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研究生： 蔡欣蓓
Shin-Bei Tsai
論文名稱： 利用解析度與紋理一致之植基於韋納濾波結合回歸的影像放大法應用於非對稱式解析度立體視訊編碼
Efficient Wiener Filter- and Regression-based Upsampling for Asymmetric Resolution Stereoscopic Video Coding with Resolution and Texture Consistency
指導教授： 鍾國亮
Kuo-Liang Chung
口試委員: 貝蘇章
Soo-Chang Pei
邱志義
Chih-Yi Chiu
陳建中
Jiann-Jone Chen
黃元欣
Yuan-Shin Hwang
學位類別： 碩士
Master
系所名稱： 電資學院 - 資訊工程系
Department of Computer Science and Information Engineering
論文出版年： 2017
畢業學年度： 105
語文別： 英文
論文頁數： 28
中文關鍵詞： 非對稱解析度立體影像編碼 、抽樣 、線性回歸 、品質計算 、放大 、韋納濾波
外文關鍵詞： Asymmetric resolution stereoscopic video coding, Downsampling, Linear Regression, Quality Assessment, Upsampling, Wiener Filter
相關次數： 點閱：232  下載：1 
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    • 在非對稱式解析度立體視訊壓縮(ARSVC) 中，一部立體影片包含原始解析度的左視圖影片以及縮小的右視圖影片，以達到減少編碼端位元率的效果。通常每個被縮小的影像會是原始大小的四分之一，然後在解碼端放大回原始大小以用於3-D 檢視。本篇論文中，我們針對ARSVC 提出了有效的放大方法。本篇方法的主要貢獻為以下三點：(1) 在基於韋納濾波器的內插法中考慮解析度一致與紋理一致以改善放大的準確度。(2) 在幀間預測利用線性回歸以增加放大的準確度。(3) 提出了基於重建誤差的方法結合以上兩點的放大結果以最佳化最終的放大影像。根據七部測試影片，實驗結果顯示，與其他優秀的放大方法相比，本篇的方法在全彩的峰值訊噪比(CPSNR)、結構相似度(SSIM)、品質-位元率權衡、以及視覺效果皆有顯著的提升。

    In asymmetric resolution stereoscopic video coding (ARSVC), a stereoscopic video consists of one full-sized left-view video sequence and synchronized quarter-sized right-view video sequence, achieving bitrate reduction effect to the encoder. Priori to displaying the 3Don the screen, it is necessary to upsample the decoded downsampled right-view video sequence by the decoder. In this thesis, we propose a novel and effective upsampling method for ARSVC and the contributions of the proposed method are threefold: (1) employing the resolution and texture consistency consideration into the conventional Wiener filter-based interpolation scheme to enhance the upsampling accuracy in the spatial domain, (2) employing the linear regression technique into the interview prediction scheme to increase the upsampling accuracy in the interview domain, (3) proposing an adaptive fusion based approach to integrate the improved Wiener filter-based interpolation scheme and the newly proposed regression-based prediction scheme to maximize the quality improvement of the upsampled images. Based on seven typical test stereoscopic video sequences, experimental results demonstrated that in terms of peak signal-to-ratio (PSNR), structural similarity (SSIM), motion-based video integrity evaluation (MOVIE), and the quality-bitrate trade-off, the proposed upsampling method achieves substantial quality improvement when compared with the state-of-the-art upsampling methods for ARSVC.

    指導教授推薦書 i 論文口試委員審定書 ii 中文摘要 iii Abstract in English iv 誌謝 v Contents vi List of Figures viii List of Tables ix 1 Introduction 1 1.1 Overview of Existing WF-related Upsampling Methods and Weaknesses 3 1.2 Motivation and Contribution 7 2 The Proposed Resolution Joint Texture Consistency- and WF-based Upsampling Method 8 3 The Proposed Linear Regression-based Interpolation Scheme in Interview Domain 14 3.1 The proposed linear regression-based interview prediction (LRIP) 14 3.2 Proposed intra RTCWF- and inter LRIP-based upsampling 17 4 Experimental Results 20 4.1 CPSNR Quality Merit 20 4.2 SSIM Quality Merit 21 4.3 RD Curve 22 4.4 Visual Effect Merit 22 5 Conclusion 25 Reference 26

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