Night Rendering

Abstract

The issues of realistically rendering naturally illuminated scenes at night are examined. This requires accurate models for moonlight, night skylight, and starlight. In addition, several issues in tone reproduction are discussed: eliminatiing high frequency information invisible to scotopic (night vision) observers; representing the flare lines around stars; determining the dominant hue for the displayed image. The lighting and tone reproduction are shown on a variety of models.

Full text

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Night Rendering
Henrik Wann Jensen
Stanford University
Simon Premoˇ ze
University of Utah
Peter Shirley
University of Utah
Michael M. Stark
University of Utah
William B. Thompson
University of Utah
James A. Ferwerda
Cornell University
Abstract
The issues of realistically rendering naturally illuminated scenes at
night are examined. This requires accurate models for moonlight,
night skylight, and starlight. In addition, several issues in tone re-
production are discussed: eliminatiing high frequency information
invisible to scotopic (night vision) observers; representing the flare
lines around stars; determining the dominant hue for the displayed
image. The lighting and tone reproduction are shown on a variety
of models.
CR Categories: I.3.7 [Computer Graphics]: Three-Dimensional
Graphics and Realism— [I.6.3]:
Applications
Keywords:
realistic image synthesis, modeling of natural phe-
nomena, tone reproduction
Simulation and Modeling—
1 Introduction
Most computer graphics images represent scenes with illumination
at daylight levels. Fewer images have been created for twilight
scenes or nighttime scenes. Artists, however, have developed many
techniques for representing night scenes in images viewed under
daylight conditions, such as the painting shown in Figure 1. The
ability to render night scenes accurately would be useful for many
applications including film, flight and driving simulation, games,
and planetarium shows. In addition, there are many phenomena
only visible to the dark adapted eye that are worth rendering for
their intrinsic beauty. In this paper we discuss the basic issues of
creating such nighttime images. We create images of naturally il-
luminated scenes, so issues related to artificial light sources are not
considered. To create renderings of night scenes, two basic issues
arise that differ from daylight rendering:
• What are the spectral and intensity characteristics of illumi-
nation at night?
• How do we tone-map images viewed in day level conditions
so that they “look” like night?
Illumination computations
To create realistic images of night scenes we must model the char-
acteristics of nighttime illumination sources, both in how much
light they contribute to the scene, and what their direct appearance
in the sky is:
• The Moon: Light received directly from the Moon, and
moonlight scattered by the atmosphere, account for most of
the available light at night. The appearance of the Moon itself
must also be modeled accurately because of viewers’ famil-
iarity with its appearance.
• The Sun: The sunlight scattered around the edge of the Earth
makes a visible contribution at night. During “astronomical”
Figure 1: A painting of a night scene. Most light comes from the
Moon. Note the blue shift, and that loss of detail occurs only inside
edges; the edges themselves are not blurred. (Oil, Burtt, 1990)
twilight the sky is still noticeably bright. This is especially
important at latitudes more than 48◦N or S where astronom-
ical twilight lasts all night in midsummer.
• The planets and stars: Although the light received from the
planets and stars is important as an illumination source only
on moonless nights, their appearance is important for night
scenes.
• Zodiacal light: The Earth is embedded in a dust cloud which
scatters sunlight toward the Earth. This light changes the ap-
pearance and the illumination of the night sky.
• Airglow: The atmosphere has an intrinsic emission of visi-
ble light due to photochemical luminescence from atoms and
molecules in the ionosphere. It accounts for one sixth of the
light in the moonless night sky.
Several authors have examined similar issues of appearance and
illumination for the daylight sky [8, 20, 32, 35, 43, 33]. To our
knowledge, this is the first computer graphics paper that exam-
ines physically-based simulation of the nighttime sky. We restrict
ourselves to natural lighting, and we include all significant natural
sources of illumination except for aurora effects (northern lights).

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Tone mapping
To display realistic images of night scenes, we must apply tone
mapping. This is the process of displaying an image to a viewer
adapted to the display environment that suggests the experience
of an observer adapted to the level of illumination depicted in the
scene. For our purposes this usually means displaying an image
that “looks like” night to an observer that is not dark adapted. The
tone mapping of night images requires us to deal with three per-
ceptual dimensions for mesopic (between day and night vision) and
scotopic (night vision) conditions (Figure 2):
• Intensity: How scotopic luminances are mapped to image lu-
minances.
