跳到主要內容

臺灣博碩士論文加值系統

(18.204.48.64) 您好!臺灣時間:2021/08/04 16:48
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

: 
twitterline
研究生:陳宏哲
研究生(外文):Hong-JheChen
論文名稱:針對放大後影像之邊緣增強演算法
論文名稱(外文):An Edge Enhancement Algorithm for Upscaled Images
指導教授:戴顯權戴顯權引用關係
指導教授(外文):Shen-Chuan Tai
學位類別:碩士
校院名稱:國立成功大學
系所名稱:電腦與通信工程研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2012
畢業學年度:100
語文別:英文
論文頁數:70
中文關鍵詞:超解析影像放大鋸齒現象
外文關鍵詞:Super-resolutionimage upscalingjagged artifact
相關次數:
  • 被引用被引用:0
  • 點閱點閱:408
  • 評分評分:
  • 下載下載:54
  • 收藏至我的研究室書目清單書目收藏:2
近年來,影像解析度放大已成為一個熱門的研究議題,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看起來就像原本即由一個高解析度的相機所取得,或者至少呈現較自然的紋理細節。此一技術又稱為超解析,目前廣泛被應用在高品質數位電視、智慧型手機、衛星影像、監視系統攝影機等設備上。而一般常見的影像放大演算法,空間域上以內插為基礎的方法可能有過度模糊或是鋸齒狀等不好的現象,而小波域上的影像放大方法則有可能產生震鈴現象。在本論文中,提出一個針對放大後影像之邊緣增強演算法,有效減少影像放大後邊緣鋸齒狀現象,並使影像邊緣看起來較清楚、自然。實驗結果顯示,我們的演算法在提供較好的影像的視覺品質的同時,亦有良好的峰值信噪比。
Image upscaling has recently become a hot research topic. The main purpose of image upscaling is to obtain high-resolution images from low-resolution ones and these upscaled images should look like they had been taken with a camera having the resolution the same as upscaled images, and at least, present natural textures. This technique is also known as super-resolution which had been widely used in high definition televisions, smart phones, satellite images, and surveillance cameras. In spatial domain, interpolation-based methods might meet defects such as blurring and jagged artifact. However, the upscaling methods in wavelet domain might fall into ringing artifact. In this thesis, we propose an edge enhancement method for upscaled images which is able to suppress the jagged artifact effectively, and it also provides more natural and clearer edges. The experimental results show that our algorithm provides better subjective visual qualities, and meanwhile, the peak signal-to-noise ratio(PSNR) is still good.
中文摘要 ____ i
Abstract ____ ii
Acknowledgements ____ iii
Contents ____ iv
List of Tables ____ vi
List of Figures ____ vii
1 Introduction ____ 1
2 Background and Related Works ____ 4
2.1 Spatial Filtering ____ 4
2.1.1 Edge-Oriented Spatial Filtering ____ 6
2.2 Prewitt Edge Detector ____ 8
2.3 Sharpness Enhancement ____ 9
2.3.1 Sharpening Spatial Filters ____ 9
2.3.2 Weighted Median Filter ____ 10
2.3.3 Quadratic Weighted Median Filter ____ 12
2.3.4 Clipped Quadratic Weighted Median Filter ____ 15
2.4 Image Upscaling Methods ____ 17
2.4.1 Bicubic Interpolation ____ 18
2.4.2 Wavelet-domain Zero Padding ____ 19
2.4.3 Iao's Method ____ 20
2.4.4 Orthogonal Fractal Super Resolution Method ____ 23
3 The Proposed Algorithm _____ 27
3.1 Generation of Edge Maps ____ 28
3.2 Decision of Orientation Edges ____ 33
3.3 Sharpness Enhancement - Modified Clipped Quadratic Weighted Median Filter ____ 38
3.4 Dejaggy Procedure ____ 39
4 Experimental Results ____ 44
5 Conclusions and Future Works ____ 65
5.1 Conclusions ____ 65
5.2 Future Works ____ 66
References ____ 67
[1] G. Arce, A general weighted median filter structure admitting negative weights, Signal Processing, IEEE Transactions on, vol. 46, no. 12, pp. 3195-3205, Dec 1998.

