Signal Processing - September 2017 - 170

L t is the luminance of the tone mapped
image. The parameter p then needs to
be selected for the best-most pleas-
ing-result. Unfortunately, the simple
solution presented above does not only
adjust the saturation, it also implies a
luminance shift. Controlling p to get
the desired effect may be hard. This
problem can be overcome by a more
careful choice of the input and output
scaling operation [10]:
I t = cc I o - 1 m p + 1 m L t .
Lo

(4)

While this allows better control of the
luminance shift, it may cause undesirable
hue artifacts [8] if applied separately to
each component of an RGB image. The
value of p in the above equations can
be automated based on the slope of the
tone curve at each luminance level [10].
To reduce hue and lightness shifts, one
may work with perceptual uniform color
space to separate the color appearance
parameters such as saturation from hue
and lightness. This will allow modifying
the saturation of the tone mapped image
to match the saturation of the input HDR
image while hue and lightness of the tone
mapped image I t will remain untouched
[8]. Other approaches exploit the use of
color appearance models and extend
the concept of gamut mapping of the
HDR content [9]. The former approach
guarantees the matching of the color
appearance attributes between the input
HDR and the tone mapped images. The
latter ensures that all the tone mapped
pixels are within the color gamut of the
display, minimizing the hue and lumi-
nance distortion.

Inverse tone mapping
The latest standardization trends and tech-
nological improvements push the display
features toward ultra HD, higher dynamic
range, i.e., up to 1,000 and 6,000 nits, and
wide color gamut (ITU-R Rec. 2020).
Since traditional liquid crystal display
(LCD) panels with constant backlight il-
lumination are not able to reproduce the
necessary dynamic range, HDR displays
make use of a modulated backlight. In
such a display, a front-layer LCD panel
includes the color filters and provides
the necessary level of detail for accurate
170

image reproduction, and a lower resolu-
tion matrix of independently controlled
LEDs modulate its illumination at a
coarser level, providing a much larger dy-
namic range. Optical layers and reflectors
around each LED maximize the bright-
ness in its corresponding area of the front
LCD panel and minimize the light leak-
age into adjacent cells. Due to the coarser
resolution of the back panel, image quality
degradation may appear, which can be re-
duced through the use of post processing
filtering of the displayed image.
The widespread availability of SDR
content and the recent availability of
displays with larger dynamic range also
made it attractive to process such con-
tent for presentations on HDR displays.
This process can be seen as the opposite
problem of tone mapping and is thus
called inverse tone mapping. The ability
to reconstruct the mapping between the
pixel values encoded in the SDR image
and the scene luminance values, also
known as the inverse camera response
function, is the desirable goal. While it
is an easy task to reconstruct the camera
response function from a series of differ-
ent exposures of the same SDR content,
it is an ill-posed problem to reconstruct
such an inverse when only a single expo-
sure of an unknown camera is available.
The camera response function mod-
els the complete pipeline from light ac-
quisition to SDR pixel values, including
the (nonlinear) sensor response, expo-
sure, camera postprocessing (e.g., flare-
removal), and tone mapping of raw pixel
values to SDR sample values. Recover-
ing the dynamic range for an SDR con-
tent will consist of two basic steps. First,
estimate an inverse camera response
function to linearize the SDR content
signal and then adjust the dynamic range
of the SDR pixel to fit it to the dynamic
range of the HDR display. However, SDR
images are presenting two major issues
when expanding them to larger dynamic
range. First, the limited pixels precision,
i.e., quantization to 256 values/channel,
causes loss of detail and posterization.
These artifacts, while barely visible in
the SDR domain, can be emphasized
during the expansion of the dynamic
range. Second, under and overexposed
regions in the SDR image contain very
IEEE SIGNAL PROCESSING MAGAZINE

|

September 2017

|

limited information. This may lead, dur-
ing the dynamic range expansion, to re-
gions that have the same appearance as
in the original SDR image.
To solve the first problem, advanced
filtering is needed before boosting the
dynamic range of the SDR image. Bilat-
eral filtering is an example: by tuning its
parameters properly, high and low fre-
quencies can be processed separately,
avoiding some of the typical artifacts
of range-expansion. While lost image
content cannot be recovered in any way,
to solve the second problem, inpainting
may at least generate plausible image
details in under- or overexposed image
regions, provided the regions are suf-
ficiently small and enough details are
available around them.

