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1 INDIAN SPACE RESEARCH ORGANISATION Evolution of Photogrammetric models in Data Products for ISRO RS missions Presented during World Geo Spatial Forum-

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Presentation on theme: "1 INDIAN SPACE RESEARCH ORGANISATION Evolution of Photogrammetric models in Data Products for ISRO RS missions Presented during World Geo Spatial Forum-"— Presentation transcript:

1 1 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

2 2 CARTOSAT-1 INDIAN 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. Inputs SST 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 parameters Components TCP Identification GCP Identification Rigorous Imaging Model

3 3 CARTOSAT-1 INDIAN SPACE RESEARCH ORGANISATION Recent Advances in Cartosat-1 Data Processing 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.

4 4 CARTOSAT-1 INDIAN SPACE RESEARCH ORGANISATION Recent Advances in Cartosat-1 Data Processing 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.

5 5 CARTOSAT-1 INDIAN SPACE RESEARCH ORGANISATION Recent Advances in Cartosat-1 Data Processing 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.

6 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:

7 (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

8 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)

9 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.

10 Modified collinearity condition equations for spaceborne imagery where (x 0, y 0, -f) is the photo co-ordinate of principle point, (x a, y a ) is the photo co-ordinate of an image point, (X A, Y A, Z A ) is the object space co-ordinate of the same image point and (X L, Y L, Z L ) 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.

11 11 CARTOSAT-1 INDIAN SPACE RESEARCH ORGANISATION Recent Advances in Cartosat-1 Data Processing 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.

12 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 SatelliteOriginal system Level (RMS in meters) Improved thro’ ln- flight calibration (RMS in meters) Catosat-1700 – 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

13 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

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16 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

17 Perspective view of Sonamarg

18 DEM REPRESENTATION OF SONAMARG AREA IN SRINAGAR DISTRICT

19 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.

20 Coordinate system for moon 02 Feb 2010ISG 2010- Planetary Geomatics: An introduction

21 0°0° TMC NEAR SIDE COVERAGE TMC 90 degree EAST COVERAGE TMC FAR SIDE COVERAGETMC 90 degree WEST COVERAGE 90° 0°0° 180° 270°

22 Chandrayaan-1 TMC & HySI Images Fore NadirAft Fore Nadir Aft TMC Image Orbit: 1936 DOP: 17-04-09 HySI Band:16-24-32Band:49-56-64 HySI Image Orbit: 1089 DOP: 07-02-09 Histogram 1.5 km Strip Width: 20 km

23 Chandrayaan-1 TMC IMAGE MOSAIC Orbit: 35862580 3521 MOSAIC DOP: 23-0411-08 10-08 Strip Width: 20 km40 km 40 km 0 10 km 85 km

24 Jawahar Sthal Seen by TMC TMC Nadir Image Orbit: 2792 DOP: 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 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)

25 Air-borne HySI Registration 1.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 100Registered Band 100

26 26 CARTOSAT-1 INDIAN SPACE RESEARCH ORGANISATION Recent Advances in Cartosat-1 Data Processing S. NoModel accuracy (in pixels) (Fore) Model accuracy (in pixels) (Aft)No. of GCPs used RMS ScanRMS PixelRMS Scan RMS Pixel Case 12.52.322.532 Case 22.51.01.31.036 Case 31.21.31.1 94 S. NoAlong error (m) Across error (m) Radial error (m) Case 13.69.610.3 Case 24.48.09.1 Case 37.36.39.6 Case 45.56.58.5 Case 53.812.813.6 Case 6131016.4 Case 72.73.74.6 RMS(m)5.98.110.3 Table 2 : SSTS model accuracy Table 3 : Accuracy of ortho products for AFT camera

27 27 CARTOSAT-1 INDIAN SPACE RESEARCH ORGANISATION Figure 1 Cartosat-1 Strip DEM (over 500 km) generated from SSTS approach Recent Advances in Cartosat-1 Data Processing

28 28 CARTOSAT-1 INDIAN SPACE RESEARCH ORGANISATION Figure 2 SSTS Performance analysis (Model Error) Recent Advances in Cartosat-1 Data Processing

29 29 CARTOSAT-1 INDIAN SPACE RESEARCH ORGANISATION Recent Advances in Cartosat-1 Data Processing 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.

30 30 CARTOSAT-1 INDIAN SPACE RESEARCH ORGANISATION Recent Advances in Cartosat-1 Data Processing 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.

31 31 CARTOSAT-1 INDIAN SPACE RESEARCH ORGANISATION Recent Advances in Cartosat-1 Data Processing Area Date Cartosat-1 images (dd/mm/yy) Path/RowCamera Location (lat./long. in Degs) Rome08/06/05170/206Fore41.891/12.725 Rome08/06/05170/206Aft41.897/12.705 Brazil15/09/061822/494Fore-22.73/316.29 Brazil15/09/061822/494Aft-22.73/316.29 Japan31/03/06798/252Fore31.560/130.646 Japan31/03/06798/252Aft31.560/130.642 Table-4 Data sets used for image restoration method

32 32 CARTOSAT-1 INDIAN SPACE RESEARCH ORGANISATION Recent Advances in Cartosat-1 Data Processing Figure 5 (c) ROME: Cartosat-1 AFT (Original)

33 33 CARTOSAT-1 INDIAN SPACE RESEARCH ORGANISATION Recent Advances in Cartosat-1 Data Processing Figure 5 (d) ROME: Cartosat-1 AFT (PSF corrected)

34 Japan 512x512 CARTOSAT-1 INDIAN SPACE RESEARCH ORGANISATION Recent Advances in Cartosat-1 Data Processing

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36 Japan 512x512 CARTOSAT-1 INDIAN SPACE RESEARCH ORGANISATION Recent Advances in Cartosat-1 Data Processing

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