• Spatial detail: How the glare effects and loss-of-detail at sco-
topic levels is applied in the displayed image.
• Hue: How the hue of displayed image is chosen to suggest
darkness in the scene.
The psychophysical approach of making displayed synthetic im-
ages have certain correct objective characteristics was introduced
by Upstill [49]. The mapping of intensity has been dealt with
by brightness matching [48], contrast detection threshold map-
ping [10, 23, 49, 52], and a combination of the two [34]. Our paper
uses existing methods in intensity mapping. The loss of spatial de-
tail has previously been handled by simple filtering to reduce high-
frequency detail at scotopic levels [10, 23, 34]. This has led to an
unsatisfactory blurry appearance which we attempt to address. The
glare experienced in night conditions has been simulated in com-
puter graphics [29, 42]. We use this work, and show how it should
be applied for stars based on observations of stellar point-spread
functions from the astronomy literature. Color shifting toward blue
tosuggest dark scenes is awell-known practiceinfilmand painting,
and has been partially automated by Upstill [49]. We examine the
magnitude and underlying reasons for this practice and attempt to
automate it. Unfortunately, this places us in the awkward position
of combining empirical practices and known constraints from psy-
chophysics. Fortunately, we can do these seemingly at-odds tasks
in orthogonal perceptual dimensions. We also discuss the sensitiv-
ity of image appearance to display conditions such as background
luminance and matte intensity.
The remainder of the paper is divided into two initial sections on
light transport and physics of the nighttime sky, and how to perform
tone reproduction from computed radiances, and is followed by ex-
ample images and discussion. Our basic approach is to strive for
as much physical and psychophysical accuracy as possible. This
is true for the appearance of the Moon, the sky, and stars, for the
amount of light they illuminate objects with, and for the tone map-
ping. Thus we use available height field data for the Moon topogra-
phy and albedo as well as stellar position. This might be considered
excessive for many applications, but it ensures that the amount of
light coming from the Moon is accurate, and allows viewers with
stellar navigation skills to avoid disorientation. More importantly,
using real data captured with extraterrestrial measurement allows
us to avoid the multidimensional parameter-tuning that has proven
extremely time-consuming in production environments. However,
the number of effects occurring in this framework is enormous, and
wedo not model some phenomena that do contribute to appearance,
and these are specified in the appropriate sections. We close with
results for a variety of scenes.
2Night illumination
Significant natural illumination at night comes primarily from the
Moon, the Sun (indirectly), starlight, zodiacal light and airglow. In
Range of
Illumination
Luminance
(log cd/ m2)
Visual
function
-6-4-202468
scotopic mesopicphotopic
no color vision
poor acuity
good color vision
good acuity
starlight moonlight indoor lighting sunlight
Figure 2: The range of luminances in the natural environment and
associated visual parameters. After Hood (1986)
Component
Sunlight
Full moon
Zodiacal light
Integrated starlight
Airglow
Diffuse galactic light
Cosmic light
Irradiance [W/m2]
1.3 · 103
2.1 · 10−3
1.2 · 10−7
3.0 · 10−8
5.1 · 10−8
9.1 · 10−9
9.1 · 10−10
Figure3: Typical values for sources of natural illumination at night.
addition a minor contribution is coming from diffuse galactic light
and cosmic light. This is illustrated in Figure 3. These components
of the light of the night sky can be treated separately as they are
only indirectly related. Each component has two important prop-
erties for our purpose: the direct appearance, and the action as an
illumination source.
The atmosphere also plays an important role in the appearance
of the night sky. It scatters and absorbs light and is responsible for
a significant amount of indirect illumination. An accurate repre-
sentation of the atmosphere and the physics of the atmosphere is
therefore necessary to accurately depict night illumination.
In this section we describe the components of the night sky and
how we integrate these in our simulation.
2.1Moonlight
Toaccurately render images under moonlight, wetakeadirectmod-
eling approach from an accurate model of the Moon position, the
measured data of the lunar topography and albedo [30]. This en-
sures the Moon’s appearance is correct even in the presence of
oscillation-like movements called optical librations. The Moon
keeps the same face turned towards the Earth, but this does not
mean that we only see half of the lunar surface. From the Earth
about 59% of the lunar surface is sometimes visible while 41% of
the surface is permanently invisible. Optical librations in latitude,
and longitude and diurnal librations expose an extra 18% of the
Moon’s surface at different times. These oscillations are caused by
the eccentricity of the lunar orbit (librations in longitude), devia-
tions in inclination of the lunar rotation axis from the orbital plane
(librations in latitude) and displacements in the diurnal parallax.
