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研究生:陳彥宏
研究生(外文):Yan-HongChen
論文名稱:應用於三維電視之擴張視差圖以保存邊界資訊
論文名稱(外文):Using Expanding Parallax Map to Preserve Edge Information for 3DTV
指導教授:賴源泰
指導教授(外文):Yen-Tai Lai
學位類別:碩士
校院名稱:國立成功大學
系所名稱:電機工程學系碩博士班
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:58
中文關鍵詞:DIBR視差圖擴張虛擬視角影像
外文關鍵詞:DIBRparallax map expandingvirtual-view image
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近幾年來,立體影像的呈現和相關的應用越來越受到重視。但傳統的立體影像必須將所有的視角影像傳送和儲存,這勢必得花大量的傳送頻寬和儲存裝置。
Depth Image Based Rending (DIBR)是將一張已知的視角影像和對應的深度圖來產生給觀察者不同虛擬視角的影像。DIBR是利用位移像素(shift pixel)來產生新的視角影像,但使用此演算法在深度變化劇烈的地方會產生洞口(hole),這些洞口會造成影像品質的降低。另一個問題是深度圖的品質太差,深度圖前後景邊緣與對應的視角影像前後景邊緣不一致,像素經過位移後,導致虛擬視角影像的前景物體邊緣不正確,降低了影像的品質。
本論文改善上述兩缺點,根據分離(Disconnection)和損失(Loss)的邊去做不一樣的處理演算法。因為分離的邊位於前景和背景的交接處,此區域也是大尺寸洞口產生的地方,為了保存前景的邊緣資訊和有效填補背景缺口,將前景的視差圖擴張,所以一部分靠近前景的背景像素移動到前景邊緣,造成小尺寸和中尺寸的洞口,小尺寸用水平內插法 (Horizontal Interpolation)做填補,中尺寸用水平外插法 (Horizontal Extrapolation)做填補。損失的邊同樣的利用前景的視差圖擴張,即可把損失的邊問題解決。

In recent years, three dimensional and related applications are getting more and more attention. The traditional three dimensional image must be transmit and store images of all view angles.
Depth Image Based Rending (DIBR) generate virtual views from one know color image and associated per-pixel depth information. DIBR generate new virtual-view images by shift pixel, but it will generate new holes in sharp depth transition of the depth image. The holes seriously degrade visual quality of synthesized virtual images. Another problem is the poor quality of the depth map. The edge of foreground in the depth image and the color image are inconsistent. After shifting the pixel, the edge of foreground in the virtual-view image is incorrect. It will degrade the virtual-view image quality.
This thesis improves the above two problems. It processes different algorithm according to the edge of disconnection and loss. Because the edge of separation is at the junction of foreground and background, the region is also large size hole to produce. In order to save the information of foreground edges and effectively fill the hole of background, I expand the parallax value of foreground edge. So parts of background near foreground are moved to close the foreground edge. It will produce small and medium size holes, small size holes will fill by horizontal interpolation and medium size holes will fill by horizontal extrapolation. Loss edge uses the same method that expanded parallax value of foreground, and then the loss problem will be solved.

Chapter 1 Introduction 1
1.1 Overview of stereo video generation 1
1.2 Motivation 3
1.3 Thesis Organization 5

Chapter 2 Background 6
2.1 Overview of DIBR 6
2.1.1 Depth Map Capture System 7
2.1.2 Zero-Parallax Setting 8
2.1.3 Shift-sensor algorithm 9
2.1.4 3D Image Warping 10
2.1.5 Problem of DIBR: Disocclusion (Hole) 11
2.1.6 Problem of DIBR: Disconnection and Loss 12
2.2 Previous works on Hole-filling 14
2.2.1 Constant color filling 14
2.2.2 Horizontal interpolation 15
2.2.3 Horizontal extrapolation 16
2.3 Previous works on Pre-processing 17
2.3.1 Symmetrical Gaussian filter 18
2.3.2 Asymmetrical Gaussian filter 19

Chapter 3 Proposed adaptive expanding method 21
3.1 Screen Parallax-Map generation 21
3.2 Discussion on Parallax-Map 23
3.2.1 Disocclusion Areas (Hole) 24
3.2.2 Disconnection edge 26
3.2.3 Loss edge 27
3.3 Proposed algorithm for edge information 28
3.3.1 Edge detection 29
3.3.2 Function for modification of parallax value 30
3.3.3 Proposed DIBR flowchart 33

