簡易檢索 / 詳目顯示

回結果列表
研究生： 賴宗煊
Lai, Tsung-Hsuan
論文名稱： 支援向量回歸為基之具預測能力影像補全技術研發
Image Completion Using Prediction Concept Based on Support Vector Regression
指導教授： 陳裕民
Chen, Yuh-Min
學位類別： 碩士
Master
系所名稱： 電機資訊學院 - 製造資訊與系統研究所
Institute of Manufacturing Information and Systems
論文出版年： 2012
畢業學年度： 100
語文別： 英文
論文頁數： 40
中文關鍵詞： 影像補全 、影像修復 、紋理合成 、結構預測
外文關鍵詞： image completion, image inpainting, texture synthesis, structure prediction
相關次數： 點閱：89  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

    • 影像補全(Image completion, IC) 是將受損影像修復或移除物件的技術，已廣泛地應用於生活當中。本研究透過導入預測之概念，不僅能夠透過系統自動選取出影像中之受損區域，並藉由結合影像補全與預測之概念，提出一利用支援向量回歸(Support vector regression, SVR)進行結構預測之影像補全技術。透過改善過去方法，以及加上預測結構的方式，並在最後進行失真樣本的偵測及改善，以有效地提升修復影像品質。實驗結果亦證明了能夠有效修復大多數之受損影像，且能夠為人眼所接受。

    Image completion is a technique widely used that automatically removes objects or repairs damaged portions of image. However, information regarding the original image is often lacking in structure reconstruction, and as a result, images with complex structures are difficult to restore. This study proposed a SVR-oriented Image Completion (SVR-IC) method, the goal of which is to predict the original structure of unknown areas and then repair or make appropriate adjustments to the structure and texture of the damaged area. From the experimental results, SVR-IC produced images of good quality that were superior to those of other methods. The results show that integrated structure prediction to image completion can effectively enhance the quality of the restored image.

    摘要......................................................II Abstract.................................................III 致謝......................................................IV Table of Contents..........................................V List of Figures..........................................VII Chapter 1. Introduction....................................1 Chapter 2. Literature Review...............................4 2.1 Image Completion.......................................4 2.2 Support Vector Regression..............................6 Chapter 3. SVR-Oriented Image Completion...................8 3.1 Unknown Region Selection Method........................9 3.2 Image Repairing Method................................11 3.2.1 Structure Prediction................................11 3.2.2 Priority Computation................................14 3.2.3 Energy Function Minimization........................15 3.2.4 Patch Synthesis.....................................16 3.3 Artifact Detection Method.............................17 Chapter 4. Experiments Results............................19 4.1 Experiment Results of the Unknown Region Selection Method....................................................19 4.2 Experiment Results of the Image Inpainting Method.....22 4.3 Experiment Results of the Artifact Detection Method...26 4.4 Comparison and Discussion of the Methods..............27 4.4.1 Subjective Comparison by the Researcher.............28 4.4.2 Objective Comparison by the Examinees...............30 Chapter 5. Conclusions and Future Research................33 References................................................35 Appendixes................................................38

