Transcript Slide 1

Medium Format Digital Cameras:
Standards and Specifications for
Calibration and Stability Analysis
A. F. Habib
Digital Photogrammetry Research Group
http://dprg.geomatics.ucalgary.ca
Department of Geomatics Engineering
University of Calgary, Canada
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Introduction
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Operational Photogrammetric Systems
• Classification of digital cameras (photogrammetric
perspective):
– Line Cameras (ADS 40)
– Large format digital frame cameras (??)
– Multi-head digital frame cameras (DMCTM, UltrCam,
DiMAC 2.0)
– Medium-format Digital Cameras (MFDC):
• Mass-produced MFDC for mapping purposes (DSS, DiMAC
Light)
• MFDC for mapping purposes from data providers (DAC 101)
• Amateur medium format digital cameras (AMFDC)
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MFDC from Data Providers
• DAC 101: Camera assembled by Selkirk Remote Sensing
•
The camera utilizes a 60mm Rollei lens with a Rodenstock Apo-Sironar shutter and a
22 megapixel digital back (5440x4080 Imacon Ixpress 132 Digital Back with 9µm
pixel size)
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Amateur Medium-Format Digital Cameras
Kodak 14n
Canon EOS 1D
AMFDC
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SONY 717
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Large Format Analog Cameras (LFAC)
WILD RC10
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Medium Format Digital Cameras (AMFDC)
SONY DSC F717
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MFDC: Relevant Questions
• Is the use of amateur MFDC in mapping applications
a temporary or permanent phenomenon?
• How to develop meaningful standards for evaluating
the outcome from the calibration procedure?
• How to develop meaningful standards for evaluating
the stability of the involved camera?
• Is there a flexibility in choosing the stability analysis
tool, which is commensurate with the geo-referencing
procedure to be implemented for this camera?
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Standards and Specification Philosophy
• Regulating the use of imaging systems in mapping
applications can be done through either:
– Having a government body (third party) responsible for
the evaluation/calibration of the imaging systems.
• Widely adopted for analog cameras (USGS, NRCAN).
– Certifying the imaging systems.
• Suitable for digital imaging systems intended for mapping
applications (DMCTM, ADS 40, UltrCam, DiMAC, DSS, etc.).
– Transferring the responsibility to the data provider after
establishing a set of standards and specifications.
• Appropriate for AMFDC and MFDC from data providers.
– Calibration, stability analysis, achievable accuracy.
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Indoor Calibration Test Field
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Indoor Calibration Test Field
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Indoor Calibration Test Field
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Indoor Calibration Test Field
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Tested Cameras (Example)
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Tested Cameras (Example)
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Data Acquisition
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Calibration Images
Center High & Low
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Calibration Images
Left High & Low
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Calibration Images
Right High & Low
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Calibration Specifications
• Variance component of unit weight:
– Tier I < 1 Pixel
– Tier II < 1.5 Pixels
– Tier III < N/A Pixels
• No correlation should exist among the estimated
parameters
• Standard deviations of the estimated IOP
parameters (xp, yp, c):
– Tier I < 1 Pixel
– Tier II < 1.5 Pixels
– Tier III < N/A
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Stability Analysis: Proposed Approach
Top View
Side View
P.C.I
cI
?
≡
P.C.II
cII
Bundle I
Bundle II
Original Image Grid Points
Distortion-free Grid Points using IOPI
Distortion-free Grid Points using IOPII
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Stability Analysis: Proposed Approach
• Method 1: Zero Rotation (ZROT)
– Same perspective center (no shift allowed)
– Parallel image coordinate systems (no rotation allowed)
P.C.

Offset  x2
cI


cI
 x1 
c II

Ray from Bundle I
Ray from Bundle II
cII
Original Image Points
Distortion-free Grid Point using IOPI
c
x2 I
cII
Distortion-free Grid Point using IOPII
Projected Grid Point of IOPII
x2
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Stability Analysis: Proposed Approach
• Method 2: Rotation (ROT)
– Same perspective center (no shift allowed)
– Rotation allowed
P.C. (0, 0, 0)
Spatial
Offset
pI (xI, yI,-cI)
R (, , )
pII (xII, yII,-cII)
Original Image Points
Distortion-free Grid Point using IOPI
Distortion-free Grid Point using IOPII
Projected Grid Point of IOPII
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Stability Analysis: Proposed Approach
• Method 3: Single Photo Resection (SPR)
– Object space comparison
– Spatial and rotational offsets permitted
cI
P.C.I
P.C.II
Original Image Points
Distortion-free Grid Point using IOPI
Distortion-free Grid Point using IOPII
Bundle I
Bundle II
Back-projected Object Points
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Stability Specifications
• The similarity measure (RMSE offset) value is
computed to express the degree of similarity
between the bundles from two sets of IOPs.
• The cameras must meet the following
specifications to be deemed stable.
– Tier I < 1 Pixel
– Tier II < 1.5 Pixels
– Tier III : N/A
• A software is available for the calibration and
stability analysis procedures.
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MFDC: Relevant Questions
• Can the stability analysis be used for evaluating the
equivalency of different distortion models?
– Appropriate distortion models.
• Should the standards for the calibration and stability
analysis be expressed in terms of image or object
space units?
• What is the achievable accuracy from MFDC?
– Geo-referencing method (GCP, GNSS-assisted,
GNSS/INSS).
– Number of tie points.
• What are the applications most suited for MFDC?
– Small blocks, in combination with LiDAR systems, in
combination with high resolution satellite scenes.
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MFDC & Aerial Mapping
• Kodak DCS-14n
• CMOS (4536x 3024)
• 50 mm Zeiss lens
• Pixel size: 7.9x7.9 µm
• 12 Photos
• Flying height: 1200 m
• GSD: 0.20 meters
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MFDC & Aerial Mapping
Federal University of Parana, Brazil
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MFDC & Aerial Mapping
Number of Check Points
Mean
(m)
Standard
dev. (m)
RMSE
(m)
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Signalized
Targets
X
0.055
0.147
0.157
Y
0.210
0.113
0.238
Z
0.170
0.311
0.355
X
0.231
0.343
0.413
Y
0.201
0.141
0.246
Z
-0.033
0.693
0.694
28 Natural
Targets
Root Mean Square Error Analysis
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MFDC & Aerial Mapping
Orthophoto generated for Kodak (left) and RC10 (right) imagery
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MFDC, LiDAR & Satellite Scenes
IKONOS
stereo-pair
up
DSS
three six-image blocks
with GPS position of
exposure stations
middle
LIDAR data
down
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Experimental Results: Dataset
Lower Block
Lower LIDAR Scan
DSS: Lower Block
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MFDC, LiDAR & Satellite Scenes
35.000
N/A 30.000
NO Frames
25.000
Frame
GPS
RMSE, m
20.000
Lines(45)
15.000
Lines (138)
Patches (45)
10.000
Patches (139)
5.000
0.000
0
1
2
3
4
5
6
7
8
9
10
15
40
Number of Control Points
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