1 / 42

INDIAN SPACE RESEARCH ORGANISATION

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.

tynice
Download Presentation

INDIAN SPACE RESEARCH ORGANISATION

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  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. Recent Advances in Cartosat-1 Data Processing CARTOSAT-1 INDIAN SPACE RESEARCH ORGANISATION • 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 • Generation of data base of Triangulated Control Points (TCPs) in stereo mode • DEM generation over a strip, and • Improvement of image orientation parameters • Components • TCP Identification • GCP Identification • Rigorous Imaging Model

  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. 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. 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. 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 (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.

  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 • 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

  14. DEM generated for Himalayan region using new image matching algorithm DEM Status on 27-12-2010 Note : SSTS in the southern India generated using GCPL library (pink color in this region represents non availability of cloud free data )

  15. Perspective view of Sonamarg

  16. DEM REPRESENTATION OF SONAMARG AREA IN SRINAGAR DISTRICT

  17. 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 .

  18. Coordinate system for moon ISG 2010- Planetary Geomatics: An introduction

  19. TMC NEAR SIDE COVERAGE TMC 90 degree EAST COVERAGE 0° 90° TMC NADIR CoVERAGE TMC FAR SIDE COVERAGE 0° TMC 90 degree WEST COVERAGE 180° 270°

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

  21. Chandrayaan-1 TMC IMAGE MOSAIC 0 10 km Orbit: 3586 2580 3521 85 km DOP: 23-04 11-08 10-08 Strip Width: 20 km 40 km 40 km MOSAIC

  22. Jawahar Sthal Seen by TMC Portion of SAR and MIS referenced image, with uncertainty circle (Diameter- 1km) TMC Nadir Image Overlaid on Clementine Polar Image TMC Image Shackelton Crater Scale 45 km 0 Jawahar Sthal (MIP Impact Point: Lat.: - 89.76 Long.:- 39.40 ) Shackelton Crater TMC Nadir Image Orbit: 2792 DOP: 29-06-09 Scale 22 km 0 All Projections are in Polar Stereographic

  23. Air-borne HySI Registration • HySI bands are inherently acquired in non-registered mode. Successive bands look at the same feature at a time interval of 51.8 msec. • Air-borne platforms are subjected to a high attitude rate resulting in distortion in image features due to changes in scale and orientation. • The Correlation based operator is employed for visible bands and Mutual Information based operator for infra-red bands • Implemented multi-threaded registration software for speeding up computation of multi-CPU multi-core machines. Acquired Band 100 Band 256 ( Reference Band) Registered Band 100

  24. CARTOSAT-1 INDIAN SPACE RESEARCH ORGANISATION Recent Advances in Cartosat-1 Data Processing Table 2 : SSTS model accuracy Table 3 : Accuracy of ortho products for AFT camera

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

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

  27. 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. 29

  28. 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.

  29. CARTOSAT-1 INDIAN SPACE RESEARCH ORGANISATION Recent Advances in Cartosat-1 Data Processing Table-4 Data sets used for image restoration method

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

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

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

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

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

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

  36. Brazil 640x640

  37. Rome 640x640

  38. INDIAN SPACE RESEARCH ORGANISATION Thank You 42

More Related