Abstract
High resolution algorithms which enhance image resolution from a set of input low resolution images translated, rotated and aliased are widely used in practical applications. In this paper, we proposed a simple method to enhance the resolution of images after reconstructed. First, images were removed artificial aliasing from a set of aliased low-resolution images. Then we continue to enhance those images for higher quality. A filter was applied for removing remain parts: noise, blur and aliasing. The result of our proposed method is better than one of previous methods that were implemented without enhancement after reconstructed from a set of aliased images. Our method demonstrated good visual results and effect for images that are sensitive to noise after removing aliased.
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References
Vandewalle, P., et al.: A frequency domain approach to registration of aliased images with application to super-resolution. Eurasip J. Appl. Signal Process. 2006, 233–233 (2006)
Lucchese, L., Cortelazzo, G.M.: A noise-robust frequency domain technique for estimating planar roto-translations. IEEE Transactions on Signal Processing 48, 1769–1786 (2000)
Tsai, R.Y., Huang, T.S.: Multiframe image restoration and registration (1984)
Irani, M., et al.: Computing occluding and transparent motions. Int. J. Comput. Vision 12, 5–16 (1994)
Borman, S., Stevenson, R.L.: Super-resolution from image sequences-a review. In: 1998 Midwest Symposium on Circuits and Systems, Proceedings 1998, pp. 374–378 (1998)
Kim, S.P., Su, W.Y.: Subpixel accuracy image registration by spectrum cancellation. In: 1993 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1993, vol. 5, pp. 153–156 (1993)
Stone, H.S., et al.: A fast direct Fourier-based algorithm for subpixel registration of images. IEEE Transactions on Geoscience and Remote Sensing 39, 2235–2243 (2001)
Zitová, B., Flusser, J.: Image registration methods: a survey. Image and Vision Computing 21, 977–1000 (2003)
Vera, E., Torres, S.: Subpixel Accuracy Analysis of Phase Correlation Registration Methods Applied to Aliased Imagery (2008)
Berman, M., et al.: Estimating band-to-band misregistrations in aliased imagery. CVGIP: Graph. Models Image Process. 56, 479–493 (1994)
Toyran, M., Kayran, A.H.: Super resolution image reconstruction from low resolution aliased images. In: IEEE 16th Signal Processing, Communication and Applications Conference, SIU 2008, pp. 1–5 (2008)
Sung Cheol, P., et al.: Super-resolution image reconstruction: a technical overview. Signal Processing Magazine 20, 21–36 (2003)
Brown, L.G.: A survey of image registration techniques. ACM Comput. Surv. 24, 325–376 (1992)
Papoulis, A.: A new algorithm in spectral analysis and band-limited extrapolation. IEEE Transactions on Circuits and Systems 22, 735–742 (1975)
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Nguyen, QV., Nguyen, P.M.L., Cho, HM., Cho, SB. (2012). Image Enhancement after Removing Aliasing from a Set of Translated, Rotated, Aliased Images. In: Zeng, D. (eds) Advances in Information Technology and Industry Applications. Lecture Notes in Electrical Engineering, vol 136. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-26001-8_12
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DOI: https://doi.org/10.1007/978-3-642-26001-8_12
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