1 INDIAN SPACE RESEARCH ORGANISATION Evolution of Photogrammetric models in Data Products for ISRO...

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INDIAN SPACE RESEARCH ORGANISATION

Evolution of Photogrammetric models in Data Products for ISRO RS missions

Presented during World Geo Spatial Forum- 2011

Pradeep K Srivastava,Deputy Director, Signal and Image Processing,

Space Applications Centre (ISRO)Ahmedabad, India

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CARTOSAT-1INDIAN SPACE RESEARCH ORGANISATION

Recent Advances in Cartosat-1 Data Processing

STEREO STRIP TRIANGULATION (SST) APPROACH

Basically SST is performed over a stereo pair of Cartosat-1 image segment by employing photogrammetric bundle adjustment technique.

InputsSST requires a primary GCP library data with accuracy better than 1 m. Major tasks under SST are

(i) Generation of data base of Triangulated Control Points (TCPs) in stereo mode

(ii) DEM generation over a strip, and(iii) Improvement of image orientation parametersComponentsTCP IdentificationGCP IdentificationRigorous Imaging Model

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Conjugate point identification

Identification of tie points or conjugate points is done in an automatic way by stereo image matching that uses Hierarchical Matching technique.Image Pyramids are formed by sub-sampling the original image at various scales (levels of hierarchy)Selection of optimal number of pyramids depends on the viewing angle of the stereo pair used and terrain undulations.The match points obtained in the last level are the conjugate points used for DEM generation.The process is tuned to identify, one conjugate point for every 100 m * 100 m region on ground.

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TCP identification

TCPs are image points, but they may not be available on a topographic map, like in the case of GCPs. The generation of TCP database involves

• Feature detection to extract candidate • Matching to find the location• Computation of ground coordinates• Blunder detection • Human visual confirmation

Approximately one TCP per square kilometer in Cartosat-1 stereo strip of 500 km length is selected.

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Rigorous Imaging Model

•Cartosat-1 rigorous imaging model is based on photogrammetric collinearity conditions.

•System knowledge over 52 s gap between two cameras in sighting a common GCP is utilised

•Model uses onboard star sensors’ measurement for attitude and GPS based state vector information for orbit.

1. Inertial co-ordinate system(ECI) :2. Geocentric (Greenwich) system, Earth Centered Rotating (ECEF) 3. Local Orbital co-ordinate system: 4. Spacecraft body co-ordinate system: 5. Image co-ordinate system:

(φ, λ, h) Object point in geodetic Everest (Ellipsoid) Frame of reference

through co-ordinate transformation (Spherical to Cartesian)

(X, Y, Z) in Geocentric Cartesian co-ordinate system (ECEF Everest ellipsoid)

through 7 parameter datum conversion

X, Y, Z in WGS 84 (ECEF Greenwich frame)

rotation through sidereal angle

X, Y, Z in Geocentric inertial system(ECI) transformation through orbital elements

X, Y, Z in local orbital co-ordinate system through attitude angles

X, Y, Z in Spacecraft body co-ordinate system tilt angles

X, Y, Z in Focal Plane or Image Plane Coordinate system

and interior orientation Point in image co-ordinate system s,p (scanline and pixel)

The relation between the image and the object co-ordinate systems is expressed by a 3x3 orthogonal matrix designated by M. The nine elements of M are functions of the orientation parameters.

in which v is the vector in x, y, z system and V is the same vector in the X, Y, Z system.

Modified collinearity condition equations for spaceborne imagery

where (x0, y0, -f) is the photo co-ordinate of principle point, (xa, ya) is the photo co-ordinate of an image point , (XA, YA, ZA) is the object space co-ordinate of the same image point and (XL, YL, ZL) is the perspective center co-ordinate in object space co-ordinate system. k is the scale factor that is equal to the ratio of the length of a to the length of A in figure 2. M is the rotation (orientation) matrix from one co-ordinate system to the other, which is a function of exterior orientation parameters.

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GCP identification

•GCPs are the features on ground whose precise ground coordinates are known and which are identifiable on the image.

•A database having well distributed network of ground control points over Indian landmass with ground coordinates obtained using differential GPS and image chips for manual/auto correlation purpose is used for operational use.

