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Abstract:
In the last few years researches in the field of High Dynamic Range (HDR)
Imaging have focused on providing
tools for expanding LDR content for the generation of HDR images due to the
growing popularity of HDR in
applications, such as photography and rendering via Image-Based Lighting, and
the imminent arrival of HDR
displays to the consumer market. LDR content expansion is required due to the
lack of fast and reliable consumer
level HDR capture for still images and videos. Furthermore, LDR content
expansion, will allow the re-use of
legacy LDR stills, videos and LDR applications created, over the last century
and more, to be widely available.
The use of certain LDR expansion methods, those that are based on the inversion
of tone mapping operators, has
made it possible to create novel compression algorithms that tackle the problem
of the size of HDR content storage,
which remains one of the major obstacles to be overcome for the adoption of
HDR. These methods are used in
conjunction with traditional LDR compression methods and can evolve
accordingly. The goal of this report is to
provide a comprehensive overview on HDR Imaging, and an in depth review on
these emerging topics. Moreover,
we are proposing how to classify and to validate them. We will discuss
limitations of these methods, and identify
remaining challenges for the future.
