在一般的電子影像多媒體產品中，需要用到LCD或其他顯示器來觀察我們所想要知道的資訊。通常原始的影像資料來源，並不符合所播放的顯示器的銀幕大小。我們需要由有限的原始影像資料，來看到我們所想要的適合影像的大小，需要用到影像內插法來縮放影像，然而傳統的影像縮放只能限制2的冪次方，而且影像縮放倍率只能用整數倍。在一般的影像內插法有最近鄰近法(Nearest Neighbor)，雙線性法(bilinear)，雙立方法(bicubic)。最近鄰近法(Nearest Neighbor)是最快最省硬體的方法，但是縮放後的影像會有嚴重的失真(artifact)與在邊緣中會有鋸齒狀(jagging)產生。雙線性法(bilinear)運算簡單只需要四個原來的像素(pixel)，與所要內插的點距離反比，就可以產生一個新的像素點，且效果會比最近鄰近法(Nearest Neighbor)好一點，但在放大高倍率時依然會容易有失真(artifact)。雙立方法(bicubic) 運算複雜，需要用到十六個像素(pixel)與sinc方程式做捲積(convoluteion)就可以得到新的像素(pixel)，縮放後的影像品質會比另外最近鄰近法(Nearest Neighbor)和雙立方法(bicubic)的結果好，但是立方法(bicubic)的計算複雜度太高。而我們所提出的影像內插法是用五個tap的濾波器，由五個像素(pixel)與縮放的係數來做權重所得到新的像素(pixel)，計算簡單而且有良好的視覺效果。

In digital multimedia and imaging, people need to use the LCD monitors or other screens to display the information we want to know. The image sources are versatile and always do not conform to the size of the screen. In order to display the limited image source on the screen, we need image scaling. The traditional image scaling factors are restricted to sizes which are the power of two. The ratios of the traditional image scaling are integer. Some interpolation algorithms include the nearest neighbor interpolation, bilinear interpolation and the bicubic interpolation. The nearest neighbor interpolation is the fastest and easiest method. The nearest neighbor will cause the jagging effects and artifacts after image scaling. The bilinear interpolation only uses four original pixels to create the new pixel. The visual quality of the bilinear interpolation is better than nearest neighbor interpolation. The bilinear interpolation still has the artifacts and blurring effects after enlarge the image. The bicubic interpolation uses 16 original pixels and performs convolution with the Sinc function. Its visual quality is much better than nearest neighbor interpolation and bilinear interpolation. However, the bicubic interpolation is computationally complex. We propose the 5-tap image scaling filter with lower complexity. The scaling filter needs five original pixels to create the new pixel. The proposed algorithm is simple and provides good visual quality.

Bibliography

[1]. Injun Hwang; Bongsoon Kang; Gerard, J., ”High-resolution Image Scaler Using interpolation Filter for Multimedia Video Applications,” Consumer Electronics, IEEE Transactions on Volume 43, Issue 3, Aug. 1997 Page(s):813 - 818 Digital Object Identifier 10.1109/30.628720

[2]. Ze-Nian Li Mark S. Drew, “Fundamentals of Multimedia” Pearson Prentice Hall, 2004, ISBN 0-13-127256-X p112~p125.

[3]. Oscal T.-C. Chen, Kuan-Tsang Wang, “A High-Speed and High-Performace Video Format Conversion System”, Circuit and Systems, 1997. Proceedings of the 40th Midwest Symposium on Volume 2, 3-6 Aug. 1997 Page(s):957 - 960 vol.2 Digital Object Identifier 10.1109/MWSCAS.1997.662234

[4]. Peter Swartz, Hemant Mallapur, Xu Dong, “Video Format Conversion in A Single chip” Consumer Electronics, 2002.ICCE. 2002 Digest of Technical Papers. International Conference on 18-20 June 2002 Page(s):60 - 61 Digital Object Identifier 10.1109/ICCE.2002.1013926

[5]. A. Murat Tekalp University of Rochester, “Digital Video Processing”, Presentice Hall PTR Upper Saddle River, NJ 07458, 1995. ISBN 0-13-190075-7 p62~70

[6].E.B. Bellers, ”De-interlacing A contribution to the interlaced versus progressive video debate” Philips Electronics N.V. 1999 ISBN 90-74445-47-0 p106~110

[7]. A. V. Oppenheim, R. W. Schafer, and J. R. Burk, “Discrete-Time Signal Processing.” Upper Saddle River, NJ: Prentice-Hall, 1989. ISBN 0-13-083443-2

[8] A. V. Oppenheim, R. W. Schafer, and J. R. Burk,”Signal and System”, Upper Saddle River, NJ: Prentice-Hall, 1983, ISBN 0-13-651175-9.