Position of the Moon
To compute the positions of the Sun and the Moon, we used the
formulas given in Meeus [28]. For the Sun, the principal pertur-
bations from the major planets are included, making the accuracy
about ten seconds of arc in solar longitude. Meeus employs 125
terms in his formula, and it is accurate to about 15 seconds of arc.
The positions of the Sun and the Moon are computed in ecliptic
coordinates, a coordinate system based on the plane of the Earth’s
orbit, and thus requires an extra step in the transformation to be
converted to altitude and azimuth. Also there are other corrections
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which must be applied, most notably diurnal parallax can affect the
apparent position of the Moon by as much as a degree.
Illumination from the Moon
Most of the moonlight visible to us is really sunlight scattered from
the surface of the Moon in all directions. The sun is approximately
500000 brighter than the moon. The Moon also gets illuminated by
sunlight indirectly via the Earth.
The Moon reflects less than 10% of incident sunlight and is
therefore considered a poor reflector. The rest of the sunlight gets
absorbed by the lunar surface, converted into heat and re-emitted
at different wavelengths outside the visible range. In addition to
visible sunlight, the lunar surface is continuously exposed to high
energy UV and X-rays as well as corpuscular radiation from the
Sun. Recombination of atoms ionized by this high energy particles
give rise to luminescent emission at longer wavelengths, which can
penetrate our atmosphere and become visible on the ground [21].
Depending on the solar cycle and geomagnetic planetary index, the
brightness of the Moon varies 10%-20%. In our simulation we do
not take into account luminescent emission.
Using the Lommel-Seeliger law [51] the irradiance Emfrom the
Moon at phase angle α and a distance d (rm ? d) can be expressed
as:
3Cr2
Em(α,d) =
2
m
d2(Es,m+ Ee,m)
?
1 − sin
?α
2
?
tan
?α
2
?
log
?
cot
?α
4
???
(1)
where rm is the radius of the Moon, Es,m and Ee,m is the irradi-
ance from the Sun and the Earth at the surface of the Moon. The
normalizing constant C can be approximated by the average albedo
of the Moon (C = 0.072).
The lunar surface consists of a layer of a porous pulverized ma-
terial composed of particles larger than wavelengths of visible light.
As a consequence and in accordance with the Mie’s theory [50], the
spectrum of the Moon is distinctly redder than the Sun’s spectrum.
The exact spectral composition of the light of the Moon varies with
the phase (being the bluest at the full Moon). Also, previously men-
tioned luminescent emissions also contribute totheredder spectrum
of the moonlight. In addition, light scattered from the lunar surface
is polarized, but we omit polarization in our model.
Appearance of the Moon
The large-scale topography of the Moon is visible from the Earth’s
surface, so we simulate the appearance of the Moon in the classic
method of rendering illuminated geometry and texture. The Moon
is considered a poor reflector of visible light. On average only 7.2%
of the light is reflected although the reflectance varies from 5-6%
for crater floors to almost 18% in some craters [21]. The albedo
is approximately twice as large for red (longer wavelengths) light
than for blue (shorter wavelengths) light.
Given the lunar latitude β, the lunar longitude λ, the lunar phase
angle α and the angle φ between the incoming and outgoing light,
the BRDF, f, of the Moon can be approximated with [12]
f(θi,θr,φ) =
2
3πK(β,λ)B(α,g)S(φ)
1
1 + cosθr/cosθi
(2)
where θr and θi is the angle between the reflected resp. incident
light and the surface normal, K(β,λ) is the lunar albedo, B(α,g)
is a retrodirective function and S is the scattering law for individual
objects.
The retrodirective function B(α,g) is given by
B(α,g) =
?
?
?
?
?
2 −
1,α ≥ π/2
tan (α)
2g
?
1 − e
−g
tan (α)
??
3 − e
−g
tan (α)
?
,α < π/2
(3)
Figure 4: The Moon rendered at different times of the month and
day and under different weather conditions.
where g is a surface density parameter which determines the sharp-
ness of the peak at the full Moon. If ρ is the fraction of volume
occupied by solid matter [12] then
g = kρ2/3
(4)
where k (k ≈ 2 ) is a dimensionless number. Most often the lunar
surface appears plausible with g = 0.6, although values between
0.4 (for rays) and 0.8 (for craters) can be used. The scattering law
S for individual objects is given by [12]:
ρo(φ) =sin(|φ|) + (π − |φ|)cos|φ|
π
+ t(1 − cos(|φ|))2
(5)
where t introduces small amount of forward scattering that arises
from large particles that cause diffraction [37].
