ASED
h as relighting
‘ground-based
1 by important
ie images, and
n environment
the simulated
sor radiance is
or low resolu-
Ogy, it can be
terrestrial im-
d radiance can
uds. In a non
tric models to
2). The model
small number
These models
| cannot repre-
8) proposes to
ed ball. It can
a scene. How-
id only for the
or other points
materials and
imation of sky
vo approaches
they are then
: artifacts (sec-
ipproaches are
obile-mapping
lation problem
interaction be-
attenuation) is
ng (Pharr and
knowledge of
y not homoge-
nostly because
roposed paper
Figure 1: Example of rosy artifacts in the case of a flat-field cor-
rection without prior rejection of overexposed pixels.
is that if the sky is now considered as a light source rather than a
part of the scene, its complete modelization and simulation is no
longer required and it suffices to sample the downward radiance
using sky-facing pixel values. The light source from the terres-
trial point of view can thus be considered as the sum of a solar
component and a sky component.
The sun component can then be modeled independently from the
sky, using a point light source located at an infinite distance mov-
ing along the well-known solar trajectory. The sky illumination
is however more complex : its is a time-varying 4D + T light-
field. Our main assumption is that every point of the scene re-
ceives the same radiance from the sky seen in a given direction
(0,0),0 € [0, 2], 6 € [0, 27]. This neglects time variations be-
tween acquired images and their parallax. These limitations are
reasonable when the weather is good (e.g. there is no low-altitude
fog or cloud), since the scene (typically a street) is relatively small
and we can neglect the scattering in the low layers of the atmo-
sphere. The sky component can thus be modeled as an environ-
ment map, i.e. a 2D map giving for each direction of the upper
hemisphere the value of the downward radiance coming from the
sky.
2.2 Input data
The available data is a set of georeferenced terrestrial images ac-
quired by a mobile-mapping vehicle in a urban area, with cal-
ibrated cameras, distributed so as to cover virtually the whole
hemisphere. The images are georeferenced by processing the
GPS and INS data. They are acquired with 12 bits per pixel, then
are corrected of geometrical distortion and of vignetting (using a
flat-field). The flat-field correction has to be performed carefully:
the bit depth of the resulting image is set to 16 bits per pixel in
order to avoid artificial overexposure in the corners (because of
the division by a value « 1). Furthermore, rosy artifacts can ap-
pear in the areas where the blue channel is overexposed while the
red one is not (an example can be seen on figure 1); that is due
to a higher coefficient for the red channel for the white balance.
For these reasons, the overexposed pixels are detected before the
flat-field correction.
These images are affected by different undesirable effects due to
inherent limitations of CCD sensors: overexposure in the solar
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B3, 2012
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia
Figure 2: Extracts from images from the urban dataset with visi-
ble radiometric artifacts: bloom and overexposure.
Figure 3: Image affected by a strong vertical smear, because of a
worn-out sensor.
halo, flare effect, bloom effect, inaccuracy of the flat-field cor-
rection, and vertical smear (figure 2). The vertical smear, usually
negligible in the absence of very high objects, can become very
important when the sensor is worn-down (figure 3). These ef-
fects, hard to model and correct, affect the accuracy of the physi-
cal measure of the light's energy, and imply discontinuities while
stitching several images into a panoramic. We use images taken
in a very short period of time (about 1 minute) to generate one
environment map, so the sky can be considered as static, even if
all images are not taken from the same location.
Examples of images used for the results section (4) are shown on
figure 4.
2.3 The problem: radiance estimation from images
Due to overexposure, the solar irradiance is not readily accessi-
ble in general purpose images. Its irradiance may be computed
by knowing the optical thickness of the whole atmosphere, or by
indirect estimation using pairs of points located on both sides of a
shadow edge (Thomas et al., 2008). In this article, we only focus
on sky radiance estimation. The problem is the computation of