[2] T. Aysal and K. Barner, Quadratic weighted median filters for edge enhancement of noisy images, Image Processing, IEEE Transactions on, vol. 15, no. 11, pp. 3294-3310, Nov. 2006.

[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] S. Dai, M. Han, W. Xu, Y. Wu, Y. Gong, and A. Katsaggelos, Softcuts: A soft edge smoothness prior for color image super-resolution, Image Processing, IEEE Transactions on, vol. 18, no. 5, pp. 969-981, May 2009.

[5] 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.

[6] M. Fischer, J. Paredes, and G. Arce, Weighted median image sharpeners for the world wide web, Image Processing, IEEE Transactions on, vol. 11, no. 7, pp. 717-727, Jul 2002.

[7] A. Giachetti and N. Asuni, Real-time artifact-free image upscaling, Image Processing, IEEE Transactions on, vol. 20, no. 10, pp. 2760-2768, Oct. 2011.

[8] R. C. Gonzalez and R. E. Woods, Digital Image Processing (3rd Edition). Upper Saddle River, NJ, USA: Prentice-Hall, Inc., 2006, sect. 3.4, Sect. 10.2.

[9] C. H. Iao and S. C. Tai, A fast algorithm for single image super resolution in both wavelet and spatial domain, Master's thesis, National Cheng Kung University, Tainan, Taiwan, R.O.C., 2011.

[10] G. E. Oien and S. Lepsoy, Fractal-based image coding with fast decoder convergence, Signal Processing, vol. 40, no. 1, pp. 105-117, 1994, international Workshop on Adaptive Methods and Emergent Techniques for Signal Processing and Communications.

[11] M. Irani and S. Peleg, Motion analysis for image enhancement : Resolution, occlusion, and transparency, Journal of Visual Communication and Image Representation, vol. 4, pp. 324-335, 1993.

[12] R. Keys, Cubic convolution interpolation for digital image processing, Acoustics, Speech and Signal Processing, IEEE Transactions on, vol. 29, no. 6, pp. 1153-1160, Dec 1981.

[13] K. M. Li and S. C. Tai, A sharpness enhancment algorithm with adaptive acutance compensation, Master's thesis, National Cheng Kung University, Tainan, Taiwan, R.O.C., 2009.

[14] B. Ramamurthi and A. Gersho, Edge-oriented spatial filtering of images with application to post-processing of vector quantized images, in Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP '84., vol. 9, Mar 1984, pp. 573 - 576.

[15] P. Rieder and G. Scheffler, New concepts on denoising and sharpening of video signals, Consumer Electronics, IEEE Transactions on, vol. 47, no. 3, pp. 666-671, Aug 2001.

[16] J. A. P. Tegenbosch, P. M. Hofman, and M. K. Bosma, Improving nonlinear upscaling by adapting to the local edge orientation, Visual Communications and Image Processing 2004, vol. 5308, no. 1, pp. 1181-1190, 2004.

[17] A. Temizel and T. Vlachos, Wavelet domain image resolution enhancement using cycle-spinning, Electronics Letters, vol. 41, no. 3, pp. 119-121, Feb. 2005.

[18] S. Thurnhofer and S. Mitra, A general framework for quadratic volterra filters for edge enhancement, Image Processing, IEEE Transactions on, vol. 5, no. 6, pp. 950-963, Jun 1996.

[19] 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.

[20] 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.

[21] L. Yin, R. Yang, M. Gabbouj, and Y. Neuvo, Weighted median filters: a tutorial, Circuits and Systems II: Analog and Digital Signal Processing, IEEE Transactions on, vol. 43, no. 3, pp. 157-192, Mar 1996.

[22] X. Zhang and X. Wu, Image interpolation by adaptive 2-d autoregressive modeling and soft-decision estimation, Image Processing, IEEE Transactions on, vol. 17, no. 6, pp. 887-896, June 2008.

連結至畢業學校之論文網頁點我開啟連結
註: 此連結為研究生畢業學校所提供,不一定有電子全文可供下載,若連結有誤,請點選上方之〝勘誤回報〞功能,我們會盡快修正,謝謝!
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top