In-flight geometric calibration

• Conventional• In-flight calibration successfully

completed for Cartosat-1, Cartosat-2 & Cartosat-2A as part of initial phase exercises/ normal phase to improve the system level performance

• Using Rigorous imaging sensor model techniques with the help of ‘ Imaging sensor data (control points)’

• Achieved accuracies

Satellite Original system Level

(RMS in meters)

Improved thro’ ln-flight calibration

(RMS in meters)

Catosat-1 700 – 1000 m Around 100 m for both Fore and Aft

Cartosat-2

1300 m Better than 50 m

Cartosat-2A

500 – 700 m Better than 70 m

New Techniques• New techniques studied and carried

out R&D exercises for utilising only a set of imaging sensors’ information for Cartosat-1

• Promising results obtained without Control points or a few control points required for validation

• Two Imaging sensors (stereo) from the same orbit of Cartosat-1 are used to derive pseudo attitude

• Platform biases are estimated using only image points or with minimum controls

- Photogrammetry Co-planarity Approach (with/without controls) - Photogrammetry Line based Resection method (no controls) - Accuracy achieved better than 10 pixels for Cartosat-1 - Further study and R&D efforts are on for Chandrayaan-1

National DEM from CARTOSAT-1

• DEM – 1/3 arc-sec posting (~10m)• OrthoImage – 1/12 arc-sec resolution co-

registered (0.1 pixel registration accuracy)• 15 m (CE-90) plannimetric accuracy• 8 m (LE-90) height accuracy• Density of match points ~ 4% using aspect-

based correlation, concensus based outlier identification

• Automatic breakline identification/ incorporation through TIN modeling

DEM generated for Himalayan region using new image matching algorithm

LEGEND SSTS run using GCPS collected from neighboring segments Not processed Outside India Completed

Note : SSTS in the southern India generated using GCPL library (pink color in this region represents non availability of cloud free data )

DEM Status on 27-12-2010

Perspective view of Sonamarg

DEM REPRESENTATION OF SONAMARG AREA IN SRINAGAR DISTRICT

• Four software packages for Chandrayaan-1 Data Processing are operationalised at ISSDC viz.,

– Quick Look Display (QLD) for TMC and HySI with near real time and offline options

– Level-0/1 data processing of TMC and HySI with PDS generation

– Data Archival in PDS standards for all the payload data

– Browse and data visualisation • First day products and many special

products are generated from TMC/HySI and MIS sensors

• Payload Operations Centre (POC) for TMC and HySI is setup at SIPA/SAC for generating higher level products like Lunar DEM, Lunar Atlas and mosaics. This also acts as a gateway for HeX data to PRL.

• A high bandwidth data link is established between SAC and ISSDC and the available raw data has been transferred to SAC-POC

Chandrayaan-1 Data Processing• L-1 DPGS s/w at ISSDC - Operations established in 3 identical chains - No. of data sets processed successfully at ISSDC : TMC – 949 (1071) , HySI - 1071 (1158)

•Active archive for TMC/HYSI/LLRI & AO payloads available at ISSDC

•Long Term Archive (LTA) will be ready by end of 2010

•Data Dissemination of TMC & HYSI from active archive available at ISSDC

• DEM and Lunar Atlas generation at SAC- POC

• Using RPCs & COTS software, DEM generation activity from TMC is on using COTS package customisation. Indigenous software is being developed .

Coordinate system for moon

02 Feb 2010 ISG 2010- Planetary Geomatics: An introduction

0°

TMC NEAR SIDE COVERAGE TMC 90 degree EAST COVERAGE

TMC FAR SIDE COVERAGE TMC 90 degree WEST COVERAGE

90°0°

180°270°

Chandrayaan-1 TMC & HySI Images

Fore Nadir AftFore

Nadir

Aft

TMC ImageOrbit: 1936DOP: 17-04-09

HySI HySI

Band:16-24-32 Band:49-56-64

HySI ImageOrbit: 1089DOP: 07-02-09

Histogram1.5 km

Strip Width: 20 km

Chandrayaan-1 TMC IMAGE MOSAIC

Orbit: 3586 2580 3521

MOSAIC

DOP: 23-04 11-08 10-08StripWidth: 20 km 40 km 40 km

0 10 km

85 km

Jawahar Sthal Seen by TMC

TMC Nadir ImageOrbit: 2792DOP: 29-06-09

TMC Nadir Image Overlaid on Clementine Polar Image

TMC Image

Jawahar Sthal (MIP Impact Point:Lat.: - 89.76 Long.:- 39.40 )

