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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
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dc.contributor.advisor | 貝蘇章 | |
dc.contributor.author | Mary Tzeng | en |
dc.contributor.author | 曾鈺鈞 | zh_TW |
dc.date.accessioned | 2021-06-13T02:02:29Z | - |
dc.date.available | 2010-07-19 | |
dc.date.copyright | 2007-07-19 | |
dc.date.issued | 2007 | |
dc.date.submitted | 2007-07-05 | |
dc.identifier.citation | [1] N.E. Huang, Z. Shen, S.R. Long, M.L. Wu,H.H. Shih, Q. Zheng, N.C. Yen, C.C. Tung and H.H. Liu, “The empirical mode decomposition and Hilbert spectrum for nonlinear and nonstationary time series analysis.” Proc. Roy. Soc.London A, Vol. 454, pp. 903–995, 1998.
[2] Rilling, G., Flandrin, P., and Goncalves, P., “On empirical mode decomposition and its algorithms.” Pro. IEEE-EURASIP Workshop on Nonlinear Signal and Image Processing, 2003. [3] A. Linderhed, “Adaptive Image Compression with Wavelet Packets and Empirical Mode Decomposition,” PhD thesis, Linköping University, Image Coding Group, 2004. [4] http://www.icg.isy.liu.se/~anna/emdcoding.html [5] J. C. Nunes, Y. Bouaoune, E. Delechelle, O. Niang and Ph. Bunel, “Image analysis by bidimensional empirical mode decomposition” Image and Vision Computing, Vol.21, Issue 12, pp.1019-1026, Nov 2003. [6] Z. X. Lin, S. L. Peng, “Boundary processing of bidimensional EMD using texture synthesis” IEEE Signal Processing Letters,Vol.12.No 1.Jan 2005. [7] D.L. Ruderman, T.W. Cronin, and C.C. Chiao, “Statistics of Cone Responses to Natural Images: Implications for Visual Coding,” J. Optical Soc. of America, vol.15, no.8, pp. 2036-2045,1998. [8] E. Reinhard, et al: Color transfer between images, IEEE .Comp. Graph. & Appl., Sep/Oct., 34-40, 2001. [9] H. Kotera, et al, Object-to-object color mapping by image segmentation, Jour. Elect. Imaging, 10(4)/1, 977-987, 2001. [10] H .Kotera, 'A Scene-Referred Color Transfer for Pleasant Imaging on Display', Proc. of IEEE International Conference on Image Processing (ICIP2005), Vol.2, II-5~II-8, 2005. [11] Yusuke Monobe, Haruo Yamashita, Toshiharu Kurosawa, Hiroaki Kotera :Image Contrast Enhancement For Displaying Without Fading Under Environment Light. [12] Yusuke Monobe, Haruo Yamashita, Toshiharu Kurosawa, Hiroaki Kotera: Fadeless Image Projection Preserving Local Contrast Under Ambient Light. Color Imaging Conference 2004: 130-135 [13] Land Edwin and McCann John, “Lightness and Retinex Theory”, Journal of the Optical Society of America,61(1), January 1971. [14] D. Jobson, Z. Rahman,and G. Woodell, “Properties and performance of a Center/Surround Retinex.” IEEE Transactions On Image Processing, vol. 6, no. 3, pp. 451-462, Mar 1997. [15] D. Jobson, Z. Rahman,and G. Woodell, “A multiscale Retinex for Bridging the gap Between color images and human observation of scenes.” IEEE Transactions On Image Processing, vol. 6, no. 7, pp. 965-976, Mar 1997. [16] S. C. Pei, and Y. M. Chiu, “Background Adjustment and Saturation Enhancement in Ancient Chinese Paintings,” IEEE Transactions On Image Processing, vol. 15, no. 10, pp. 3230–3234,Oct. 2006. [17] http://dragon.larc.nasa.gov/retinex/pao/news/ [18] http://ivrgwww.epfl.ch/~lmeylan/HdrImages/April04/april04.html [19] http://www.debevec.org/Research/HDR/ [20] http://www.cg.tuwien.ac.at/research/theses/matkovic/node84.html [21] C. Tomasi and R. Manduchi, “Bilateral filtering for gray and color images,” in Proc. 6th Int. Conf. Computer Vision, New Delhi, India,pp. 839-846, 1998. [22] Jack Tumblin, Greg Turk, LCIS: A Boundary Hierarchy for Detail-Preserving Contrast Reduction, SIGGRAPH 1999. [23] Fredo Durand, Julie Dorsey, Fast Bilateral Filtering for the Display of High Dynamic Range Images, SIGGRAPH 2002. [24] K. Chiu, M.Herf, P. Shirley, S. Swamy, C.Wang, and K. Zimmerman.”Spatially nonuniform scaling functions for high contrast images.” In Proceedings of Graphics Interface '93, pages 245–254, May 1993. [25] R. C. Gonzalez and R. E. Woods, Digital Image Processing. Second Edition, Prentice-Hall, 2002. [26] W. C. Kao and Y. J. Chen, “Multistage Bilateral Noise Filtering and Edge Detection for Color Image Enhancement,” IEEE Transactions On Consumer Electronics, vol. 51, no. 4, pp. 1346–1351, Oct 2005. [27] M Altaf , T. Gautama, T. Tanaka, and D. P. Mandic “Rotation Invariant Complex Empirical Mode Decomposition” ICASSP 2007. [28] T. Tanaka and D. P. Mandic, “Complex Empirical Mode Decomposition,” IEEE Signal Processing Letters, vol. 14, no. 2, pp. 101-104, Feb 2007. [29] Ramamurthy Bhagavatula and Marios Savvides, “Analyzing Facial Images Using Empirical Mode Decomposition for Illumination Artifact Removal and Improved Face Recognition,” ICASSP 2007. [30] Arash Abadpour and Shohreh Kasaei, “An efficient PCA-based color transfer method,” Journal of Visual Communication and Image Representation, vol.18, pp.15-34, Feb 2007. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/30379 | - |
dc.description.abstract | 近年來隨著科技產品的數位化,越來越多的東西需要影像處理的技巧,不管是在相機、手機、投影機、印表機、液晶電視、LCD…等,都需要將影像或影片美好的表現出來或紀錄下來。另外,自動影像辨識也是影像處理領域中的ㄧ項重要課題,像是安全保密系統,需要辨識一些生物特徵,就需要先將ㄧ張影像做分析,抽取特徵向量及參數,再配合一些演算法加以比對,而獲得想要的結果。
本篇論文主要分為三部分,在第一部分中,用一種稱之為經驗模分解(EMD)的演算法來分析信號及影像,可以將信號拆解成幾個函數(IMF),進而想利用這些函數的局部特徵來幫助影像辨識的應用。 本論文的第二部份是在探討圖像色彩傳遞的演算法,在環境的限制下,常常某些風景或場所的光源或顏色,所造成的景象,並不讓人們滿意,因此有了顏色傳遞的演算法,利用兩張圖像,ㄧ張原始的彩色影像及ㄧ張想要的目標彩色影像,而可以將原始影像的顏色氣氛轉變為目標影像的,除了可以讓人們將圖片轉成自己想要的顏色之外,亦可以拿來當作顏色矯正之用,或是使用名畫當目標影像,就可以使自然的圖像變成有藝術風格的感覺。 最後一部分,主要是在研究如何將ㄧ張影像,利用現有的資訊,來將它加強,使其更加清晰,或是看起來更加愉人。在許多情況下,相機無法像人眼一樣,在較暗的環境下,紀錄我們所看到的影像時,通常會較暗且有點糢糊,而這裡我們利用Retinex及 LCRT演算法,應用到電腦中的圖案,使它看起來較清晰且保留住原有的局部對比,這樣便可以彌補環境的缺憾,一樣能擁有美好的照片。除此之外,我們在照相時,數位相機都會先經過類比轉數位及壓縮的過程,過程中會有雜訊的產生,造成圖像失去一些資訊,所以要利用bilateral filtering 來降低雜訊,且保留住原有的邊界資訊,邊界輪廓資訊在影像中是很重要的ㄧ環,若使其模糊將無法辨認物體。 | zh_TW |
dc.description.abstract | With the digitization of the scientific and technological products in recent years, more and more things need the image processing skill, no matter in camera , cell-phone , projector , printer , liquid crystal TV , LCD, etc., they all need to show good-looking images or movies. In addition, the automatic image recognition is also an important subject in image processing, such as a security system that needs to recognize some biometric characteristics. However, we should analyze image and extract some characteristic features before recognition.