    [1] J. Shen, X. Jin, C. Zhou, and C. C. L. Wang, "Gradient based image completion by solving the Poisson equation," Computers & Graphics, 31(1), pp. 119-126, 2007.
    [2] J. Hays and A. A. Efros, "Scene completion using millions of photographs," Commun. ACM, 51(10), pp. 87-94, 2008.
    [3] C. W. Fang and J. J. J. Lien, "Rapid Image Completion System Using Multiresolution Patch-Based Directional and Nondirectional Approaches," IEEE Transactions on Image Processing, 18(12), pp. 2769-2779, 2009.
    [4] M. Bertalmio, L. Vese, G. Sapiro, and S. Osher, "Simultaneous structure and texture image inpainting," IEEE Transactions on Image Processing, 12(8), pp. 882-889, 2003.
    [5] A. Hertzmann, C. E. Jacobs, N. Oliver, B. Curless, and D. H. Salesin, "Image analogies," presented at the Proceedings of the 28th annual conference on Computer graphics and interactive techniques, 2001.
    [6] J. Jia and C.-K. Tang, "Image repairing: robust image synthesis by adaptive ND tensor voting," in IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings. 2003, 2003, pp. I-643-I-650 vol.1.
    [7] W. H. Hsu, L. S. Kennedy, and C. Shih-Fu, "Reranking Methods for Visual Search," Multimedia, IEEE, 14(3), pp. 14-22, 2007.
    [8] X. Li, B. Hu, and R. Du, "Predicting the Parts Weight in Plastic Injection Molding Using Least Squares Support Vector Regression," IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 38(6), pp. 827-833, 2008.
    [9] S. Qiu and T. Lane, "A Framework for Multiple Kernel Support Vector Regression and Its Applications to siRNA Efficacy Prediction," IEEE/ACM Transactions on Computational Biology and Bioinformatics, 6(2), pp. 190-199, 2009.
    [10] P. H. Gosselin and M. Cord, "Active Learning Methods for Interactive Image Retrieval," Image Processing, IEEE Transactions on, 17(7), pp. 1200-1211, 2008.
    [11] S. W. Lee, D. S. Kim, and M. G. Na, "Prediction of DNBR Using Fuzzy Support Vector Regression and Uncertainty Analysis," IEEE Transactions on Nuclear Science, 57(3), pp. 1595-1601, 2010.
    [12] M. Bertalmio, G. Sapiro, V. Caselles, and C. Ballester, "Image inpainting," presented at the Proceedings of the 27th annual conference on Computer graphics and interactive techniques, 2000.
    [13] P. Perez, M. Gangnet, and A. Blake, "Poisson image editing," ACM Trans. Graph., 22(3), pp. 313-318, 2003.
    [14] I. Drori, D. Cohen-Or, and H. Yeshurun, "Fragment-based image completion," ACM Transactions on Graphics, 22(3), pp. 303-312, 2003.
    [15] A. Criminisi, P. Perez, and K. Toyama, "Region filling and object removal by exemplar-based image inpainting," IEEE Transactions on Image Processing, 13(9), pp. 1200-1212, 2004.
    [16] J. Sun, L. Yuan, J. Jia, and H.-Y. Shum, "Image completion with structure propagation," ACM Transactions on Graphics, 24(3), pp. 861-868, 2005.
    [17] N. Komodakis and G. Tziritas, "Image Completion Using Efficient Belief Propagation Via Priority Scheduling and Dynamic Pruning," IEEE Transactions on Image Processing, 16(11), pp. 2649-2661, 2007.
    [18] Z. Xu and J. Sun, "Image Inpainting by Patch Propagation Using Patch Sparsity," IEEE Transactions onImage Processing, 19(5), pp. 1153-1165, 2010.
    [19] C. Cortes and V. Vapnik, "Support-Vector Networks," Mach. Learn., 20(3), pp. 273-297, 1995.
    [20] J. Canny, "A Computational Approach to Edge Detection," IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-8(6), pp. 679-698, 1986.
    [21] A. A. Efros and W. T. Freeman, "Image quilting for texture synthesis and transfer," presented at the Proceedings of the 28th annual conference on Computer graphics and interactive techniques, 2001.
    [22] V. Kwatra, A. Schodl, I. Essa, G. Turk, and A. Bobick, "Graphcut textures: image and video synthesis using graph cuts," ACM Transactions on Graphics, 22(3), pp. 277-286, 2003.
    [23] M. David, "A Database of Human Segmented Natural Images and its Application to Evaluating Segmentation Algorithms and Measuring Ecological Statistics," 2001, pp. 416-416.

    無法下載圖示 校內：2014-06-18公開
    校外：不公開
    電子論文尚未授權公開，紙本請查館藏目錄
    QR CODE