Techniques for Processing and Analysis of Digital
Images from Grand Canyon and Great Smoky
Mountains National Parks
John V. Molenar, David S. Cismoski and Frank Schreiner; Air Resource Specialists,
Inc. and William C. Malm; National Park Service
ABSTRACT
Air quality metrics were estimated from pixel data in high resolution digital
images captured at Grand Canyon and Great Smoky Mountains National Parks. The air
quality metrics included target/sky contrast and ground detail. The metrics were
compared to collocated visibility monitoring instrumentation to determine if digital
images can be used to estimate visual air quality in near real time from digital imagery.
INTRODUCTION
The National Park Service (NPS) and several other organizations currently
operate World Wide Web based digital camera networks. One of the goals of these
networks is to provide public outreach and education on air quality issues. The use of a
Web-based interface allows high quality near real time images and associated air quality
information to be presented together. This presentation is designed to demonstrate the
link between the perceived air quality (“what you see”) and measured air quality
parameters.
Each digital camera system in the digital camera networks includes a high
resolution digital camera, image acquisition computer, internet access, and supporting
hardware. System site requirements include a vista with a recognizable or interesting
view, available power, communications infrastructure, and serviceability. Each system
acquires a high resolution (1600 x 1200 pixel, 8 bit per pixel) image at 15 minute
intervals. Following acquisition, each system collects any available air quality and
meteorological data associated with the image then and uploads the image and data to the
Web site.
The air quality and meteorological data available for association with a digital
image varies greatly by network. Typical sites have air temperature, relative humidity,
wind speed and direction, and precipitation available. In addition, some sites include of
one or more of the following: criteria pollutants such as ozone, fine particles, and optical
properties of the atmosphere (scattering by particles and gases, and total extinction).
The perceived air quality presented by the digital image is closely related to the
optical properties of the atmosphere. The optical properties are typically measured by
integrating nephelometers (scattering by particles) and long path transmissometers (total
extinction). It is often the case that optical measurements are not available due to specific
site and operational requirements, as well as cost. This paper presents concepts being
investigated to obtain air quality metrics directly from the digital images, relate the air
quality metrics to measured optical measurements, and develop methods to present the air
quality metrics as a surrogate for the measured optical data.
METHODS
Images for Grand Canyon and Great Smoky Mountains National Parks for the
period October 2003 through May 2004 were chosen as representative of an eastern
(relatively hazy) and western (relatively clean) vista.
Each image set consists of images at 15 minute intervals over a wide variety of
atmospheric, lighting, and ground/sky conditions. Each image is a 1600 x 1200 pixel, 8
bit per pixel JPEG with approximately 2:1 compression applied by the camera. The
camera is an Olympus 700 series operated in full automatic mode to capture images over
the widest possible lighting conditions.
During each 15 minute interval there is limited time for image metric processing
due to the time needed to capture the image, send it from the camera to the computer,
obtain the associated meteorological and air quality data, and upload the information to
the Web site. These constraints narrow the image metric processing time for the digital
images to approximately 4 minutes out of the 15 minute window.
Image analysis is affected greatly by lighting conditions. In particular, clouds
significantly affect how the image is perceived by a human observer. For this reason,
only images determined to be free of clouds (“clear sky images”) were used in this
analysis.
Image analysis includes preprocessing (such as clear sky analysis) prior to
evaluation of image metrics. Following image capture, the image evaluation process
includes the following steps:
1. Image Registration Registering each image to account for camera movement.
The image registration process entails creating a black and white image of the
registration region so that a binary comparison to a base registration image
can be done. By moving the image out of the color domain into a binary
image we can eliminate clouds, shading and other color variances for the
registration process. A pixel by pixel bitwise comparison of the two images is
done and if the images are at least 98% the same, the image is flagged as
registered. The image is then shifted by one pixel location and compared
again. This process continues until either a better fit is found (higher
correlation of values between the two images) or the process “walks” beyond
the registration boundary (typically 50 pixels). Image registration results in
numerical offsets in the horizontal and vertical axes but does not change the
image itself. In the case where the image cannot be registered (a weather
event, or cloud obscuring the registration target), the last known good
registration is used. The selection of the registration target in the image to
register is critical. If the target is very close to the camera it is almost always
visible but a small shift in registration will cause a large shift in element
locations in the distance (parallax float). A target that is a long distance from
the camera will not be visible on a consistent enough basis to have a high
confidence in the registration. A good rule of thumb is to use a target that is ¾
the distance of the range of expected visibility for the site.
