Summary
In this paper we propose a simple but efficient method for increasing resolution of digital images. Such algorithms are needed in many practical applications like for example digital zoom in camcorders or conversion between conventional TV content and high resolution HDTV format. In general the main problem when converting an image to higher resolution is the lack of high frequency components in the resulting image. The result is the blurry aspect of images obtained using conventional algorithms like, for example, commonly used bilinear or bicubic interpolation. High frequency components in the frequency domain correspond to the image edges in the spatial domain. Building on this simple constatation here we propose to reconstruct high frequency components and sharp aspect of resulting images using edge information.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Jankowska, J., Jankowski, M.: A Review of Methods and Numerical Algorithms. Wydawnictwa Naukowo-Techniczne. Scientific-Technical Publishers, Warsaw (1988)
Wróbel, Z., Koprowski, R.: Processing of an Image in MATLAB Program. Silesian University Publisher, Katowice (2001)
Malina, W., Smiatacz, M.: Methods of Digital Processing of Images, Akademicka Akademicka Oficyna Wydawnicza EXIT, Warsaw. Academic Publisher - EXIT
Press, W.H., Flannery, B.P., Teukolsky, S.A., Vetterling, W.T.: Numerical Recipes in C: The Art of Scientific Computing, 2nd edn. Cambridge University Press, Cambridge (1992), http://www.nrbook.com/a/bookcpdf.php
Image processing toolbox - user guide for use with Matlab version 3, The Math Works Inc. (2001)
Tadusiewicz, R., Korohoda, P.: Computer Analysis and Images Processing. Publisher of Telecommunication Progress Foundation, Cracow (1997)
Bose, N.K., Lertarattanapanich, S., Chappalli, M.B.: Superresolution with second generation wavelets. Signal processing: Image Communication 19, 387–391 (2004)
Aniśko, C.: Edges detection, http://anisko.net/agent501/segmentacja/DetekcjaKrawedzi/
Candocia, F.M., Principe, J.C.: Superresolution of image based on local correlations. IEEE Transactions on Neural Networks 10(2), 372–380 (1999)
Chen, T.: A study of spatial color interpolation algorithms for single-detector digital cameras, http://www-ise.stanford.edu/~tingchen/
Freeman, W.T., Jones, T.R., Pasztor, E.C.: Example-based Super-resolution. IEEE ComputerGraphits and Applications (March/April 2002)
Baker, S., Kanade, T.: Super-resolution optical flow, Technical Report CMU-RI-TR-99-36, Carnegy Mellon University (1999)
Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 2nd edn. Prentice Hall, Englewood Cliffs (2002)
Świerczyński, Z., Rokita, P.: Increasing resolution of digital images using edge-based approach. Opto Electronic Review 16(1), 76–84 (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Świerczyński, Z., Rokita, P. (2009). Low-Cost Adaptive Edge-Based Single-Frame Superresolution. In: Kurzynski, M., Wozniak, M. (eds) Computer Recognition Systems 3. Advances in Intelligent and Soft Computing, vol 57. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-93905-4_6
Download citation
DOI: https://doi.org/10.1007/978-3-540-93905-4_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-93904-7
Online ISBN: 978-3-540-93905-4
eBook Packages: EngineeringEngineering (R0)