INFORMATION CHANGE THE WORLD

International Journal of Image, Graphics and Signal Processing(IJIGSP)

ISSN: 2074-9074 (Print), ISSN: 2074-9082 (Online)

Published By: MECS Press

IJIGSP Vol.5, No.5, Apr. 2013

A Comparative Analysis of Image Scaling Algorithms

Full Text (PDF, 656KB), PP.55-62


Views:117   Downloads:3

Author(s)

Chetan Suresh,Sanjay Singh,Ravi Saini,Anil K Saini

Index Terms

Image Scaling, Nearest-neighbour, Bilinear, Bicubic, Lanczos, Modified Bicubic

Abstract

Image scaling, fundamental task of numerous image processing and computer vision applications, is the process of resizing an image by pixel interpolation. Image scaling leads to a number of undesirable image artifacts such as aliasing, blurring and moiré. However, with an increase in the number of pixels considered for interpolation, the image quality improves. This poses a quality-time trade off in which high quality output must often be compromised in the interest of computation complexity. This paper presents a comprehensive study and comparison of different image scaling algorithms. The performance of the scaling algorithms has been reviewed on the basis of number of computations involved and image quality. The search table modification to the bicubic image scaling algorithm greatly reduces the computational load by avoiding massive cubic and floating point operations without significantly losing image quality.

Cite This Paper

Chetan Suresh,Sanjay Singh,Ravi Saini,Anil K Saini,"A Comparative Analysis of Image Scaling Algorithms", IJIGSP, vol.5, no.5, pp.55-62, 2013.DOI: 10.5815/ijigsp.2013.05.07

Reference

[1]J. Xiao, X. Zou, Z. Liu, X. Gu, A Novel Adaptive Interpolation Algorithm For Image Resizing, International Journal of Innovative Computing, Information and Control, Vol. 3, n. 6(A), pp. 1335-1345, 2007.

[2]Wolberg, G., Massalin, H., A Fast Algorithm for Digital Image Scaling, Proceedings of Computer Graphics International (Year of Publication: 1993).

[3]F. Chin, A. Choi, Y. Luo, Optimal Generating Kernels for Image Pyramids by Piecewise Fitting, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 14, n. 12, pp. 1190-1198, 1992.

[4]P. Meer, E.S. Baugher, A. Rosenfeld, Frequency Domain Analysis and Synthesis of Image Pyramid Generating Kernels, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. PAMI-9, n. 4, pp. 512-522, 1987.

[5]P.P.Vaidyanathan, Multirate Systems and Filter Banks (Prentice Hall, 1993).

[6]G. Wolberg, Digital Image Warping (IEEE Computer Society Press, 1992).

[7]W.H. Press, B.P. Flannery, S.A. Teukolsky, W.T. Vetterling, Numerical Recipes: The Art of Scientific Computing (FORTRAN Version) (Cambridge University Press, 1989).

[8]C. Boor, A Practical Guide to Splines (Springer-Verlag, 1978).

[9]R.C. Gonzalez, R.E. Woods, Digital Image Processing (Prentice Hall, 2007).

[10]K. Turkowski, Filters for common resampling tasks, In A.S. Glassner (Ed.), Graphic Gems, 4 (San Diego: Academic Press, 1990, 147-170).

[11]M. Unser, A. Aldroubi, M. Eden, Fast B-Spline Transforms for Continuous Image Representation and Interpolation, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 13, n. 3, pp. 277-285, 1991.

[12]Meijering, E.H.W., Niessen, W.J., Viergever, M.A., The sinc-approximating kernels of classical polynomial interpolation, Proceedings of the International Conference on Image Processing (Page: 652-656 Year of Publication: 1999 ISBN: 0-7803-5467-2).

[13]Zhe, W., Jiefu, Z., Mengchu, Z., A Fast Autoregression Based Image Interpolation Method, Proceedings of the IEEE International Conference on Networking, Sensing and Control (Page: 1400-1404 Year of Publication: 2008 ISBN: 978-1-4244-1685-1).