2. Clear Sky Identification Testing each image for cloud free (clear sky)
conditions. Though it is not possible to determine whether an image is
completely cloud free, the clear sky tests are designed to determine which
images are least affected by clouds. To determine “clear sky images” a variety
of techniques were tested, but the most robust technique was obtained by
scanning 5 separate regions of the sky from top to bottom and determining if
there were any significant discontinuities. The tests are relatively unaffected
by the image registration since the sky zones are large and can be adjusted for
any movement in the camera mount.
3. Image Metric Extraction Evaluating each image for metrics that can be
related to measured visibility conditions. The image metrics evaluated in this
paper are listed in Table 1. It is important to note that while these metrics
have been evaluated so far, others are being investigated and may prove to be
more closely related to measured visibility. The target/sky metric is the most
sensitive to registration. Since some of the distant targets are only 30 x 30
pixels in area and a 3 x 3 matrix is used to determine the intensity of the green
component, any error in registration could lead to comparing sky to sky or
target to target.
The image sets span the period October 2003 through April 2004 and from dawn
until dusk. The lighting conditions of the scene vary dramatically by month and by time
of day. Therefore, the image metrics are likely to be date (month) and time (hour)
dependent.
Table 1. Image Metrics
Metric
Description
The target/sky contrast from digital image pixel intensities is defined
as1:
DNC’r
Target/Sky
Contrast
=
Itarget (green) - Isky (green)
Isky (green)
Where,
Itarget (green) is the intensity of the green component of a 3x3 pixel area in
the target
Isky (green) is the intensity of the green component of a 3x3 pixel area in the
sky above the target.
The intensities are the green component of the RGB triplet and range
from 0 to 255.
The frequency content of a selected area of ground (non sky) is analyzed
for frequency content. Frequency content is related to the visibility of
edges and other details in the image. High frequency content occurs when
greater detail and sharper edges are evident in the image, corresponding to
higher contrast and better visibility. Since the cloud free sky does not
contain details, only the ground is used.
The ground detail is determined by computing the mean of the Fast
Fourier Transform (FFT) of a pixel area:
Ground
Detail
Ground Detail 
1 x

xy 0
y
 f (I
)
x , y ( green)
0
Where
x is the size of the selected area in the horizontal
y is the size of the selected area in the vertical
Ix,y (green) is the intensity of the green component of the pixel at
coordinates x,y (0 to 255)
f(Ix,y) is the Fourier transform of the pixel intensity
Typical pixel areas are 512 x 512 or 1024 x 256 pixels.
RESULTS
The image metrics described in Table 1 were used to evaluate image sets from
Grand Canyon and Great Smoky Mountains National Parks. Results of the evaluation are
presented in the following sections.
Grand Canyon Image Metrics
Image metrics for Grand Canyon were compared to total extinction (bext) data
from the rim-to-river (in-canyon) transmissometer and to particle scattering (bsp) data
from the ambient nephlometer on the South Rim. Data were used only when the
transmissometer and/or nephelometer data validity flags indicated no meteorological
influences were present. Image 1 shows the target used for the target/sky contrast
analysis and the area used for the ground detail analysis. Mount Trumbull was used as
the target. It is 62 miles (99 km) from the camera site.
Image 1. Target and Ground Detail Area of Grand Canyon Image
Figures 1 through 3 show the relationship between target/sky contrast and total
extinction; Figures 4 through 6 show the relationship between target/sky contrast and
particle scattering; Table 2 presents the regression statistics for the target/sky contrast
comparisons.