HDR quality indices
The evaluation of the quality of an
image or video is one of the fundamen-
tal steps in understanding whether the
algorithm is capable of achieving a level
of quality acceptable for a specific appli-
cation. Depending on whether the origi-
nal source is available when assessing a
somewhat distorted image or video, one
distinguishes between full-reference
and no-reference quality indices. If only
partial information on the original is
available, they are called reduced-reference indices. In a second dimension,
we can distinguish between objective
and subjective quality indices. In the
former method, a computer algorithm
quantifies the differences between a ref-
erence and a test image or video. Such
an algorithm may include a model of the
human visual system and then evaluates
the visibility of image defects in terms
of its observer's model. The latter meth-
od evaluates quality through studies by
human observers. Based on a particular
test methodology, observers are asked to
qualify characteristics of single or pairs
of visual stimuli in form of image or
video and to provide a score on a scale
or a relative rating between multiple
presentations. The second method is
capable of catching all aspects of human
vision and is thus more appropriate to
evaluate (or even define) the quality of
an image or a video. It is, however, also
very resource and time consuming and



Table of Contents for the Digital Edition of Signal Processing - September 2017

Signal Processing - September 2017 - Cover1
Signal Processing - September 2017 - Cover2
Signal Processing - September 2017 - 1
Signal Processing - September 2017 - 2
Signal Processing - September 2017 - 3
Signal Processing - September 2017 - 4
Signal Processing - September 2017 - 5
Signal Processing - September 2017 - 6
Signal Processing - September 2017 - 7
Signal Processing - September 2017 - 8
Signal Processing - September 2017 - 9
Signal Processing - September 2017 - 10
Signal Processing - September 2017 - 11
Signal Processing - September 2017 - 12
Signal Processing - September 2017 - 13
Signal Processing - September 2017 - 14
Signal Processing - September 2017 - 15
Signal Processing - September 2017 - 16
Signal Processing - September 2017 - 17
Signal Processing - September 2017 - 18
Signal Processing - September 2017 - 19
Signal Processing - September 2017 - 20
Signal Processing - September 2017 - 21
Signal Processing - September 2017 - 22
Signal Processing - September 2017 - 23
Signal Processing - September 2017 - 24
Signal Processing - September 2017 - 25
Signal Processing - September 2017 - 26
Signal Processing - September 2017 - 27
Signal Processing - September 2017 - 28
Signal Processing - September 2017 - 29
Signal Processing - September 2017 - 30
Signal Processing - September 2017 - 31
Signal Processing - September 2017 - 32
Signal Processing - September 2017 - 33
Signal Processing - September 2017 - 34
Signal Processing - September 2017 - 35
Signal Processing - September 2017 - 36
Signal Processing - September 2017 - 37
Signal Processing - September 2017 - 38
Signal Processing - September 2017 - 39
Signal Processing - September 2017 - 40
Signal Processing - September 2017 - 41
Signal Processing - September 2017 - 42
Signal Processing - September 2017 - 43
Signal Processing - September 2017 - 44
Signal Processing - September 2017 - 45
Signal Processing - September 2017 - 46
Signal Processing - September 2017 - 47
Signal Processing - September 2017 - 48
Signal Processing - September 2017 - 49
Signal Processing - September 2017 - 50
Signal Processing - September 2017 - 51
Signal Processing - September 2017 - 52
Signal Processing - September 2017 - 53
Signal Processing - September 2017 - 54
Signal Processing - September 2017 - 55
Signal Processing - September 2017 - 56
Signal Processing - September 2017 - 57
Signal Processing - September 2017 - 58
Signal Processing - September 2017 - 59
Signal Processing - September 2017 - 60
Signal Processing - September 2017 - 61
Signal Processing - September 2017 - 62
Signal Processing - September 2017 - 63
Signal Processing - September 2017 - 64
Signal Processing - September 2017 - 65
Signal Processing - September 2017 - 66
Signal Processing - September 2017 - 67
Signal Processing - September 2017 - 68
Signal Processing - September 2017 - 69
Signal Processing - September 2017 - 70
Signal Processing - September 2017 - 71
Signal Processing - September 2017 - 72
Signal Processing - September 2017 - 73
Signal Processing - September 2017 - 74
Signal Processing - September 2017 - 75
Signal Processing - September 2017 - 76
Signal Processing - September 2017 - 77
Signal Processing - September 2017 - 78
Signal Processing - September 2017 - 79
Signal Processing - September 2017 - 80
Signal Processing - September 2017 - 81