[14]Amanatiadis, A., Andreadis, I., Konstatinidis, K., Fuzzy Area-Based Image Scaling, Proceedings of the IEEE Instrumentation and Measurement Technology Conference (Page: 1-6 Year of Publication: 2007 ISBN: 1-4244-0588-2).

[15]Mueller, N., Nguyen, T.K., Image interpolation using classification and stitching, Proceedings of the IEEE International Conference on Image Processing (Page: 901-904 Year of Publication: 2008 ISBN: 978-1-4244-1765-0).

[16]Morse, B.S., Schwartzwald, D., Isophote-based interpolation, Proceedings of the IEEE International Conference on Image Processing (Page: 227-231 Year of Publication: 1998 ISBN: 0-8186-8821-1).

[17]Liang, F., Xie, K., An Image Interpolation Scheme combined with Artificial Neural Network, Proceedings of the Third International Conference on Natural Computation (Page: 99-102 Year of Publication: 2007 ISBN: 978-0-7695-2875-5).

[18]S.D. Ruikar, D.D. Doye, Image Denoising using Tri Nonlinear and Nearest Neighbour Interpolation with Wavelet Transform, International Journal of Information Technology and Computer Science, Vol.4, n. 9, pp. 36-44, 2012.

[19]D. Su, P. Willis, Image Interpolation by Pixel Level Data-Dependent Triangulation, Computer Graphics Forum, Vol.23, n. 2, pp. 189-201, 2004.

[20]Zhang, J., Kuo, C., Region-adaptive Texture-aware Image Resizing, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (Page: 837-840 Year of Publication: 2012 ISBN: 978-1-4673-0045-2).

[21]Jiang, W., Xu, H., Chen, G., Zhao, W., Xu, W., An Improved Edge-adaptive Image Scaling Algorithm, Proceedings of the IEEE Eighth International Conference on ASIC (Page: 895-897 Year of Publication: 2009 ISBN: 978-1-4244-3868-6).

[22]Lai, Y., Tzeng, C., Wu, H., Adaptive Image Scaling Based on Local Edge Directions, Proceedings of the International Conference on Intelligent and Advanced Systems (Page: 1-4 Year of Publication: 2010 ISBN: 978-1-4244-6623-8).

[23]Jenkins, W., Mather, B., Munson, D., Jr., Nearest Neighbor And Generalized Inverse Distance Interpolation For Fourier Domain Image Reconstruction, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (Page: 1069-1072 Year of Publication: 1985).

[24]W. Ye, A. Entezari, A Geometric Construction of Multivariate Sinc Functions, IEEE Transactions on Image Processing, Vol.21, n. 6, pp. 2969-2979, 2012.

[25]Xiao, L., Dong, X., Soong, A.C.K., Effective Interpolator Design for Pilot Symbol Assisted Modulation Systems, Proceedings of the IEEE Global Telecommunications Conference (Page: 3671-3675 Year of Publication: 2004 ISBN: 0-7803-8794-5).

[26]Wenbo, T., Jianming, Y., Xiaojin, M., Ji, L., Power system harmonic detection based on Bartlett–Hann Windowed FFT interpolation, Proceedings of the Asia-Pacific Power and Energy Engineering Conference (Page: 1-3 Year of Publication: 2012 ISBN: 978-1-4577-0545-8).

[27]Ye, Z., Suri, J., Sun, Y., Janer, R., Four Image Interpolation Techniques for Ultrasound Breast Phantom Data Acquired Using Fischer's Full Field Digital Mammography and Ultrasound System (FFDMUS): A Comparative Approach, Proceedings of the IEEE International Conference on Image Processing (Page: 1238-1241 Year of Publication: 2005 ISBN: 0-7803-9134-9).

[28]Zhang, Y., Li, Y., Zhen, J., The Hardware Realization of Bicubic Interpolation Enlargement Algorithm Based on FPGA, Proceedings of the Third International Symposium on Information Processing (Page: 277-281 Year of Publication: 2010 ISBN: 978-1-4244-8627-4).