Table 2. Image Metric Regression Statistics for Grand Canyon National Park
Transmissometer
bext vs. DNC’r
Slope
Intercept
R2
9:00 AM
79.8
23.6
0.12
12:00 PM
129.9
27.0
0.27
3:00 PM
63.9
20.9
0.23
Nephelometer
bsp vs. DNC’r
Slope
Intercept
R2
9:00 AM
187.8
15.7
0.20
12:00 PM
151.1
13.3
0.62
3:00 PM
90.4
9.9
0.55
Figure 7 shows the relationship between ground detail and total extinction; Figure
8 shows the relationship between ground detail and and particle scattering. The Grand
Canyon view is toward the west. The 9:00 AM image therefore is typically very bright
and does not contain much detail, regardless of the measured extinction and particle
scattering. As the day progressed, more detail becomes evident. Figures 7 and 8 clearly
show this phenomenon.
Figure 1
Figure 2
Total Extinction vs. Target/Sky Contrast Image Metric
Total Extinction vs. Target/Sky Contrast Image Metric
Grand Canyon National Park
Grand Canyon National Park
9:00 AM
60
50
50
Total Extinction (bext ) Mm-1
Total Extinction (bext ) Mm-1
12:00 PM
60
40
30
20
10
40
30
20
10
0
-0.10
-0.08
-0.06
-0.04
-0.02
0
-0.10
0.00
-0.08
-0.06
-0.02
0.00
DN
Figure 3
Figure 4
Total Extinction vs. Target/Sky Contrast Image Metric
Particle Scattering vs. Target/Sky Contrast Image Metric
Grand Canyon National Park
Grand Canyon National Park
3:00 PM
60
9:00 AM
60
50
Particle Scattering (bsp ) Mm
-1
-1
50
Total Extinction (bext ) Mm
-0.04
C'r
C'r
DN
40
30
20
40
30
20
10
10
0
0
-0.10
-0.08
-0.06
-0.04
-0.02
-10
-0.10
0.00
DNC'r
-0.08
-0.02
0.00
Figure 5
Figure 6
Particle Scattering vs. Target/Sky Contrast Image Metric
Particle Scattering vs. Target/Sky Contrast Image Metric
Grand Canyon National Park
12:00 PM
60
-1
50
Particle Scattering (bsp ) Mm
40
30
20
10
0
-10
-0.10
3:00 PM
60
50
-1
-0.04
DNC'r
Grand Canyon National Park
Particle Scattering (bsp ) Mm
-0.06
40
30
20
10
0
-0.08
-0.06
DNC'r
-0.04
-0.02
0.00
-10
-0.10
-0.08
-0.06
-0.04
DNC'r
-0.02
0.00
Figure 7
Total Extinction vs. Ground Detail Image Metric
Grand Canyon National Park
60
60
3:00 PM
40
9:00 AM
-1
12:00 PM
Particle Scattering (bsp ) Mm
Total Extinction (bext ) Mm-1
50
9:00 AM
50
Figure 8
Particle Scattering vs. Ground Detail Image Metric
Grand Canyon National Park
30
20
10
12:00 PM
40
3:00 PM
30
20
10
0
0
0.005
0.006
0.007
0.008
Ground Detail
0.009
0.010
-10
0.005
0.006
0.007
0.008
0.009
0.010
Ground Detail
Comparison of Measured and Image Metric Based Total Extinction (bext) for Grand
Canyon
Target/Sky contrast measurements can be used to estimate total extinction (bext)
using the following relationship1:
1  Cr 
bext   ln  
r C0 
where,
r is the distance to the target,
Cr is the apparent target/sky contrast (DNC’r in this case),
C0 is the inherent contrast when r = 0.
Historically, the inherent contrast used for Mount Trumbull for analysis of 35 mm
Kodachrome slides has been -0.90. Analysis of slides was performed using target and
sky density values calibrated to account for film processing using Kodak supplied film
curves2.
