研究生: |
戴承武 Chen-Wu(Jacky) Tai |
---|---|
論文名稱: |
應用適應性中值模糊權重疊代濾波器於影像脈衝式雜訊去除之研究 Impulse Noise Removal of Corrupted Images Using Adaptive Median Fuzzy Weighted Recursive Filter |
指導教授: |
郭永麟
Yong-Lin Kuo |
口試委員: |
郭鴻飛
Hung-Fei Kuo 彭盛裕 Sheng-Yu Peng |
學位類別: |
碩士 Master |
系所名稱: |
工程學院 - 自動化及控制研究所 Graduate Institute of Automation and Control |
論文出版年: | 2013 |
畢業學年度: | 101 |
語文別: | 中文 |
論文頁數: | 169 |
中文關鍵詞: | 模糊理論 、脈衝雜訊 、中值濾波器 、適應性中值濾波器 、適應性中值模糊權重疊代濾波器 |
外文關鍵詞: | Impulse Noise (IN), Adaptive Median Fuzzy Weighted Recursive Filter |
相關次數: | 點閱:645 下載:1 |
分享至: |
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報 |
人類自從真空管發明以來,隨著時代的進步,演變至電晶體與半導體做為人類主要運算的工具。而後隨著電腦演算能力的強大,各式各樣的應用應運而生。在影像方面也因為計算機功能與儲存裝置的容量日益強大,而將傳統底片逐步取代。為了滿足影像應用上的需求,影像品質的改善技術就顯得相當重要。
本論文在此提出一個結合效率與可用性的方法,並應用模糊理論(Fuzzy Theory),做為一個非線性的濾波器來消除受到脈衝雜訊影響的影像。此方法對於隨機大小的脈衝雜訊與高污染度的影像有著不錯的處理結果。本文所提及的濾波方式使用適應性中值濾波器(Adaptive Median Filter)與模糊理論做為結合,成為適應性中值模糊權重疊代濾波器(Adaptive Median Fuzzy Weighted Recursive Filter),針對受到不同程度污染的影像做為處理。最後根據實驗比較不同的濾波器濾波結果,可知道本文所使用的方法可以有效的消除低污染度影像與高污染度影像的隨機脈衝雜訊,並保持該影像的完整與細節。
Nowadays, human’s computing technology is progressed from vacuum tube to transmitter and semiconductor. The quantity and quality of computing technology is faster and diverse. Lots of applications depending on computers, especially for mechanical visual technology, are used to replace older films. Since storage devices and CMOS are recently cheaper than before, images can be saved as high-quality digital data. In real world, when an image is transformed from one place to another by a digital technology, the image may be corrupted due to imposed noises like impulse noises.
In literature, there are many algorithms to process corrupted images. A well-known approach is called the median filter, which also refers to the standard filter because lots of moderate filters are developed and based on it. In this thesis, a new approach called the Adaptive Median Fuzzy Weighted Recursive Filter (AMFWRF) is proposed to enhance image filtering and obtain high-quality images. Several experiments will be performed by the AMFWRF and some traditional filters, including the Standard Median Filter (SMF), the Center Weighted Median Filter (CWMF), the Tri-State Median Filter (TSMF), the Adaptive Median Filter (AMF), and the Adaptive Fuzzy Multilevel Filter (AFMF). The tested images are those with different corrupted-level impulse noises.
[1]Gonzalez and Wintz, “DIGITAL IMAGE PROCESSING 3rd Edition”
[2]IEEE SIGNAL PROCESSING LETTERS, VOL. 7, NO. 10, OCTOBER 2000 281
[3]T.A Nodes and N.C Gallager, JR., “The output distribution of median type filter” IEEE Trans. Commun., vol. COM-32,no 5,pp.532-541,May 1984.
[4]A. Taguchi, H. Takashima, and Y. Murata, “Fuzzy Filters for Image Smoothing” in Proc. SPIE Conf. Nonlinear Image Processing V, San Jose, CA, Feb7-9, pp.332-339, 1994.
[5]Y. Choi and R. Krishnapuram, “A robust approach to image enhancement based on fuzzy logic” IEEE Transactions on Image Processing, vol. 6, pp.808-825,1997.
[6]R. Sucher, “A self-organizing nonlinear filter based on fuzzy clustering”, IEEE International Symposium On Circuit System, vol. 2 pp.101-104, 1996.
[7]蕭進松,「數位影像處理」,臺北,全華科技圖書股份有限公司,民88。
[8]Park S C,Park M K,Kang M G, “Super-resolution image reconstruction: a technical review[J]”. IEEE signal processing magazine, 2003, (5):21-36.
[9]Scott E. Umbaugh, “Computer Vision and Image Processing”, Prentice Hall International Edition, 1998.
[10]Robert V. Hogg, Allen Craig, Joseph W. McKean, “Introduction to Mathematical Statistics”, Prentice Hall, 2004.
[11]Raymond H. Chan, Chung-Wa Ho, and Mila Nikolova, “Salt and Pepper Noise Removal by Median-type Noise Detectors and Detail preserving Regularization”, July, 2004.
[12]C S. J. Ko and Y. H. Lee, “Center Weighted Median filters and their applications to image enhancement”, IEEE Transactions on Circuits and System, vol.38, pp.984-933, 1991.
[13]T. Chen, K. Kuang, L. H. Chen, “Tri-State median filter for image denoising”, IEEE Transactions on image processing, vol.8 No.12, pp.1834-1838, 1999.
[14]H. Hwang and R. A. Haddad, “Adaptive median filters: New Algorithms and result”, IEEE Trans. Image Process., vol.4, no.4, pp.499-502, Apr. 1995.
[15]X.Tang and P.S. Toh,”Adaptive fuzzy multilevel median filter,”IEEE Trans. On Image Processing, vol.4, no. 5, pp. 680-682,May 1995.
[16]Pitas and A.N.Venetsanopoulos, “Nonlinear digital filters Principles and applications”, 1990.
[17]Gonzalez and Woods, “Digital Image processing using Matlab”, Pearson Education, 2004.
[18]S. Zhang and M. A. Karim, “A new impulse detector for switching median filters”, IEEE Signal Processing Letters 9, pp. 360-363, 2002.
[19]V.R.Vijay Kumar and D.Ebenezer, ECTI TRANSACTIONS ON ELECTRICAL ENG., ELECTRONICS, AND COMMUNICATIONS VOL.6, NO.1,pp. 73-74, 2008.
[20]孫宗瀛、楊英魁,Fuzzy控制:理論、實作與應用,臺北市,全華科技圖書股份有限公司,民88。
[21]馮德益、樓世博,模糊數學方法與應用,臺北市,全華科技圖書股份有限公司,民80。
[22]王文俊,”認識Fuzzy”,臺北,全華科技股份圖書有限公司,民90。
[23]Mamdani, E.H. and S. Assilian, “An experiment inlinguistic synthesis with a fuzzy logic controller,” International Journal of Man-Machine Studies, Vol. 7 No. 1, pp. 1-13, 1975
[24]F. Russo, “Recent advances in fuzzy techniques for image enhancement”, IEEE Instrumentation and Measurement Magazine, vol. 1, no. 4, pp.29-35, 1998.