In single view HDR imaging, existing low rank based methods
minimize the Truncated Nuclear Norm (TNN) with r = 1 as the matrix rank can
be assumed to be 1. However, this assumption does not hold
for light fields with disparities between views, and produces blur
in the completed regions as shown in Figures (c),(g) below. Using higher
values of r keeps the details but not the low spatial frequencies
(Figures (a),(b),(e),(f)). Our rank minimization successfully recovers
both low and high frequencies (Figures (d),(h)).
The figure below shows: (a)-(d) show the central view in false color for each method of a 13x13 HDR Light field reconstructed from 3 exposures.
(e),(f),(g),(h) are the epipolar images corresponding to the blue segment
in (a),(b),(c),(d) respectively (vertical axis shows vertical viewpoint
change). The epipolar image in (g) shows that the structures
completed using TNN minimization with r=1 are blurred and identical
in all the views (parallax is not preserved).
Recovery of saturated areas from two exposures
One view of a HDR light field captured from two significantly
different exposures (images are gamma encoded for display
purpose). Some over-exposed areas in the high exposure capture
are under-exposed in the low exposure one. Independent processing
of the viewpoints (a) highlights the presence of noise due to underexposition.
Using all the viewpoints in the WLRA (b) naturally exploits
redundancies to reduce the noise.
Video of (left) original light field, (right) HDR reconstructed light field represented in false colors to show the coherency between the views.
Video showing the sub-apertures with a progressive change of exposure.
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