This thesis is composed of three parts. In first part, we discuss so-called Empirical Mode Decomposition (EMD) algorithm and apply it to analyze signals and images. EMD can decompose the signal into several Intrinsic Mode Functions (IMFs). In second part, we discuss color transfer algorithms. Under the restriction of the environment, pictures we take are not satisfied by people due to the light source or color of scenes at that place. Color transfer algorithms not only transfer color atmosphere from image to image but also can correct scene color. The last part discusses the issue that how to enhance images. In many situations, the camera is unable to imitate human eyes. For example, the camera can’t work well under darker environment. Here we utilize Retinex and LCRT algorithm to make pictures look clearer and keep the local contrast. In addition, when we take pictures by digital camera, the process of analog data to digital data would produce noise. Bilateral filtering can reduce the noise and keep the information of edges. | en |
dc.description.provenance | Made available in DSpace on 2021-06-13T02:02:29Z (GMT). No. of bitstreams: 1 ntu-96-R94942041-1.pdf: 5934981 bytes, checksum: 8e76a3334c8ec12b71b20fdac06dce86 (MD5) Previous issue date: 2007 | en |
dc.description.tableofcontents | Chapter1 Empirical Mode Decomposition 1
1.1 Introduction 1 1.2 Empirical Mode Decomposition for one dimensional signal 2 1.2.1 Intrinsic Mode Function 2 1.2.2 The sifting process of The Empirical Mode Decomposition method 3 1.2.3 Algorithmic variations of EMD 6 1.2.3.1 Interpolation method 7 1.2.3.2 Stopping criteria 8 1.2.3.3 Boundary conditions 9 1.2.4 Apply EMD to audio signal 9 1.2.5 Instantaneous Frequency and the Hilbert Spectrum 11 1.3 Empirical Mode Decomposition for two-dimensional signals 12 1.3.1 Algorithm of 2D-EMD sifting process 12 1.3.1.1 The first algorithm of BEMD 13 1.3.1.2 The second algorithm of BEMD 14 1.3.1.3 The third algorithm of BEMD 14 1.3.2 Experimental results of 2D-EMD applied to images 16 1.3.2.1 For synthesized images 18 1.3.2.2 For natural images 20 1.3.2.3 For color images 25 1.3.3 Application of BEMD 26 1.3.3.1 For text images 27 1.3.3.2 For nature color images 31 1.4 Conclusion and Future Work 31 Chapter2 Color Transfer between Images 33 2.1 Introduction 33 2.2 Color Spaces 33 2.2.1 CIE XYZ 34 2.2.2 LMS 34 2.2.3 35 2.2.4 CIE L*a*b* 35 2.2.5 HSV 36 2.3 Algorithms of Color Transfer between Images 37 2.3.1 Color Transfer Model 37 2.3.2. Principal Component Color Matching Algorithm 38 2.3.3 Object to Object Color Mapping 39 2.4 Experimental Results and Discussion 40 Chapter3 Retinex and Local Contrast Range Transform for Image Enhancement 45 3.1 Introduction 45 3.2 Retinex Algorithm 46 3.2.1 Single-Scale Retinex 48 3.2.2 Multi-Scale Retinex 49 3.2.3 Multi-Scale Retinex with Color Restoration 49 3.3 Implementation of Retinex Algorithm 51 3.3.1 Overview of the experimental system 51 3.3.2 The Results of Single-Scale Retinex and Multi-Scale Retinex 52 3.3.3 MSR with Treatment and Saturation Enhancement 55 3.4 Local Contrast Range Transform 57 3.5 Implementation of Local Contrast Range Transform Algorithm 60 3.6 Conclusion 67 Chapter 4 Bilateral Filtering 69 4.1 Introduction 69 4.2 The Notion of Bilateral Filter 70 4.3 High Dynamic Range Images Display using Bilateral Filtering 73 4.3.1 The Detail-Preserving Contrast Reduction Algorithm 74 4.3.2 Implementation and Results 75 4.4 Bilateral Filtering for Noise Removal 77 4.5 Conclusion 79 Chapter5 Conclusion and Future Work 81 Reference 83 | |
dc.language.iso | en | |
dc.title | 智慧型的彩色影像處理 | zh_TW |
dc.title | Intelligent Color Image Processing | en |
dc.type | Thesis | |
dc.date.schoolyear | 95-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 鐘國亮,鄭伯順,陳永昌 | |
dc.subject.keyword | 經驗模分解,二維經驗模分解,色彩傳遞,影像加強,去雜訊, | zh_TW |
dc.subject.keyword | empirical mode decomposition(EMD),bi-dimensional empirical mode decomposition (BEMD),color transfer,retinex,local contrast range transform,bilateral filtering, image enhancement, | en |
dc.relation.page | 86 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2007-07-09 | |
dc.contributor.author-college | 電機資訊學院 | zh_TW |
dc.contributor.author-dept | 電信工程學研究所 | zh_TW |
顯示於系所單位: | 電信工程學研究所 |
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