1 / 32

Classical Approaches of Informatics to Astronomical Images Processing

a presentation by Dimo T. Dimov 1 (dtdim@iinf.bas.bg ) in collaboration with Milcho Tsvetkov 2 and Yuliana Goranova 2. Classical Approaches of Informatics to Astronomical Images Processing. 1 Institute of Information Technologies at Bulgarian Academy of Science (IIT-BAS)

hedva
Download Presentation

Classical Approaches of Informatics to Astronomical Images Processing

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. a presentation by Dimo T. Dimov1 (dtdim@iinf.bas.bg ) in collaboration with Milcho Tsvetkov2 and Yuliana Goranova2 Classical Approaches of Informatics to Astronomical Images Processing 1Institute of Information Technologies at Bulgarian Academy of Science (IIT-BAS) 2Institute of Astronomy at Bulgarian Academy of Science (IA-BAS) Sofia 7th Bulgarian-Serbian Astronomical Conference June 01-04, 2010, Chepelare, Bulgaria

  2. Acknowledgements This work was supported by following grants of the Institute of Information Technologies (IIT) at Bulgarian Academy of Sciences (BAS): Grant # DO-02-275/2008 of the National Science Fund at Bulgarian Ministry of Education & Science, and Grant # 010088/2007 of BAS

  3. Some Abbreviations ADBI = Astronomical DB of Images FITS = Flexible Image Transfer System HT = Hough Transform EFIRS = Experimental Fast Image Retrieval System

  4. Contents 1. EFIRS – an instrumental system used for our demonstrations 2. ADBI: some types of astro-images of interest - star chain plate images - Carte-du-Ciel plate images - astro-images of lost positioning Hough transform to stress on stretched objects in plate images - (,)HT, it is equal to a 2D Radon transform - (,)HT applied for astro-images of interest - Plate images preprocessing: adaptive binarization - Exact HT performance for the both given grids: the input grid and the chosen grid for HT output 4. Registrationof astro-images: “lost-in-space” type (vector type or grid based algorithm) 5. Discussion & Conclusion

  5. References • 1. Kounchev, O., Tsvetkov, M., Dimov, D., et al.: 2009, Bulg. J. Phys.,32/2. • 2. Aniol, R., Duerbeck, H.W., Seitter, W.C., Tsvetkov, M.K. 1990, IAU Symp. • 137,Kluwer Acad. Publish., Dordrecht-Boston-London, 85. • 3. Starck, J.-L., Murtagh F., 2002, Springer-Verlag, 303. • Bertin, E., Arnouts, S., 1996, Astronomy & Astrophysics Supplement Series, 117, 393. • Spratling B. B., and D. Mortari, Algorithms J., 2 (2009), 93-107 • (www.mdpi.com/journal/algorithms) • Kolomenkin, M., Polak, S., Shimshoni, I., and Lindenbaum M., (2008) • (http://mis.hevra.haifa.ac.il/~ishimshoni/papers/StarTracker.pdf)

  6. input image image content to a key index key access Image DB of PORB EFIRS DBMS … … Result of EFIRS operation Original images from the Patent Office of Republic of Bulgaria (PORB)

  7. HT of a point

  8. HT of 2 points

  9. HT of 4 points

  10. HT of a line (the points of a line)

  11. HT of imagination of lines (text rows)

  12. HT of a chain star image See EFIRS experiment (No.26) For more detail, see: Dimov, D., K. Tsvetkova, M. Tsvetkov, A. Kolev, Hough Transform Approach to Flare Stars’ Identification in Chain Plate Images, Serdica J., Sofia, (to appear, 2010)

  13. HT of a Carte-du-Ciel plate image See EFIRS experiment (No.26)

  14. Necessary refinements of HTused for astronomical applications Preliminary binarization of input images, i.e. segmentation in 2 levels of intensity: object(s) & background A locally adaptive and data driven binarization to suppress different “lightening conditions” and/or artifacts in plate images For more detail, see: Dimov, D., and A. Dimov, Data Driven Approach to Binarization of Astronomical Images, in Proceedings of CompSysTech’2010, Sofia, Bulgaria, (to appear) (2) Exact HT performance for the both given grids: the input astro-image grid and the chosen grid of HT accumulation space. - the basic idea is briefly shared in next 2-3 slides - the currently developed software explores an approximation of above idea; it’s expected that the operation efficiency (processing speed and preciseness) will be much better. For more detail, see: Dimov, D., Exact Performance of (,)-Hough Transform for Star Chain Images Processing, to be presented at CTF’2010, 04-10.06.2010, Sozopol, Bulgaria

