Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/15974
標題: 彩色影像多元色彩模式轉換高頻資訊保留之研究
A Study on High Frequency Component Preservation of Color Transformations on Color Images
作者: 衛我仁
Wei, Wo-Jen
關鍵字: Color transformation
色彩模式轉換
Fourier Transformation
Wavelet Transformation
Edge Detector
傅立葉轉換
小波轉換
邊緣偵測
出版社: 土木工程學系所
引用: 阮秋琦、阮宇智 譯,数字图像处理(第二版),電子工業出版社, 北京, 2006。 张德丰,Matlab 小波分析,一版,機械工業出版社,北京,2009。 鍾國亮,影像處理與電腦視覺導論,東華出版社,2008。 繆紹綱 譯,數位影像處理-運用Matlab,東華出版社,2005。 蔡榮得,中華衛星二號遙測影像融合品質分析之研究,第二十三屆測量學術及應用研討會,2004。 蔡榮得,影像處理,國立中興大學土木工程學系授課講義,2007。 Jähne B., Digital Image Processing : Concepts, Algorithms, and Scientific Applications, 4th edition , Springer, Germany , 1997. Jähne B., Practical Handbook on Image processing for Scientific and Technical Applications, 2nd edition, CRC press LLC., USA, 2004. Richards J. A. and X. Jia, Remote Sensing Digital Image Analysis An Introduction, 4th edition, Springer, Germany, 2006. Blackledge J. M., Image Processing : Mathematical Methods and Applications, Oxford University Press Inc., New York, 1997. Prasad L. and S. S. Iyengar, Wavelet Analysis With Applications to Image Processing, CRC press LLC., USA, 1997. Plataniotis K. N. and A. N. Venetsanopoulos, Color Image Processing and Applications, Springer, Germany, 2000. Gonzalez R.C. and R. E. Woods, Digital Image Processing, 3rd edition, Upper Saddle River, New Jersey, USA, 2008. Qin Q. at el., “The Application of dyadic Wavelet in the RS Building Edge Detection,” 2004 International Conference on Image Processing., pp.1731 – 1734. Mallat S. and S. Zhong, “Characterization of Signals from Multiscale Edges,” IEEE transactions on pattern analysis and machine intelligence, Vol. 14, No. 7, pp.710 – 732, July 1992. The MathWorks Inc., Matlab 6.5 Help, The MathWorks Inc, 2002. Nass P. , “The Laplacian Pyramid”, http://www.eso.org/sci/data-processing/software/esomidas//doc/user/98NOV/volb/node319.html, 1999. Wikipedia, “YIQ”, http://en.wikipedia.org/wiki/YIQ, 2009.
摘要: 在實際運用衛星影像或航空影像時,吾人關注在影像中能帶有多少邊緣訊息,供後續處理或研究使用。人工、半自動化、自動化的影處匹配、影像對位、影像鑲嵌、影像重建;或是影像資料庫建立、搜尋、比對…等等。均己發展成熟,但針對彩色影像邊緣線萃取,現行常用的處理模式為:先將彩色影像轉換成灰階影像,再施以各種邊緣線萃取處理方法。唯何種轉換模式能代表原始彩色影像、能保留原始彩色影像的邊緣資訊,尚未有明確、統一之方法。 本研究將實驗影像轉換至不同色彩模式,再分別以空間域及頻率域的邊緣偵測方法,找出分別對映之邊緣。另以彩色影像的測邊方法,找出彩色影像之邊緣,再進行比較。本文實驗結果顯示,在空間域的部份,Lu’v’ 的轉換模式能獲得多的邊緣資訊;而在頻率域的部份,沒有明顯的單一轉換模式能獲較多的邊緣資訊,建議運用頻率域作邊緣偵測時,能每一種模式都先作前處理,尋找最具該影像代表性的轉換模式,再作後處理,期以獲得最大的研究成果。
In practical applications using satellite images or aerial images, we are concerned about the amount of edge information preserved in the images for following-up processes and studies. It has been well developed in using images in manual, semi-automatic, or automatic matching, registration, moasicking, reconstruction, and database search, etc. With respect to the edge extraction from color images, however, it is common in current model that the color images were transformed into grayscale images followed by applying an edge detector. But it is not clear what kind of color transformation is good for preserving the edge information of the original color images. In this study, the experimental images were transformed into different color models, followed by detecting corresponding edges in space domain and frequency domain, respectively for comparison with the edges extracted from the original color images. Experimental results of this study show that Lu'v' color transformation preserves the most edge information in space domain while there is no dominant color transformation in frequency domain. It is recommended that in frequency domain the color images may transformed into every color model for finding an optimal representation of the image in follow-up edge extraction.
URI: http://hdl.handle.net/11455/15974
其他識別: U0005-1607200909011700
文章連結: http://www.airitilibrary.com/Publication/alDetailedMesh1?DocID=U0005-1607200909011700
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