Chapter 4 Experimental Results 36
4.1 Test Video Sequences and Parameter Selection 36
4.2 Subjective Evaluation 37
4.3 Objective PSNR Evaluation 52

Chapter 5 Conclusions 55

REFERENCES 56

[1]C. Fehn, “Depth-image-based-rendering (DIBR), compression and transmission for a new approach on 3D-TV, in Proc. International Society for Optical Engineering Conf. Stereoscopic Displays and Virtual Reality Systems XI, San Jose, CA, Jan. 2004, vol. 5291, pp.93–104.
[2]C. Fehn, K. Hopf, and Q. Quante, “Key technologies for an advanced 3D-TV system, in Proc. International Society for Optical Engineering Conf. Three-Dimensional TV, Video and Display III, Philadelphia, PA, Oct. 2004, pp. 66–80.
[3]Y. C. Fan and T. C. Chi, “The novel non-hole-filling approach of depth image based rendering, 3DTV, pp. 325–328, May 2008.
[4]L. McMillan, An Image-Based Approach to Three-Dimensional Computer Graphics. PhD thesis, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA, 1997.
[5]W. R. Mark, Post-Rendering 3D Image Warping: Visibility, Reconstruction, and Performance for Depth-Image Warping. PhD thesis, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA, Apr. 1999.
[6]Wikipedia. [Online]. Available: http://en.wikipedia.org/wiki/3D_scanner.
[7]Y. L. Chang, C. Y. Chen, S. F. Lin, and L. G. Chen, “Depth map generation for 2D-to-3D conversion by short-term motion assisted color segmentation, in Proc. Int. Conf. Multimedia and Expo, 2007, pp.1958–1961.
[8]K. C. Liu, Q. Wu, W. C. Chen, C. F. Wu, F. C. Jan, and T. Chen, “Example-based depth generation from single image for 3D content, in Proc. 3DTV Conf.: The True Vision—Capture, Transmission and Display of 3D Video, May 2008, pp. 333–336.
[9]A. Woods, T. Docherty, and R. Koch, “Image Distortions in Stereoscopic Video Systems, in Proc. of SPIE Stereoscopic Displays and Applications ’93, pp. 36–48, (San Jose, CA, USA), Feb. 1993.
[10]W. A. IJsselsteijn, H. de Ridder, and J. Vliegen, “Stereoscopic Filming Parameters and Display Duration on the Subjective Assessment of Eye Strain, in Proc. of SPIE Stereoscopic Displays and Virtual Reality Systems ’00, pp. 12–22, (San Jose, CA, USA), Apr. 2000.
[11]L. Zhang and W. J. Tam, “Stereoscopic image generation based on depth images for 3DTV, IEEE Trans. Broadcast., vol. 51, pp. 191–199, Jun. 2005.
[12]C. Vzquez, W. J. Tam, and F. Speranza, “Stereoscopic Imaging: Filling Disoccluded Areas in Depth Image-Based Rendering, Proceedings of SPIE, Vol.6392, 2006.
[13]P.-J. Lee and Effendi, “Nongeometric distortion smoothing approach for depth map preprocessing, IEEE Trans. Multimedia, vol. 13, no. 2, pp. 246-254, Apr. 2011.
[14]T.C. Lin, H.C. Huang, and Yueh-min Huang, “Preserving depth resolution of synthesized images using parallax-map-based DIBR for 3D-TV, IEEE Trans. On Consumer Electronics, Vol.56, No.2, May.2010.
[15]A. Bourge and C. Fehn, ISO/IEC CD 23002-3 Auxiliary Video Data Representation, ISO/IEC JTC 1/SC 29/WG 11/N8038, 2006.
[16]MSR 3D Video Download [Online]. Available: http://research.microsoft.com/en-us/um/people/sbkang/3dvideodownload/
[17]W. J. Tam, G. Alain, L. Zhang, T. Martin, and R. Renaud, “Smoothing depth maps for improved stereoscopic image quality, in Proc. International Society for Optical Engineering Conf. Three-Dimensional TV, Video, and Display III, Philadelphia, USA, Oct. 2004, vol. 5599, pp.162–172.
[18]C.L. Zitnick, S.B. Kang, M. Uyttendaele, S. Winder and R. Szeliski, high-quality video view interpolation using a layered representation, ACM SIGGRAPH and ACM Trans. on Graphics, Los Angeles, CA, pp. 600-608, Aug. 2004.

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