影像超解析科技的應用於近年來顯著增加，其主要目的為藉由低解析度影像來產生高解析度影像，而這些高解析度影像必須保持良好的視覺品質，呈現自然的紋理細節。影像放大演算法以空間域上的內插法最為常見，然而經過放大的影像可能會產生模糊的現象，因此常以空間銳化濾波器將模糊影像變得較清晰銳利，而銳化程度的多寡是決定影像的視覺品質的關鍵。在本論文中，提出一個以影像自相似性為基底的方法，使用簡單線性性迴歸來建立一重建模型，適應性地增強影像視覺品質。實驗結果顯示，我們的演算法同時提供較好的影像品質和峰值信噪比及結構相似性品質指標。

The application of image Super-Resolution technologies in recent years has increased noticeably.
The main purpose of image upscaling is to obtain high-resolution images from low-resolution images, and these upscaled images should keep satisfactory visual qualities and present natural textures. The most popular image upscaling algorithms are based on interpolation methods in spatial domain. However, the upscaled images may produce blurring artifacts. Therefore, using spatial sharpening filters is usually used to make blurred images sharp and clear. The quantity of image sharpening is the key to decide the visual qualities of upscaled images.
In this thesis, a method based on Self-Similarity of images and using simple linear regression to build a reconstruction model for improving visual qualities of upscaled images adaptively is proposed.
The experimental results show that our algorithm provides better subjective visual qualities as well as the peak signal-to-noise ratio(PSNR) and structural similarity (SSIM).

[1] S. Baker and T. Kanade, Hallucinating faces," in Automatic Face and Gesture
Recognition, 2000. Proceedings. Fourth IEEE International Conference on, 2000,
pp. 83{88.
[2] H. Chang, D.-Y. Yeung, and Y. Xiong, Super-resolution through neighbor em-
bedding," in Computer Vision and Pattern Recognition, 2004. CVPR 2004. Pro-
ceedings of the 2004 IEEE Computer Society Conference on, vol. 1, 2004, pp.
I{I.
[3] S. Dai, M. Han, Y. Wu, and Y. Gong, Bilateral back-projection for single image
super resolution," in Multimedia and Expo, 2007 IEEE International Conference
on, july 2007, pp. 1039 {1042.
[4] H. Demirel and G. Anbarjafari, Image resolution enhancement by using discrete
and stationary wavelet decomposition," Image Processing, IEEE Transactions on,
vol. 20, no. 5, pp. 1458 {1460, May 2011.
[5] W. Dong, D. Zhang, G. Shi, and X. Wu, Nonlocal back-projection for adaptive
image enlargement," in Image Processing (ICIP), 2009 16th IEEE International
Conference on, 2009, pp. 349{352.
[6] C. E. Duchon, Lanczos ltering in one and two dimensions," J. Appl.
Meteor., vol. 18, no. 8, pp. 1016{1022, Aug. 1979. [Online]. Available:
http://dx.doi.org/10.1175/1520-0450(1979)018%3C1016:l oat%3E2.0.co;2
[7] R. C. Gonzalez and R. E. Woods, Digital Image Processing (3rd Edition). Upper
Saddle River, NJ, USA: Prentice-Hall, Inc., 2006.
[8] S.-H. Hong, R.-H. Park, S. Yang, and J.-Y. Kim, Image interpolation using
interpolative classi ed vector quantization," Image and Vision Computing,
vol. 26, no. 2, pp. 228 { 239, 2008. [Online]. Available: http://www.sciencedirect.
com/science/article/pii/S0262885607000765
[9] K. Jensen and D. Anastassiou, Subpixel edge localization and the interpolation of
still images," Image Processing, IEEE Transactions on, vol. 4, no. 3, pp. 285{295,
1995.
[10] R. Keys, Cubic convolution interpolation for digital image processing," Acoustics,
Speech and Signal Processing, IEEE Transactions on, vol. 29, no. 6, pp. 1153{1160,
1981.
[11] X. Li and M. Orchard, New edge-directed interpolation," Image Processing, IEEE
Transactions on, vol. 10, no. 10, pp. 1521 {1527, oct 2001.
[12] S. Mallat and G. Yu, Super-resolution with sparse mixing estimators," Image
Processing, IEEE Transactions on, vol. 19, no. 11, pp. 2889 {2900, nov. 2010.
[13] M. Sonka, V. Hlavac, and R. Boyle, Image Processing, Analysis, and Machine
Vision. Thomson-Engineering, 2007.
[14] A. Temizel and T. Vlachos, Wavelet domain image resolution enhancement using
cycle-spinning," Electronics Letters, vol. 41, no. 3, pp. 119{121, 2005.
[15] J. van Ouwerkerk, Image super-resolution survey," Image and Vision
Computing, vol. 24, no. 10, pp. 1039 { 1052, 2006. [Online]. Available:
http://www.sciencedirect.com/science/article/pii/S0262885606001089
[16] Z. Wang, A. Bovik, H. Sheikh, and E. Simoncelli, Image quality assessment: from
error visibility to structural similarity," Image Processing, IEEE Transactions on,
vol. 13, no. 4, pp. 600 {612, April 2004.
[17] Y. C. Wee and H. J. Shin, A novel fast fractal super resolution technique,"
Consumer Electronics, IEEE Transactions on, vol. 56, no. 3, pp. 1537 {1541, aug.
2010.
[18] J. Yang, J. Wright, T. Huang, and Y. Ma, Image super-resolution via sparse
representation," Image Processing, IEEE Transactions on, vol. 19, no. 11, pp.
2861{2873, 2010.
[19] X. Zhang and X. Wu, Image interpolation by adaptive 2-d autoregressive mod-
eling and soft-decision estimation," Image Processing, IEEE Transactions on,
vol. 17, no. 6, pp. 887{896, 2008.