Stars’ Centroid Determination Using PSF-Fitting Method

• Autorzy: Suszyński R. , Wawryn K.

Identyfikatory

DOI

10.1515/mms-2015-0047

• Języki publikacji: EN

Abstrakty

EN

This paper presents an algorithm for restoring telescope images corrupted by turbulence effects and readout noise of a telescope system in order to determine centroid positions of stars, especially the position of a reference star. A computation method employing an accurate centroid estimation algorithm reconstructing a point spread function (PSF) from the recorded astronomical images has been used. Minimisation of turbulence effects and telescope control system noise in long exposure images acquired and recorded by the ground telescope is proposed. As a solution of the distortion error a minimisation signal is dedicated to GoTo calibration procedures built in control mechanisms of the electromechanical telescope system. The proposed method has been verified in the Matlab environment for real deep sky images recorded by the ground telescope system.

Słowa kluczowe

EN

centroid estimation; PSF-fitting; image processing

• Wydawca: Komitet Metrologii i Aparatury Naukowej PAN
• Czasopismo: Metrology and Measurement Systems
• Rocznik: 2015
• Tom: Vol. 22, nr 4
• Strony: 547--558
• Opis fizyczny: Bibliogr. 33 poz., rys., tab., wykr., wzory

Twórcy

autor

Suszyński R.

• Koszalin University of Technology, Faculty of Electronics and Information Technology, Śniadeckich 2, 75-543 Koszalin, Poland

autor

Wawryn K.

• Koszalin University of Technology, Faculty of Electronics and Information Technology, Śniadeckich 2, 75-543 Koszalin, Poland