Rougier’s measurements [15] of the light from the Moon well.
This function has been found to give a good fit to measured data,
and the complete Hapke-Lommel-Seeliger model provides good
approximation to the real appearance of the Moon even though
there are several discrepancies between the model and measured
photometric data. Two places it falls short are opposition brighten-
ing and earthshine.
When the Moon is at opposition (ie. opposite the Sun), it is
substantially brighter (10%−20%) than one would expect due to
increased area being illuminated. The mechanisms responsible for
the lunar opposition effect is still being debated, but shadow hid-
ing is the dominant mechanism for the opposition effect. Shadow
hiding is caused by the viewer’s line-of-sight and the direction of
the sunlight being coincident at the antisolar point, therefore effec-
tively removing shadows from the view. Since the shadows cannot
be seen the landscape appears much brighter. We do not model op-
position effect explicitly, although it affects the appearance of the
Moon quite significantly. Fullycapturing this effect would require a
more detailed representation of the geometry than what is currently
available.
When the Moon is a thin crescent the faint light on the dark side
of the Moon is earthshine. The earthshine that we measure on the
dark side of the Moon, naturally, depends strongly on the phase
t = 0.1 fits
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of the Earth. When the Earth is new (at full Moon), it hardly il-
luminates the Moon at all and the earthshine is very dim. On the
other hand, when the Earth is full (at new Moon), it casts the great-
est amount of light on the Moon and the earthshine is relatively
bright andeasilyobserved bythenaked eye. Ifwecouldobserve the
Earth from the Moon, the full Earth would appear about 100 times
brighter than the full Moon appears to us, because of the greater
solid angle that the Earth subtends and much higher albedo (Earth’s
albedo is approximately 30%). Earthshine fades in a day or two be-
cause the amount of light available from the Earth decreases as the
Moon moves around the Earth in addition to loss of the opposition
brightening. We model earthshine explicitly by including the Earth
as a second light source for the Moon surface. The intensity of
the Earth is computed based on the Earth phase (opposite of Moon
phase), the position of the Sun and the albedo of the Earth [51].
2.2Starlight
Stars are obviously important visual features in the sky. While one
could create plausible stars procedurally, there are many informed
viewers who would know that such a procedural image was wrong.
Instead we use actual star positions, brightnesses, and colors. Less
obvious is that starlight is also scattered by the atmosphere, so that
the sky between the stars is not black, even on moonless nights. We
simulate the this effect in addition to the appearance of stars.
Position of stars
For the stars, we used the Yale Bright Star Catalog [14] of most
(≈ 9000) stars up to magnitude +6.5 as our database. This database
contains all stars visible to the naked eye. The stellar positions
are given in spherical equatorial coordinates of right ascension and
declination, referred to the standard epoch J2000.0 [11].
These coordinates are based on the projection of the Earth’s
equator of January 1, 2000 1GMT, projected onto the celestial
sphere. To render the stars, we need the altitude above the hori-
zon and the azimuth (the angle measured west from due south) of
the observer’s horizon at a particular time. The conversion is a two-
step process. The first is to correct for precession and nutation, the
latter being a collection of short-period effects due to other celes-
tial objects [11]. The second step is to convert from the corrected
equatorial coordinates to the horizon coordinates of altitude and az-
imuth. The combined transformation is expressed as a single rota-
tionmatrixwhich canbe directlycomputed as afunction of the time
and position on the Earth. We store the stellar database in rectangu-
lar coordinates, then transform each star by the matrix and convert
back to spherical coordinates to obtain altitude and azimuth. Stellar
proper motions, the slow apparent drifting of the stars due to their
individual motion through space, are not included in our model.
Color and brightness of stars
Apparent star brightnesses are described as stellar magnitudes. The
visual magnitude mv of a star is defined as [22]:
mv = −(19 + 2.5log10(Es))
(6)
where Esis the irradiance at the earth. Given visual magnitude the
irradiance is:
Es = 10−mv−19 W
m2
(7)
For the Sun mv ≈ −26.7, for the full Moon mv ≈ −12.2, for
Sirius (the brightest star) mv ≈ −1.6. The naked eye can see stars
with a stellar magnitude up to approximately 6.