Calibration of digital cameras for use in estimating target/sky contrast is currently
being investigated. We have found that using -0.90 for the inherent contrast yields poor
results, while an inherent contrast of -0.40 yields much better results. If this correction is
instead applied to Cr, the correction factor is about 0.45, which is also the Gamma
correction applied to JPEG images for pleasing display on CRT and LCD computer
monitors.4
Figures 9 through 14 show the total extinction measured with the in-canyon
transmissometer versus the total extinction derived from the target/sky contrast from the
digital images for inherent contrasts of -0.90 and -0.40 (or correction factor of 0.45
applied to Cr). Table 3 presents the regression statistics for the comparisons.
Perpendicular regression was used to obtain regression lines and statistics because both
data sets are subject to error1,3 .
Figure 9
Measured vs. Image Metric Derived Total Extinction
Grand Canyon National Park
9:00 AM
C0 = -0.9
Figure 10
Measured vs. Image Metric Derived Total Extinction
Grand Canyon National Park
9:00 AM
C0 = -0.4
40
Transmissometer Measured bext (Mm )
-1
-1
Transmissometer Measured bext (Mm )
40
35
30
25
20
15
10
35
30
25
20
15
10
10
15
20
25
30
35
40
10
15
-1
30
35
40
Image Metric Derived bext (Mm )
Figure 12
Measured vs. Image Metric Derived Total Extinction
Grand Canyon National Park
12:00 PM
C0 = -0.4
Figure 11
Measured vs. Image Metric Derived Total Extinction
Grand Canyon National Park
12:00 PM
C0 = -0.9
40
-1
-1
Transmissometer Measured bext (Mm )
40
Transmissometer Measured bext (Mm )
25
-1
Image Metric Derived bext (Mm )
35
30
25
20
15
35
30
25
20
15
10
10
10
15
20
25
30
35
40
10
45
15
20
25
30
35
40
-1
-1
Image Metric Derived bext (Mm )
Image Metric Derived bext (Mm )
Figure 13
Measured vs. Image Metric Derived Total Extinction
Grand Canyon National Park
3:00 PM
C0 = -0.9
Figure 14
Measured vs. Image Metric Derived Total Extinction
Grand Canyon National Park
3:00 PM
C0 = -0.4
40
-1
-1
Transmissometer Measured bext (Mm )
40
Transmissometer Measured bext (Mm )
20
35
30
25
20
15
35
30
25
20
15
10
10
10
15
20
25
30
35
-1
Image Metric Derived bext (Mm )
40
10
15
20
25
30
35
-1
Image Metric Derived bext (Mm )
40
Table 3. Total Extinction Regression Statistics for Grand Canyon National Park
Measured vs. Image
Metric Derived bext
9:00 AM
C0=-0.90
9:00 AM
C0=-0.40
Slope
Intercept
R
0.89
-6.5
0.19
0.89
0.83
0.91
1.33
-18.24
0.15
1.33
-7.3
0.91
0.79
-4.4
0.09
0.79
2.1
0.76
(or Cr correction = 0.45)
12:00 PM
C0=-0.90
12:00 PM
C0=-0.40
(or Cr correction = 0.45)
3:00 PM
C0=-0.90
3:00 PM
C0=-0.40
(or Cr correction = 0.45)
Great Smoky Mountains Image Metrics
Image metrics for Great Smoky Mountains were compared to total scattering (bsp)
data from the Look Rock ambient nephelometer (the Park does not have a
transmissometer). Data were used only when the validity flags indicated no
meteorological influences were present. Image 2 shows the target used for the target/sky
contrast analysis and the area used for the ground detail analysis. Rich Mountain was
used as the target. It is 10 miles (16 km) from the camera site.
Image 2. Target and Ground Detail Area of Great Smoky Mountains Image
Figures 15 through 17 show the relationship between target/sky contrast
(described in Table 1) and particle scattering, and Table 4 presents the regression
statistics for the plots.