Signal Processing - September 2017 - 82
Signal Processing - September 2017 - 83
Signal Processing - September 2017 - 84
Signal Processing - September 2017 - 85
Signal Processing - September 2017 - 86
Signal Processing - September 2017 - 87
Signal Processing - September 2017 - 88
Signal Processing - September 2017 - 89
Signal Processing - September 2017 - 90
Signal Processing - September 2017 - 91
Signal Processing - September 2017 - 92
Signal Processing - September 2017 - 93
Signal Processing - September 2017 - 94
Signal Processing - September 2017 - 95
Signal Processing - September 2017 - 96
Signal Processing - September 2017 - 97
Signal Processing - September 2017 - 98
Signal Processing - September 2017 - 99
Signal Processing - September 2017 - 100
Signal Processing - September 2017 - 101
Signal Processing - September 2017 - 102
Signal Processing - September 2017 - 103
Signal Processing - September 2017 - 104
Signal Processing - September 2017 - 105
Signal Processing - September 2017 - 106
Signal Processing - September 2017 - 107
Signal Processing - September 2017 - 108
Signal Processing - September 2017 - 109
Signal Processing - September 2017 - 110
Signal Processing - September 2017 - 111
Signal Processing - September 2017 - 112
Signal Processing - September 2017 - 113
Signal Processing - September 2017 - 114
Signal Processing - September 2017 - 115
Signal Processing - September 2017 - 116
Signal Processing - September 2017 - 117
Signal Processing - September 2017 - 118
Signal Processing - September 2017 - 119
Signal Processing - September 2017 - 120
Signal Processing - September 2017 - 121
Signal Processing - September 2017 - 122
Signal Processing - September 2017 - 123
Signal Processing - September 2017 - 124
Signal Processing - September 2017 - 125
Signal Processing - September 2017 - 126
Signal Processing - September 2017 - 127
Signal Processing - September 2017 - 128
Signal Processing - September 2017 - 129
Signal Processing - September 2017 - 130
Signal Processing - September 2017 - 131
Signal Processing - September 2017 - 132
Signal Processing - September 2017 - 133
Signal Processing - September 2017 - 134
Signal Processing - September 2017 - 135
Signal Processing - September 2017 - 136
Signal Processing - September 2017 - 137
Signal Processing - September 2017 - 138
Signal Processing - September 2017 - 139
Signal Processing - September 2017 - 140
Signal Processing - September 2017 - 141
Signal Processing - September 2017 - 142
Signal Processing - September 2017 - 143
Signal Processing - September 2017 - 144
Signal Processing - September 2017 - 145
Signal Processing - September 2017 - 146
Signal Processing - September 2017 - 147
Signal Processing - September 2017 - 148
Signal Processing - September 2017 - 149
Signal Processing - September 2017 - 150
Signal Processing - September 2017 - 151
Signal Processing - September 2017 - 152
Signal Processing - September 2017 - 153
Signal Processing - September 2017 - 154
Signal Processing - September 2017 - 155
Signal Processing - September 2017 - 156
Signal Processing - September 2017 - 157
Signal Processing - September 2017 - 158
Signal Processing - September 2017 - 159
Signal Processing - September 2017 - 160
Signal Processing - September 2017 - 161
Signal Processing - September 2017 - 162
Signal Processing - September 2017 - 163
Signal Processing - September 2017 - 164
Signal Processing - September 2017 - 165
Signal Processing - September 2017 - 166
Signal Processing - September 2017 - 167
Signal Processing - September 2017 - 168
Signal Processing - September 2017 - 169
Signal Processing - September 2017 - 170
Signal Processing - September 2017 - 171
Signal Processing - September 2017 - 172
Signal Processing - September 2017 - 173
Signal Processing - September 2017 - 174
Signal Processing - September 2017 - 175
Signal Processing - September 2017 - 176
Signal Processing - September 2017 - 177
Signal Processing - September 2017 - 178
Signal Processing - September 2017 - 179
Signal Processing - September 2017 - 180
Signal Processing - September 2017 - 181
Signal Processing - September 2017 - 182
Signal Processing - September 2017 - 183
Signal Processing - September 2017 - 184
Signal Processing - September 2017 - 185
Signal Processing - September 2017 - 186
Signal Processing - September 2017 - 187
Signal Processing - September 2017 - 188
Signal Processing - September 2017 - 189
Signal Processing - September 2017 - 190
Signal Processing - September 2017 - 191
Signal Processing - September 2017 - 192
Signal Processing - September 2017 - 193
Signal Processing - September 2017 - 194
Signal Processing - September 2017 - 195
Signal Processing - September 2017 - 196
Signal Processing - September 2017 - Cover3
Signal Processing - September 2017 - Cover4
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