identified a method with the least
error.
Once captured, SHDR content needs to be efficiently compressed. Five SHDR
compression methods that are backward compatible are presented. The proposed
methods can encode SHDR content to little more than that of a traditional single
LDR image (18% larger for one method) and the backward compatibility property
encourages early adoption of the format.
The work presented in this thesis has introduced and advanced capture and
compression methods for the adoption of SHDR imaging. In general, this research
paves the way for a novel field of SHDR imaging which should lead to improved
and more realistic representation of captured scenes