Shackelton Crater

Shackelton Crater Scale

0 45 km

Scale

0 22 km

All Projections are in Polar Stereographic

Portion of SAR and MIS referenced image, with uncertainty circle (Diameter- 1km)

Air-borne HySI Registration1. HySI bands are inherently acquired in non-registered mode. Successive bands look at the same feature at a time interval

of 51.8 msec.

2. Air-borne platforms are subjected to a high attitude rate resulting in distortion in image features due to changes in scale and orientation.

3. The Correlation based operator is employed for visible bands and Mutual Information based operator for infra-red bands

4. Implemented multi-threaded registration software for speeding up computation of multi-CPU multi-core machines.

Band 256 ( Reference Band)Acquired Band 100 Registered Band 100

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S. No Model accuracy (in pixels) (Fore)

Model accuracy (in pixels) (Aft) No. of

GCPs used

RMS Scan RMS Pixel RMS Scan

RMS Pixel

Case 1 2.5 2.3 2 2.5 32Case 2 2.5 1.0 1.3 1.0 36Case 3 1.2 1.3 1.1 1.1 94

S. No Along error(m)

Across error(m)

Radial error(m)

Case 1 3.6 9.6 10.3Case 2 4.4 8.0 9.1Case 3 7.3 6.3 9.6Case 4 5.5 6.5 8.5Case 5 3.8 12.8 13.6Case 6 13 10 16.4Case 7 2.7 3.7 4.6RMS(m) 5.9 8.1 10.3

Table 2 : SSTS model accuracy

Table 3 : Accuracy of ortho products for AFT camera

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Figure 1 Cartosat-1 Strip DEM (over 500 km) generated from SSTS approach


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Figure 2 SSTS Performance analysis (Model Error)


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CONCLUSIONS

The model accuracy achieved through SSTS approach is better than 10 m (circular error ~ 4 pixels at product, inclusive of all the processing errors further to SSTS). From the analysis on results of all available dates, SSTS performance is seen to be good in terms of realised accuracy for both along track and across track error. SSTS pre-adjustment results at GCPs were used for geometrical in-flight calibration analysis to estimate spacecraft misalignment to cameras, attitude biases and inter camera alignment angles. SSTS has been found to be successful in all cases when cloud free segments of stereo pair data and required number of GCPs (10 or more) were available for given pass.

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Approach for restoration of Cartosat-1 imagery

The laboratory measured PSFs for the Fore and Aft sensors of Cartosat-1 were taken as the degradation function for restoration of respective imagery. Wiener filter, which incorporates the degradation function as well as the model of noise, was designed in frequency domain for each sensor. The noise to signal ratio was modelled to vary exponentially between nsrmin and nsrmax for low to high frequencies. Restoration of the FORE and AFT images was performed block-wise. Overlap of few pixels was maintained between successive blocks to avoid artefacts at block boundaries. Fast Fourier Transform (FFT) techniques were used to achieve high speed.

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Area Date Cartosat-1 images(dd/mm/yy)

Path/Row Camera Location (lat./long. in Degs)

Rome 08/06/05 170/206 Fore 41.891/12.725Rome 08/06/05 170/206 Aft 41.897/12.705Brazil 15/09/06 1822/494 Fore -22.73/316.29Brazil 15/09/06 1822/494 Aft -22.73/316.29Japan 31/03/06 798/252 Fore 31.560/130.646Japan 31/03/06 798/252 Aft 31.560/130.642

Table-4 Data sets used for image restoration method

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Figure 5 (c) ROME: Cartosat-1 AFT (Original)

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Figure 5 (d) ROME: Cartosat-1 AFT (PSF corrected)

Japan512x512



Brazil640x640

Rome640x640

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INDIAN SPACE RESEARCH ORGANISATION

1 INDIAN SPACE RESEARCH ORGANISATION Evolution of Photogrammetric models in Data Products for ISRO...

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