[9]. T. M. Lehmann, C. Gönner, and K. Spitzer, “Survey: interpolation methods in medical image processing.” Medical Imaging, IEEE Transactions on Volume 18, Issue 11, Nov. 1999 Page(s):1049 - 1075 Digital Object Identifier 10.1109/42.816070

[10].Robert G. Keys, “Cubic Convolution Interpolation for Digital Image Processing”, IEEE Train. Acoust., Speech, Signal Process, Vol. ASSP-29, pp.1153-1160, 1981.

[11].Hsieh S. Hou and Harry C. Andrews, “Cubic Splines for Image Interpolation and Digital Filtering.”, IEEE Trans. Acoust., Speech, Signal Process. Vol. ASSP-26, pp.508-517, 1987

[12]. Jong-Ki Han; Seung-Ung Baek; “Parametric cubic convolution scaler for enlargement and reduction of image” Consumer Electronics, IEEE Transactions on
Volume 46, Issue 2, May 2000 Page(s):247 - 256 Digital Object Identifier 10.1109/30.846654

[13] C. H. Kim, S. M. Seong, J. A. Lee, L.S. Kim, “Winscale: an image-scaling algorithm using an area pixel model”, IEEE, Trans. On Circuit and Systems for Video Technology, Vol. 13, pp.549-533, June 2003

[14]E. Aho, J. Vanne, K. Kuusilinna, T.D. Hamalainen, “Comments on Winsacle: an image-scaling algorithm using an area pixel model”, IEEE, Trans. On Circuits and System for Video Technology, Vol. 15, pp.454-455, March2005

[15]. Vasudev Bhaskaran Konstantinos Konstantinides Hewlett-Packard Laboratories, “Image and Video Compression Standards Algorithms and Architectures”, 1997 by Kluwer Academic Publishers ISBN 0-7953-9952-8, P272~P274.

[16]. Yuan-Hao Huang; Chiuan-Shian Chen; “A novel control method for horizontal and vertical scaler in the arbitrary resolution LCD panel” Consumer Electronics, 2005. ICCE. 2005 Digest of Technical Papers. International Conference on 8-12 Jan. 2005 Page(s):73 - 74 Digital Object Identifier 10.1109/ICCE.2005.1429723

[17]. C. Hentschel, “Generic Method for 2-D Image Resizing with Non-Separable Filters,” IEEE International conference on Image Processing, 2004.

[18]. Eero Aho, Jarno Vanne, Timo D. Hämäläinen, and Kimmo Kuusilinna,
“Block-Level Parallel Processing for Scaling Evenly Divisible Images” Circuits and Systems I: Regular Papers, IEEE Transactions on Volume 52, Issue 12, Dec. 2005 Page(s):2717 – 2725, Digital Object Identifier 10.1109/TCSI.2005.856894

[19]. Hentschel, C.; Schiemenz, S.; “High quality, low complexity image scaler suitable for rational factors” Consumer Electronics, 2006. ICCE '06. 2006 Digest of Technical Papers. International Conference on 7-11 Jan. 2006 Page(s):179 - 180
Digital Object Identifier 10.1109/ICCE.2006.1598369

[20]. Gheorghe Berbecel. “Digital image display: algorithms and implementation” Chichester Hoboken, NJ: J. Wiley, 2003 ISBN 0-470-84921-5 P83~p115.

[21]. Neil A Dodgson, “Quadratic Interpolation for Image Resampling,” Image Processing, IEEE Transaction on Volume 6, Issue 9, Sept. 1997 Page(s):1322 - 1326
Digital Object Identifier 10.1109/83.623195

[22]. Rafael C. Gonzalez, “Digital Image Processing Edition,” 2002 by Prentice-Hall, Inc. Upper Saddle River, New Jersey 07458. ISBN 0-201-18075-8

[23]. Ethan E. Danahy, Sos S. Agaian, Kare A. Panetta, “Algorithms for the Resizing of Binary and Grayscale Images Using A Logical Transform”, Proc. Of SPIE-IS&T Electronic Imaging, SPIE Vol.6497, 64970Z, 2007

[24]. S.-C. Hsia ,B.-D. Liu ,J.-F. Yang and C.-H. Huang, “A Parallel video converter for
displaying 4:3 image on 16:9 HDTV receivers,” IEEE transactions on circuits and
systems for video technology, vol. 6, pp. 695-699, Dec. 1996.

[25]. Volleberg, G.T.G.; van Dalfsen, A.J.; de With, P.H.N.; “Flexible re-sampling topology for widescreen television systems” Consumer Electronics, 2005. ICCE. 2005 Digest of Technical Papers. International Conference on 8-12 Jan. 2005 Page(s):463 - 464 Digital Object Identifier 10.1109/ICCE.2005.1429918