The color of the star is not directly available as a measured spec-
trum. Instead astronomers have established a standard series of
Figure 5: Left: close-up of rendered stars. Right: close-up of time-
lapsed rendering of stars.
measurements in particular wavebands. A widely used UBV sys-
tem introduced by Johnson [16] isolates bands of the spectrum in
the blue intensity B (λ = 440nm, ∆λ = 100nm), yellow-green
intensity V (λ = 550nm, ∆λ = 90nm) and ultra-violet intensity
U (λ = 350nm, ∆λ = 70nm). The difference B − V is called
a color index of a star, and it is a numerical measurement of the
color. A negative value of B−V indicates more bluish color while
a positive value indicates redder stars. UBV is not directly useful
for rendering purposes. However, we can use the color index to
estimate a star’s temperature. [41]:
Teff =
7000K
B − V + 0.56
(8)
Stellar spectra are very similar to spectra of black body radiators,
but there are some differences. One occurs in the Balmer contin-
uum at wavelengths less than 364.6 nm largely due to absorption by
hydrogen.
To compute spectral irradiance from a star given Teff we first
compute a non spectral irradiance value from the stellar magnitude
using equation 7. We then use the computed value to scale a nor-
malized spectrum based on Planck’s radiation law for black body
radiators [40]. This gives us spectral irradiance.
Illumination from stars
Even though many stars are not visible to the naked eye there is a
contribution from all stars when added together. This is can be seen
on clear nights as the Milky Way. Integrated starlight depends on
galactic coordinates — it is brighter in the direction of the galactic
plane. We currently assume that the illumination from the stars is
constant (3 · 10−8 W
Way is simulated using a direct visualization of the brightest stars
as described in the following section.
m2) over the sky. The appearance of a Milky
Appearance of stars
Stars are very small and it is not practical to use ray tracing to ren-
der stars. Instead we use an image based approach in which a sep-
arate star image is generated. In addition a spectral alpha image is
generated. The alpha map records for every pixel the visibility of
objects beyond the atmosphere. It is generated by the renderer as a
secondary image. Every time a ray from the camera exits the atmo-
sphere and enters the universe the integrated optical depth is stored
in the alpha image. The star image is multiplied with the alpha im-
age and added to the rendered image to produce the final image.
The use of the alpha image ensures that the intensity of the stars is
correctly reduced due scattering and absorption in the atmosphere.
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2.3 Zodiacal light
The Earth co-orbits with a ring of dust around the Sun. Sunlight
scatters from this dust and can be seen from the Earth as zodiacal
light [7, 36]. This light first manifests itself in early evening as a
diffuse wedge of light in the southwestern horizon and gradually
broadens with time. During the course of the night the zodiacal
light becomes wider and more upright, although its position rel-
ative to the stars shifts only slightly [5]. On dark nights another
source of faint light can be observed. A consequence of preferen-
tial backscattering near the anti solar point, the gegenshine is yet
another faint source of light that is not fixed in the sky [39]. It is
part of the zodiacal light. In the northern hemisphere, the zodiacal
light is easiest to see in September and October just before sunrise
from a very dark location.
The structure of the interplanetary dust is not well-described and
to simulate zodiacal light we use a table with measured values [38].
Whenever a ray exits the atmosphere we convert the direction of
the ray to ecliptic polar coordinates and perform a bilinear lookup
in the table. This works since zodiacal light changes slowly with
direction and has very little seasonal variation.
2.4Airglow
Airglow is faint light that is continuously emitted by the entire up-
per atmosphere with a main concentration at around 110 km el-
evation. The upper atmosphere of the Earth is continually being
bombarded by high energy particles, mainly from the Sun. These
particles ionize atoms and molecules or dissociate molecules and
in turn cause them to emit light in particular spectral lines (at dis-
crete wavelengths). As the emissions come primarily from Na and
O atoms as well as molecular nitrogen and oxygen the emission
lines are easily recognizable. The majority of the airglow emis-
sions occur at 557.7nm (O − I), 630nm (O − I) and a 589.0nm -
589.6nm doublet (Na−I). Airglow is the principal source of light
in the night sky on moonless nights. Airglow has significant diurnal
variations. 630nm emission is a maximum at the beginning of the
night, but it decreases rapidly and levels off for the remainder of the
night [27]. All three emissions show significant seasonal changes
in both monthly average intensities as well as diurnal variations.
