近年來，由於數位顯示裝置的快速發展，影像/視訊格式的轉換顯得愈來愈重要。影像/視訊格式的轉換包括有影像縮放以及解交錯兩大方面，兩者皆是以影像內插的方式來達成。常用的影像內插方法在影像的邊緣區域可能會有模糊的問題，所以難以提供一個清晰而銳利的視覺效果。因此，一個能夠提供良好影像品質同時保留銳利邊緣的影像內插方法是我們主要的研究目標。
本論文對於影像內插法的兩大應用，影像縮放以及解交錯進行研究，在影像縮放以及解交錯方面均提出一個以區域邊緣方向為基礎的內插演算法，將影像區分為邊緣區域以及非邊緣區域來做適應性的內插處理。在解交錯方面，更進一步地運用移動偵測來將視訊區分為移動以及靜態的部分分別做不同的處理。透過適應性的方法，能夠針對視訊中不同的區域特性，選擇出合適的內插方式，以達成良好的視訊品質。

In recent years, image/video format conversion becomes increasingly important due to the rapid development of digital display devices. Image/video format conversion includes two main fields: image scaling and de-nterlacing, which both can be performed by image interpolation. Conventional image interpolation methods suffer blurring problems in edge regions, so it is hard to produce sharp and clear visual effects. The objective of our research is to find an interpolation method which can provide good image quality while keeping the edge sharp.
In this thesis, we research on two applications of image interpolation, image scaling and de-interlacing. We propose the corresponding interpolation algorithms based on edge directions to classify the image/video into edge regions and non-edge regions for adaptive interpolation. For de-interlacing, motion detection process is adopted to divide the video into moving regions and static regions. Good video quality can be achieved by choosing the proper interpolation method according to the different local features in video sequence.

[1]A. V. Oppenheim, R. W. Schafer and J. R. Burk, "Discrete-Time Signal processing," Prentice-Hall, N.J., 1989.
[2]R. C. Gonzalez and R. E. Woods, "Digital Image Process, "Prentice-Hall, N.J., 2002.
[3]R. Keys, "Cubic Convolution Interpolation for Digital Image Processing," IEEE Trans. Signal Processing, vol. 29, pp.1153-1160, 1981.
[4]M. Hadhoud, M.I. Dessouky and F.E.A. EI-Samie, "Adaptive image interpolation based on local activity levels," in Proc. IEEE Int. Conf. Radio Science Conference, pp. 1-8, 2003.
[5]X. Li et.al., "New edge-directed interpolation," IEEE trans. on Image Processing, Vol. 10, No 10, October 2001, pp. 1521-1527.
[6]Sobel, I. and Feldman,G., "A 3x3 Isotropic Gradient Operator for Image Processing", presented at a talk at the Stanford Artificial Project in 1968, unpublished but often cited, orig. in Pattern Classification and Scene Analysis,
Duda,R. and Hart,P., John Wiley and Sons,'73, pp271-2.
[7]Y. C. Lan, "Adaptive digital zoom techniques based on hypothesized boundary," master dissertation, National Taiwan Univ. 1999.
[8]G. de Haan and E. B. Bellers, "Deinterlacing–an overview, " Proceedings of the IEEE, Vol. 86, Issue 9, pp. 1839-1857, 1998.
[9]G. de Haan and E. B. Bellers, "De-interlacing of Video Data", IEEE Transactions on Consumer Electronics, Vol. 43, Issue 3, pp. 819-825, August 1997.
[10]T. Doyle, "Interlaced to sequential conversion for EDTV applications," in Proc. 2nd. Int. Workshop Signal Processing of HDTV, 1988, pp.412–430.
[11]H. S. Oh, Y. Kim, Y. Y. Jung, A. W. Morales and S. J. Ko, "Spatio-temporal edge-based median filtering for de-interlacing," in Proc. IEEE Int. Conf.
[12]T. Koivunen, "Motion Detection of an Interlaced Video Signal, "IEEE Transactions on Consumer Electronics", Vol. 40, Issue 3, pp.753-760, August 1994.
[13]C. L. Lee, S. Chang, and C. W. Jen, "Motion detection and motion adaptive pro-scan conversion, " in Proc. IEEE ISCAS, 1991, pp, 666-669.
[14]M. Zhao and G. de Haan, "Subjective evaluation of de-interlacing techniques", Proceedings of SPIE on Image and Video Communications and Processing, Vol. 5685, pp. 683-691, March 2005.