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Algorithm and Architecture Design for 2D and 3D Video Signal Processing
|關鍵字:||2D轉3D;2D to 3D;視野合成;深度圖估測;View Synthesis;Depth Map Estimation||出版社:||電機工程學系所||引用:|| ITU-T and ISO/IEC JTC 1, Advanced video coding for generic audiovisual services, ITU-T Recommendation H.264 and ISO/IEC 14496-10 (MPEG-4 AVC), 2010.  ITU-T and ISO/IEC JTC 1, Generic coding of moving pictures and associated audio informationVPart 2: Video, ITU-T Recommendation H.262 and ISO/IEC 13818-2 (MPEG-2 Video), 1994.  A. Vetro, P. Pandit, H. Kimata, A. Smolic, and Y.-K. Wang, Joint draft 8 of multiview video coding, Hannover, Germany, Joint Video Team (JVT) Doc. JVT-AB204, Jul. 2008.  K. Müller, P. Merkle, and T.Wiegand, “3D video representation using depth maps,” Proc. IEEE, 2011.  C. Fehn, “Depth-image-based rendering (DIBR), compression and transmission for a new approach on 3D-TVm,” in Proc. SPIE Conf. Stereoscopic Displays Virtual Reality Syst. XI, San Jose, CA, USA, Jan. 2004, pp. 93–104.  A. Vetro, S. Yea, and A. 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Srinivasan, “Design and FPGA Implementation of a Video Scalar with on-chip reduced memory utilization,” in Proc. IEEE Euromicro Symposium on Digital System Design, pp. 206-213, Sep. 2003.||摘要:||
在近年來，3D顯示技術進步相當快速且吸引更多的注意。由於目前市面上還存在大量的2D視訊資料，因此2D轉3D視訊的轉換扮演相當重要的角色在3D內容的產品上。在本篇論文裡提出了一混合型的深度圖估測演算法並應用於2D轉3D視訊的轉換。它採用了三種深度線索來當作深度圖的估測: 移動物體的資訊、線性透視和材質的特性。深度影像的展示(DIBR)技術能夠結合深度圖資訊和原本的2D影像資訊，並同時視野合成 (view synthesis)出3D的左視圖和右視圖，此外亦提出了一個高品質的視野合成(view synthesis)演算法和架構可應用於2D轉3D視訊的轉換。此方法包含兩個部份: 3D影像彎曲(3D Image Warping)和影像補點(hole-filling)，在3D影像彎曲部分把2D相機影像平面經過座標轉換到3D座標平面，然而此方法會把影像的整數點映設到不規則的點上，進而產生空洞(occlusion)和重覆點的問題，此論文提出了一補點的演算法，可增加PSNR大約0.2~1.5dB相對於其他演算法，我們採用軟硬體共整合的方式來實現它的硬體並實現於FPGA平台。
在多媒體系統，目前有相當多的標準如MPEG-1/2/4, VC-1和H.264/AVC。它們都有一個反離散餘弦(IDCT)轉換。為了能支援多規格的標準並有更低的成本，它是需要設計一個可重組化的IDCT架構對於各種不同的視訊規格並使用同一個硬體架構就可支援多種規格，本論文提出的IDCT架構可同時支援MPEG-1/2/4, VC-1和H.264/AVC並可支援4種矩陣型式的轉換: 8x8, 8x4, 4x8和4x4轉換。這個架構都優點是不需要要乘法器和唯讀記憶體電路，它只需要加法器和移位器電路就可實現此架構。在本論文的最後部分提出了一可調整視窗並具有影像增強的六階濾波器演算法，此演算法可用於觸控式的嵌入式平台並且容易實現，此演算法具有低運算複雜度而且可保有影像的品質並可應用於各種消費型電子產品的數位顯示器上。
In recent years, 3D display technology has been receiving increasingly more attention. Due to the enormous number of existing 2D videos, 2D-to-3D video conversion plays an important role in 3D content production. In this thesis, we propose a hybrid depth-generation algorithm for 2D-to-3D conversion in 3D displays. We choose three depth cues for depth estimation: motion information, linear perspective, and texture characteristics. Depth-Image-Based Rendering (DIBR) can combine the depth map information with original 2D images, and simultaneously output 3D rendering for the left and right eyes. Moreover, we propose a high quality view synthesis algorithm and architecture for 2D-to-3D conversion. The proposed view synthesis algorithm consists of two parts: 3D image warping and inpainting (hole filling). 3D image warping transforms a 2D camera image plane to a 3D coordinate plane. However the integer grid points of the reference are warped to irregularly spaced points in the virtual view, resulting in occlusion problems. Thus inpainting is needed to fix the virtual images. The proposed algorithm shows an improved PSNR gain of 0.2~1.5dB. We adopt hardware/software co-design to accomplish the proposed view synthesis algorithm. For this we implemented the image inpainting on a FPGA device and the remaining algorithm in software.
In multimedia system, there are many standards such as MPEG-1/2/4, VC-1 and H.264, which all have the IDCT transform. In order to support multi-standard and lower cost, it is necessary to design a reconfigurable IDCT architecture for video decoder to decode various video standards. The proposed IDCT architecture can support various video standards such as VC-1, MPEG-1/2/4 and H.264 AVC. It can sustain four transform types, 8x8, 8x4, 4x8 and 4x4 transform. The advantages of the proposed architecture are that this architecture does not require multipliers and ROM. It only needs adders and shifters. Finally, we proposed scalable view window with quality enhancement for touchable displays. The algorithm is easy for implementation, and its computational complexity is acceptable on an embedded system. Its computational complexity is not only low, but it can also get good image quality. This algorithm is suitable for various digital displays applications like digital picture frame.
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