Bibliografia

• [1] Suszyński, R., Wawryn, K., Dziebowski, M. (2015). An Efficient Algorithm for Determining Positions of Astronomical Objects in the Deep Sky Object Pictures. Bulletin of the Polish Academy of Sciences-Technical Sciences, 63(3), 679–684.
• [2] Suszyński, R. (2009). Convolution Method for CCD Images Processing for DSO Astrophotography. Proc. of the 52nd IEEE International Midwest Symposium on Circuits and Systems, Cancun, Mexico, 762–765.
• [3] Suszyński, R., Wawryn, K., Wirski, R. (2011). 2D image processing for auto-guiding system. Proc. of the 54th IEEE International Midwest Symposium on Circuits and Systems, Seoul, Korea, 1–4.
• [4] Suszyński, R., Wawryn, K., Wirski, R. (2011). 2D signal processing for identification and tracking moving object. Przeglad Elektrotechniczny, 87(10), 126–129.
• [5] Suszyński, R. (2008). Digital processing of CCD images for auto-guiding astrophotography system. Proc. of the 15th International Conference on Mixed Design of Integrated Circuits and Systems. Łódź, Poland, 559– 562.
• [6] Suszyński, R., Wawryn, K. (Sep. 2014). An Improvement of Stars’ Centroid Determination using PSF-fitting Method. Proc. of the International Conference on Signals and Electronic Systems, Poznań, Poland, 1–4.
• [7] Hajek, M., Dezortova, M., Materka, A., Lerski, R. (2006). Texture Analysis for Magnetic Resonance Imaging. COST B21, Med4Publishing.
• [8] Ogiela, M.R., Tadeusiewicz, R. (2008). Modern Computational Intelligence Methods for the Interpretation of Medical Images. Studies in Computational Intelligence, 84, Springer-Verlag.
• [9] Mazur-Milecka, M., Nowakowski, A. (2011). Comparison of Tracking Methods in Respect of Automation of an Animal Behavioral Test. Metrol. Meas. Syst., 18(1), 91–104.
• [10] Pełczyński, P., Ostrowski, B., Rzeszotarski, D. (2012). Motion Vector Estimation of a Stereovision Camera with Inertial Sensors. Metrol. Meas. Syst., 19(1), 141–150.
• [11] McGuire, P.C., Sandler, D.G., Hart, M. L., Rhoadarmer, T.A. (1998). Adaptive optics: neural networks wavefront sensing, reconstruction, and prediction. J.W. Clark, T. Lindenau, M.L. Ristig (eds.). Scientific applications of neural nets, Springer-Verlag Publishers.
• [12] Thomas, S., Fusco, T., Tokovinin, A., Nicolle, M., Michau, V., Rousset, G. (2006). Comparison of centroid computation algorithms in a Shack-Hartmann sensor. Monthly Notices of the Rolay Astronomical Society, 371, 323–336.
• [13] Baker, K.L., Moalem, M.M. (2007). Iteratively weighted centroid of Shack-Hartmann wave-front sensors. Opt. Express., 15, 5147–5159.
• [14] Poyneer, L.A., Palmer, D.W., LaFortune, K.N., Bauman, B. (2005). Experimental results for correlation-based wave-front sensing. SPIE. 5894, 58940N.
• [15] Vyas, A., Roopashree, M.B., Prasad, B.R. (2010). Cetroid detection by Gaussian pattern matching in adaptive optics. International Journal of Computer Applications, 1(26), 30–36.
• [16] Noll, R.J. (1976). Zernike polynomials and atmosphere turbulences. JOSA, 66(3), 207–211.
• [17] Berghi, A., Canedese, A., Masiero, A. (2007). Atmospheric turbulence prediction: a pca approach. Proc. of the IEEE 46th Conference on Decision and Control, 572–577.
• [18] Jeffs, B.D., Christou, J.C. (1998). Blind bayesian restoration of adaptive optics telescope images using generalized gaussian markov random field models. Proc. of the SPIE, Conference on Adaptive Optics and Telescope Systems, 3353.
• [19] Suszyński, R. (2009). Stand-alone station for deep space objects astrophotography. Proc. of the 52nd IEEE Int. Midwest Symposium on Circuits and Systems, Cancun, Mexico, 333–336.
• [20] Zhang, W., Jiang, Z., Zhang, H., Luo, J. (2012). Optical Image Simulation System for Space Surveillance. Proc. of the IEEE 26th Int. Parallel and Distributed Processing Symposium.
• [21] Li, C., Zhang, Y., Zheng, C., Hu, X. (2013). Implementing High-performance Intensity Model with Blur Effect on GPUs for Large-scale Star Image Simulation. Proc. of Int. Conference on Image and Graphics.
• [22] Li, C.Z., Jin, S.Z. (2006). The Implement of High Speed Correlation Tracking Algorithm Based on FPGA in Space Solar Telescope. Proc. of 8th International Conference on Signal Processing.
• [23] Zhai, C., Shao, M., Goullioud, R., Nemati, B. (2011). Micro-pixel accuracy centroid displacement estimation and detector calibration. Instrumentation and Methods for Astrophysics.
• [24] Lee, S. (2002). Pointing accuracy improvement using model-based noise reduction method. Proc. SPIE, Mecherle, G.S. (eds.). Free-Space Laser Communication Technologies XIV, 4635, 65–71.
• [25] Jendernalik, W., Blakiewicz, G., Handkiewicz, A., Melosik, M., (2013). Analogue CMOS ASICs in Image Processing Systems. Metrol. Meas. Syst., 20(4), 613–622.
• [26] Jendernalik, W., Jakusz, J., Blakiewicz, G., Szczepański, S., Piotrowski, R. (2012). Characteristics of an Image Sensor with Early-Vision Processing Fabricated in Standard 0.35 μm Cmos Technology. Metrol. Meas. Syst., 19(2), 191–202.
• [27] Jendernalik, W., Jakusz, J., Blakiewicz, G., Piotrowski, R., Szczepanski, S. (2011). CMOS realisation of analogue processor for early vision processing. Bulletin of the Polish Academy of Sciences, Technical Sciences, 59(2), 141−147.
• [28] Blakiewicz, G. (2009). Analog multiplier for a low-power integrated image sensor. Proc. of 16th Int. Conf. Mixed Design of Integrated Circuits & Systems MIXDES’09, Łódź, Poland, 226−229.
• [29] Handkiewicz, A., Lukowiak, M., Kropidlowski, M. (2002). Switched-current implementation of two-dimensional DCT for image processing. 15th Annual IEEE Int. Conf. on ASIC/SOC, 186−190.
• [30] Handkiewicz, A., Kropidlowski, M., Lukowiak, M., Bartkowiak, M. (2000). Switched-current filter design for image processing systems. 13th Annual IEEE International Conference on ASIC/SOC, 8−12.
• [31] Handkiewicz, A., Kropidlowski, M., Lukowiak, M. (1999). Switched-Current Technique for Video Compression and Quantization. 12th Annual IEEE International Conference on ASIC/SOC, 299−303.
• [32] Jendernalik, W., Blakiewicz, G., Jakusz, J., Szczepanski, S., Piotrowski, R. (2013). An Analog Sub-Miliwatt CMOS Image Sensor with Pixel-Level Convolution Processing. IEEE Trans. Circuits Syst. I, 60(2), 279−289.
• [33] Jendernalik, W., Jakusz, J., Blakiewicz, G., et al. (2011). Analog CMOS processor for early vision processing with highly reduced power consumption. 20th European Conf. on Circuits Theory and Design (ECCTD), 745−748.

Uwagi

EN

This work was supported by Koszalin University of Technology research grant no. 504.03.81. The presented method was introduced at the Conference on Signals and Electronic Systems, ICSES’2014 organized by the Faculty of Electronics and Telecommunications, Poznan University of Technology, Poland, with technical co-sponsorship of Polish IEEE CAS Society Chapter and with co-operation of Signals, Circuits and Electronic Systems Section of the Electronics and Telecommunications Committee of Polish Academy of Sciences.