Figure 18 shows the relationship between ground detail (described in Table 1) and
particle scattering. The Great Smoky Mountains view is toward the south and the images
often include inversions and meteorology below the horizon such as clouds in the valleys.
In addition, the deciduous trees can be coated with frost, causing very bright detail
against dark coniferous trees. This manifests itself as high frequency information that is
not related to the measured particle scattering. As with Grand Canyon, the 9:00 AM
images show limited detail, regardless of the measured particle scattering
Figure 15
Figure 16
Particle Scattering vs. Target/Sky Contrast Image Metric
Particle Scattering vs. Target/Sky Contrast Image Metric
Great Smoky Mountains National Park
Great Smoky Mountains National Park
9:00 AM
80
70
60
Particle Scattering (bsp ) Mm-1
Particle Scattering (bsp ) Mm-1
12:00 PM
80
70
50
40
30
20
10
0
60
50
40
30
20
10
0
-10
-0.5
-0.4
-0.3
-0.2
-0.1
0.0
-10
-0.5
-0.4
-0.3
C'r
DN
-0.2
C'r
DN
Figure 17
Particle Scattering vs. Target/Sky Contrast Image Metric
Great Smoky Mountains National Park
3:00 PM
80
60
50
40
30
20
10
0
-10
-0.5
-0.4
-0.3
-0.2
-0.1
0.0
C'r
DN
80
Figure 18
Particle Scattering vs. Ground Detail Image Metric
Great Smoky Mountains National Park
70
Particle Scattering (bsp ) Mm-1
Particle Scattering (bsp ) Mm-1
70
9:00 AM
12:00 PM
3:00 PM
60
50
40
30
20
10
0
-10
0.003
0.004
0.005
0.006
Ground Detail
0.007
0.008
-0.1
0.0
Table 4. Image Metric Regression Statistics for Great Smoky Mountains National Park
Nephelometer
bsp vs. DNC’r
Slope
Intercept
R2
9:00 AM
100.4
46.5
0.65
12:00 PM
157.1
65.5
0.70
3:00 PM
171.7
65.9
0.75
SUMMARY
Digital images can be used to obtain image metrics correlated to measured air
quality parameters such as total extinction and particle scattering. Images and data from
Grand Canyon and Great Smoky Mountains National Parks for the period October 2003 –
April 2004 were used to evaluate two such metrics: Target/sky contrast and ground
detail.
Initial results show a clear relationship between information extracted from the
images and measured visibility parameters. These first two metrics are very preliminary
and are in the process of further development and refinement. Other metrics are also
being evaluated. It appears that application of the target/sky contrast metric requires
taking the Gamma correction inherent in JPEG images into account. The Gamma
correction is part of the overall camera calibration information: how the image created
by the camera relates to the actual scene.
Accurate registration of the images is critical to the collection of useful metrics
from the images.
REFERENCES
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Comparison of Atmospheric Extinction Measurements Made by a
Transmissometer, Integrating Nephelometer, and Teleradiometer with Natural and
Artificial Black Target, in Proceedings of APCA International Specialty
Conference – Research and Policy Aspects, Grand Teton National Park, WY,
September 7-10, 1986
2.
Dietrich, D. L., M. A. Klitch, D. S. Cismoski, and J. V. Molenar, An Assessment
of the Accuracy and Precision of Photographic Densitometric Measurements for
Monitoring Visual Air Quality, in Transactions: Visibility and Fine Particles, pp.
281-292, C. V. Mathai, Editor, Air and Waste Management Association,
Pittsburgh, PA., 1989
3. Mandel, J., Fitting Straight Lines When Both Variables are Subject to Error, in
Journal of Quality Technology, Volume 16, Number 1, January 1984
4. Poynton, C., Digital Video and HDTV, Algorithms and Interfaces, Morgan
Kaufmann Publishers, San Francisco, CA., 2003, Library of Congress Control
Number 2002115312, ISBN: 1-55860-792-7