Adaptive Enhancement Techniques for Solar Images


Radio astronomy radio telescope plays the role of a linear operator, affecting the function that describes the object of research, formation of image of a monitored object. This paper presents methods for reconstruction and correction of solar radio images using the algorithm of rejections, the updated Weiner-filter, and the method CLEAN designed by Hegbomom (Pseudonym, 2009) for point sources. It is the process of numerical convolution in signal handling, an algorithm for separating weak-contrast formations on the solar which represents most points of the actual limb by using the ellipse equation. Consequently, the filling algorithm is applied by moving from the center to the ellipse points and filling each point by solar image data. Finally, a linear limb-darkening expression is used to remove the limb darkening. Different examples of the intermediate and final results are presented in addition to the developed algorithm.

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M. Al-Rababah, A. Al-Marghilani, M. Al-Shomrani and I. A. Atoum, "Adaptive Enhancement Techniques for Solar Images," Journal of Signal and Information Processing, Vol. 4 No. 4, 2013, pp. 359-363. doi: 10.4236/jsip.2013.44045.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] V. V. Zharkova, S. S. Ipson, S. I. Zharakov, A. Benkhalil, J. Aboudarham and R. D. Bentley, “A Full-Disk Image Standardisation of the Synoptic Solar Observations at the Meudon Observatory,” Solar Physics, Vol. 214, No. 1, 2003, pp. 89-105.
[2] N. Fuller and J. Aboudarham, “Automatic Detection of Solar Filaments versus Manual Digitization,” International Conference on Knowledge-Based and Intelligent Information & Engineering Systems, Vol. 3215, 2004, pp. 467-475.
[3] N. Fuller, J. Aboudarham and R. D. Bentley, “Filament Recognition and Image Cleaning on Meudon Hα Spectroheliograms,” Solar Physics, Vol. 227, No. 1, 2005, pp. 61-73.
[4] M. Qu, F. Y. Shih, J. Jing and H. Wang, “Automatic Solar Filament Detection Using Image Processing Techniques,” Solar Physics, Vol. 228, No. 1-2, 2005, pp. 119- 135.
[5] F. Y. Shih and A. J. Kowalski, “Automatic Extraction of Filaments in H-Alpha Solar Images,” Solar Physics, Vol. 218, No. 1-2, 2003, pp. 99-122.
[6] P. N. Bernasconi, D. M. Rust and D. Hakim, “Advanced Automated Solar Filament Detection and Characterization Code: Description, Performance and Results,” Solar Physics, Vol. 228, No. 1-2, 2005, pp. 97-119.
[7] R. Qahwaji and T. Colak, “Automatic Detection and Verification of Solar Features,” International Journal of Imaging Systems and Technology, Vol. 15, 2005, pp. 199- 210.
[8] A. D. Joshi, N. Srivastava and S. K. Mathew, “Automated Detection of Filaments and Their Disappearance Using Full-Disc Hα Images,” Solar Physics, Vol. 262, No. 2, 2009, pp. 425-436.
[9] Y. Yuan, F. Y. Shih, J. Jing, H. Wang and J. Chae, “Automatic Solar Filament Segmentation and Characterization,” Solar Physics, Vol. 272, No. 1, 2010, pp. 101-117.
[10] National Solar Observatory, “Ca K and H Alpha Images Explained,” 1996.
[11] G. Kom, A. Tiedeu and M. Kom, “Automated Detection of Masses in Mammograms by Local Adaptive Thresholding,” Computers in Biology and Medicine, Vol. 37, No. 1, 2007, pp. 37-48.
[12] N. Efford, “Digital Image Processing, a Practical Introduction Using Java,” 1st Edition, Pearson Education Limited, Addison Wesley, 2009.
[13] A. M. K. Hamid, “Linearized Limb-Darkening Coefficients for Use in Analysis of Eclipsing Binary Light Curves,” Astrophysics and Space Science Journal, Vol. 53, No. 1, 1977, pp. 181-192.
[14] I. A. Atoum, R. S. Qahwaji, T. Colak and Z. H. Ahmed, “Adaptive Thresholding Technique for Solar Filament Segmentation,” Ubiquitous Computing and Communication Journal, Vol. 4, 2009, pp. 91-95.

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