  15. Locally Adaptive Data Driven Binarization of Astro Images A part of Pleiades (For better visibility) A binarization by an adaptive threshold surface A binarization by a global optimal threshold (as a negative example)

  16. Locally Adaptive Data Driven Binarization… The division map for binarization by parts A threshold surface calculated for the division map A demo is available. For more detail see: Dimov, D., and A. Dimov, Data Driven Approach to Binarization of Astronomical Images, in Proceedings of CompSysTech’2010, Sofia, Bulgaria, (to appear)

  17. Exact HT performance for the both given grids: (the input grid and the chosen grid for HT output) Basic types for the trapezium-like hexagon TC6, i.e. the arbitrary vertical section of Cosine-shape of a given image pixel.

  18. Registrationof astro-images • Registration or positioning towards a stellar catalog. A similar task: for star trackers, cf. the survey by Spratling and Mortari (2009), as well as Kolomenkin et al (2008). • Algorithm types: “lost-in-space”, recursive (tracking) and non-dimensional ones. • In our case (archive plate images), we should most of all interested in application/modification of “lost-in-space” algorithms. This is the most general case, nevertheless of not being the most often one. • We have not to obey strong limitations for real time processing and/or for computing energy consumption that are typical for star trackers of cosmic installation. • Possible decisions: (1) Search-Less Algorithm (SLA)of Mortari (star 3-angles based) (2) Lost-in-space algorithm of Kolomenkin (“star distances” based) (3) Grid algorithm based on CBIR techniques (an idea still under construction).

  19. input image image content to a key index key access Image DB of PORB EFIRS DBMS … … Result of EFIRS operation Original images from the Patent Office of Republic of Bulgaria (PORB)

  20. EFIRS’sBackground (for AstroInformatics) - a visual comparison of E1, E2 & E3 keys of EFIRS - a promising result for an image of Pleiades An original mark image. Log2DFT-SPM-FWT-keyE1 Log2DFT-SPM-FCsT-keyE3 Log2DFT-SPM-FFT-keyE2

  21. EFIRS’sBackground (continues…)for more details, see “ADMKD'07 Varna_.ppt”(e.g. slides #25  #28)And, it’s better to see a demo 

  22. A Brief Demonstration of EFIRS: • If the Demo is not possible show next 4 slides: • EFIRS: the IDB browser • EFIRS: the Search-engine start menu • EFIRS: the Search-engine (result table I) • EFIRS: the Search-engine (result table II)

  23. EFIRS: the IDB browser

  24. EFIRS: the Search-engine start menu

  25. EFIRS: the Search engine (result table I)

  26. EFIRS: the Search engine (result table II)

  27. Discussion & Conclusions • Discussion ? • Possible conclusion – HT is promising tool for flare object identification in star-chain plate images • Possible conclusion – HT can be also used for auxiliary measuring lines determination in Carte-du-Ciel plate images • Which type of lost-in-space algorithm to chose for archive plate images registration

  28. Thank You!

  29. How EFIRS operates with astro-images, now 3 images of experiment: BEL016A000076 (Orion), BEL016A000134 (Pleiades), and ROZ050 000046 (centre). 2D Wavelets: (MatLab similarities ) 2D Fourier transform: Simple Polar Mapping (SPM), Log Polar Mapping (LgPM): PFWT (Polar Fourier Wavelet Transform): similarities with the Fourier-Mellin transform Generation of EFIRS image keys to ADBI Binarization experiment: an aim: to locate potential star centers Contouring: not very promising, eventually to isolate (manually ?) damaged regions of a plate Zoom: ? a demo tour in Pleiades ? Hough/Radon transform: (see ROZ050 000046 (centre) )?

More Related