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CLC number: TN79+1; TP752

On-line Access: 2011-09-09

Received: 2011-02-18

Revision Accepted: 2011-06-30

Crosschecked: 2011-08-22

Cited: 4

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Journal of Zhejiang University SCIENCE C 2011 Vol.12 No.9 P.743-753

http://doi.org/10.1631/jzus.C1100040


Efficient implementation of a cubic-convolution based image scaling engine


Author(s):  Xiang Wang, Yong Ding, Ming-yu Liu, Xiao-lang Yan

Affiliation(s):  Institute of VLSI Design, Zhejiang University, Hangzhou 310027, China

Corresponding email(s):   wangxiang@vlsi.zju.edu.cn, dingy@vlsi.zju.edu.cn

Key Words:  Cubic-convolution, Hardware implementation, Interpolation, Engine


Xiang Wang, Yong Ding, Ming-yu Liu, Xiao-lang Yan. Efficient implementation of a cubic-convolution based image scaling engine[J]. Journal of Zhejiang University Science C, 2011, 12(9): 743-753.

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T1 - Efficient implementation of a cubic-convolution based image scaling engine
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.C1100040


Abstract: 
In video applications, real-time image scaling techniques are often required. In this paper, an efficient implementation of a scaling engine based on 4×4 cubic convolution is proposed. The cubic convolution has a better performance than other traditional interpolation kernels and can also be realized on hardware. The engine is designed to perform arbitrary scaling ratios with an image resolution smaller than 2560×1920 pixels and can scale up or down, in horizontal or vertical direction. It is composed of four functional units and five line buffers, which makes it more competitive than conventional architectures. A strict fixed-point strategy is applied to minimize the quantization errors of hardware realization. Experimental results show that the engine provides a better image quality and a comparatively lower hardware cost than reference implementations.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

[1]Aho, E., Vanne, J., Hamalainen, T.D., Kuusilinna, K., 2007. Configurable implementation of parallel memory based real-time video downscaler. Microprocess. Microsyst., 31(5):283-292.

[2]Arandiga, F., Donat, R., Mulet, P., 2003. Adaptive interpolation of images. Signal Process., 83(2):459-464.

[3]Chen, P.Y., Lien, C.Y., Lu, C.P., 2009. VLSI implementation of an edge-oriented image scaling processor. IEEE Trans. VLSI Syst., 17(9):1275-1284.

[4]Erup, L., Gardner, F.M., Harris, R.A., 1993. Interpolation in digital modems. II. Implementation and performance. IEEE Trans. Commun., 41(6):998-1008.

[5]Farrow, C.W., 1988. A Continuously Variable Digital Delay Element. IEEE Int. Symp. on Circuits and Systems, 3:2641-2645.

[6]Feng, T., Xie, W.L., Yang, L.X., 2001. An Architecture and Implementation of Image Scaling Conversion. 4th Int. Conf. on ASIC, p.409-410.

[7]Gardner, F.M., 1993. Interpolation in digital modems. I. Fundamentals. IEEE Trans. Commun., 41(3):501-507.

[8]Her, I., Yuan, C.T., 1994. Resampling on a pseudohexagonal grid. CVGIP: Graph. Models Image Process., 56(4):336-347.

[9]Hong, K.P., Paik, J.K., Kim, H.J., Lee, C.H., 1996. An edge-preserving image interpolation system for a digital camcorder. IEEE Trans. Consum. Electron., 42(3):279-284.

[10]Hou, H., Andrews, H., 1978. Cubic splines for image interpolation and digital filtering. IEEE Trans. Acoust. Speech Signal Process., 26(6):508-517.

[11]Keys, R., 1981. Cubic convolution interpolation for digital image processing. IEEE Trans. Acoust. Speech Signal Process., 29(6):1153-1160.

[12]Kim, C.H., Seong, S.M., Lee, J.A., Kim, L.S., 2003. Winscale: an image-scaling algorithm using an area pixel model. IEEE Trans. Circ. Syst. Video Technol., 13(6):549-553.

[13]Lehmann, T., Sovakar, A., Schmitt, W., Repges, R., 1997. A comparison of similarity measures for digital subtraction radiography. Comput. Biol. Med., 27(2):151-167.

[14]Lehmann, T.M., Gonner, C., Spitzer, K., 1999. Survey: interpolation methods in medical image processing. IEEE Trans. Med. Imag., 18(11):1049-1075.

[15]Li, X., Orchard, M.T., 2001. New edge-directed interpolation. IEEE Trans. Image Process., 10(10):1521-1527.

[16]Lin, C.C., Sheu, M.H., Chiang, H.K., Liaw, C., Wu, Z.C., 2008. The Efficient VLSI Design of BI-CUBIC Convolution Interpolation for Digital Image Processing. IEEE Int. Symp. on Circuits and Systems, p.480-483.

[17]Lin, C.C., Sheu, M.H., Liaw, C., Chiang, H.K., 2010. Fast first-order polynomials convolution interpolation for real-time digital image reconstruction. IEEE Trans. Circ. Syst. Video Technol., 20(9):1260-1264.

[18]Nuno-Maganda, M.A., Arias-Estrada, M.O., 2006. Real-Time FPGA-Based Architecture for Bicubic Interpolation: an Application for Digital Image Scaling. Int. Conf. on Reconfigurable Computing and FPGAs, p.1-8.

[19]Parker, J.A., Kenyon, R.V., Troxel, D.E., 1983. Comparison of interpolating methods for image resampling. IEEE Trans. Med. Imag., 2(1):31-39.

[20]Sheikh, H.R., Sabir, M.F., Bovik, A.C., 2006. A statistical evaluation of recent full reference image quality assessment algorithms. IEEE Trans. Image Process., 15(11):3440-3451.

[21]Sheikh, H.R., Wang, Z., Cormack, L., Bovik, A.C., 2010. LIVE Image Quality Assessment Database Release 2. Available from http://live.ece.utexas.edu/research/quality/subjective.htm [Accessed on Oct. 18, 2010].

[22]Shi, H.J., Ward, R., 2002. Canny Edge Based Image Expansion. IEEE Int. Symp. on Circuits and Systems, 1:785-788.

[23]Shi, J.Z., Reichenbach, S.E., 2006. Image interpolation by two-dimensional parametric cubic convolution. IEEE Trans. Image Process., 15(7):1857-1870.

[24]Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P., 2004. Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process., 13(4):600-612.

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