Airglow is integrated into the simulation by adding an active
layer to the atmosphere that contributes with spectral in-scattered
radiance.
2.5Diffuse galactic light and cosmic light
Diffuse galactic light and cosmic light are the last components of
the night sky that we include in our simulation. These are very faint
(see Figure 3) and modeled as a constant term (1·10−8W/m2) that
is added when a ray exits the atmosphere.
2.6The atmosphere modeling
Molecules and aerosols (dust, water drops and other similar sized
particles) are the two main constituents of the atmosphere that af-
fect light transport. As light travels through the atmosphere it can
be scattered by molecules (Rayleigh scattering) or by aerosols (Mie
scattering). The probability that a scattering event occurs is propor-
tional to the local density of molecules and aerosols and the optical
path length of the light. The two types of scattering are very differ-
ent: Rayleigh scattering is strongly dependent on the wavelength of
the light and it scatters almost diffusely, whereas aerosol scattering
is mostly independent of the wavelength but with a strong peak in
the forward direction of the scattered light.
We model the atmosphere using a spherical model similar to
Nishita et al. [33] and we use the same phase functions they did to
approximate the scattering of light. To simulate light transport with
multiple scattering we use distribution ray tracing combined with
ray marching. A ray traversing the atmosphere uses ray marching
to integrate the optical depth and it samples the in-scattered indirect
radiance at random positions in addition to the direct illumination.
Each ray also keeps track of the visibility of the background, and all
rays emanating from the camera save this information in the alpha
image. This framework is fairly efficient since the atmosphere is
optically thin, and it is very flexible and allows us to integrate other
components in the atmosphere such as clouds and airglow.
We model clouds procedurally using an approach similar to [9]
— instead of points we use a turbulence function to control the
placement of the clouds. When a ray traverses a cloud medium it
spawns secondary rays to sample the in-scattered indirect radiance
as well as direct illumination. This is equivalent to the atmosphere
but since clouds have a higher density the number of scattering
events will be higher. The clouds also keep track of the visibility of
the background for the alpha image; this enables partial visibility
of stars through clouds. For clouds we use the Henyey-Greenstein
phase-function [13] with strong forward scattering.
3 Tone mapping
Tone reproduction is usually viewed as the process of mapping
computed image luminances into the displayable range of a par-
ticular output device. Existing tone mapping operators depend on
adaptation in the human vision system to produce displayed images
in which apparent contrast and/or brightness is close to that of the
desired target image. This has the effect of preserving as much as
possible of the visual structure in the image.
Whilepeople arenot abletoaccurately judge absolute luminance
intensitiesunder normal viewingconditions, theycan easilytellthat
absolute luminance at night is far below that present in daylight.
At the same time, the low illumination of night scenes limits the
visual structureapparent even toawelladapted observer. Thesetwo
effects have significant impacts on tone mapping for night scenes.
While the loss of contrast and frequency sensitivity at scotopic
levels has been addressed by Ward et al. [23] and Ferwerda et
al. [10], the resulting images have two obvious subjective short-
coming when compared to good night film shots and paintings. The
first is that they seem too blurry. The second is that they have a
poor hue. Unfortunately, the psychology literature on these sub-
jects deals with visibility thresholds and does not yet have quantita-
tive explanations for suprathreshold appearance at scotopic levels.
However, we do have the highly effective empirical practice from
artistic fields. Our basic strategy is to apply psychophysics where
we have data (luminance mapping and glare), and to apply empir-
ical techniques where we do not have data (hue shift, loss of high
frequency detail). We make an effort to not undermine the psy-
chophysical manipulations when we apply the empirical manipula-
tions.
3.1 Hue mapping
In many films, the impression of night scenes are implied by us-
ing a blue filter over the lens with a wide aperture [25]. Computer
animation practitioners also tend to give a cooler palette for dark
scenes than light scenes (e.g., Plate 13.29 in Apodaca et al. [2]).
Painters also use a blue shift for night scenes [1]. This is some-
what surprising given that moonlight is warmer (redder) than sun-
light; moonlight is simply sunlight reflected from a surface with an
albedo larger at longer wavelengths.
While it is perhaps not obvious whether night scenes really
“look” blue or whether it is just an artistic convention, we believe
that the blue-shift is a real perceptual effect. The fact that rods
contribute to color vision at mesopic levels is well-known as “rod
5