Abstract
A block-based upsampling method for images and videos is proposed in this work. Block classification is first conducted in the DCT domain to categorize 8x8 image blocks into several types: smooth areas, edges and others. For the plain background and smooth surfaces, simple patches are used to enlarge the image size without degrading the resultant visual quality. Since human eyes are more sensitive to edges, a more sophisticated technique is applied to edge blocks. They are approximated by a facet model so that the image data at subpixel positions can be generated accordingly. By taking temporal information into account, this concept can further be applied to videos. To upsample an image block in the current frame, we may borrow the upsampled version of the corresponding block in the reference frame if the residual is tolerable. Experimental results are shown to demonstrate the great reduction of computational complexity while the output visual quality still remains satisfactory.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Stark, H., Oskoui, P.: High-resolution image recovery from image-plane arrays, using convex projections. J. Opt. Soc. Am. A 6, 1715–1726 (1989)
Irani, M., Peleg, S.: Improving resolution by image registration. Graphical Models and Image Processing 53, 231–239 (1991)
Schultz, R.R., Stevenson, R.L.: A Bayesian Approach to Image Expansion for Improved Definition. IEEE Transaction of Image Processing 3(3) (1994)
Gunturk, B.K., Altunbasak, Y., Mersereau, R.: Bayesian resolution-enhancement framework for transform-coded video. In: Proceedings of IEEE International Conference on Image Processing, vol. 2, pp. 41–44 (2001)
Gevrekci, M., Gunturk, B.K., Altunbasak, Y.: POCS-Based Restoration Of Bayer-Sampled Image Sequences. In: International Conference on Acoustics, Speech and Signal Processing (ICASSP), vol. 1, pp. I-753– I-756 (2007)
Tom, B.C., Katsaggelos, A.K.: Reconstruction of a High Resolution Image from Multiple Degraded Mis-Registered Low Resolution Images. In: SPIE VCIP, vol. 2308, September 1994, pp. 971–981 (1994)
Elad, M., Feuer, A.: Restoration of a single superresolution image from several blurred, noisy, and undersampled measured images. IEEE Trans. Image Processing 6(12), 1646–1658 (1997)
Liu, S., Bovik, A.C.: Efficient DCT-Domain Blind Measurement and Reduction of Blocking Artifacts. IEEE Trans. on Circuits and Systems for Video Technology 12(12), 1139–1149 (2002)
Pratt, W.K.: Digital Image Processing, 4th edn
Lee, M.-S., Shen, M.-Y., Jay Kuo, C.-C.: A content-adaptive up-sampling technique for image resolution enhancement. Intelligent Information Hiding and Multimedia Signal Processing (IIHMSP) 1, 87–90 (2007)
Park, S.C., Park, M.K., Kang, M.G.: Super-resolution image reconstruction a technical overview. IEEE Signal Processing Magazine 20(3), 21–36 (2003)
Borman, S., Stevenson, R.L.: Super Resolution From Image Sequences - A Review. In: Proceedings of Circuit and Systems (1998)
Tudor, P.N.: MPEG-2 Video Compression. Electronics & Communication Engineering Journal (1995), http://www.bbc.co.uk/rd/pubs/papers/paper_14/paper_14.shtml
Isnardi, M.: MPEG-2 Video Compression, November 29 (1999), http://www.leitch.com/resources/tutorials/mpeg-2VideoCompression.pdf
Haskell, B.G., Puri, A., Netravali, A.N.: Digital Video: An Introduction to MPEG-2
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Lee, MS., Chang, CW. (2009). An Efficient Upsampling Technique for Images and Videos. In: Muneesawang, P., Wu, F., Kumazawa, I., Roeksabutr, A., Liao, M., Tang, X. (eds) Advances in Multimedia Information Processing - PCM 2009. PCM 2009. Lecture Notes in Computer Science, vol 5879. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10467-1_6
Download citation
DOI: https://doi.org/10.1007/978-3-642-10467-1_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-10466-4
Online ISBN: 978-3-642-10467-1
eBook Packages: Computer ScienceComputer Science (R0)