臺灣博碩士論文加值系統

近年來隨著立體顯示器的技術逐漸成熟，從初期的3D電影，逐漸轉成掌上型遊戲機與智慧型手機等手持裝置，透過立體顯示器播放立體影像視訊可提供使用者更加真實的臨場感受。然而，立體視訊的資料量相較於平面視訊來的更為龐大，為了解決這個問題，立體視訊編碼標準相繼被提出，可以藉由視角之間的高度相似性消除冗餘的部分，大幅降低所需傳輸的資料量。
傳統立體編碼技術在設計的過程並沒有探討立體影像的失真可能引起的雙眼現象，如雙眼融合、雙眼競爭、雙眼壓迫等，所以合乎人眼的立體視訊編碼系統變得十分重要。在雙眼觀賞立體影像時，可能會產生某些視覺現象，如雙眼融合、雙眼競爭、雙眼壓迫等，為了克服上述壓縮立體視訊可能產生的問題，除了調整編碼策略之外，影像的品質評估也要有所改變，立體影像的實際品質體驗牽涉到的不單只是2D影像的品質，還有某些立體影像才會產生的問題，立體影像的品質評估必須都要顧慮到才行。
本論文根據BJND(Binocular Just Noticeable Distortion)分別提出了立體影像的壓縮策略與品質評估演算法，近期所提出的BJND被認為可以用於衡量失真的立體影像可能產生的雙眼效應，加上影像中的每個區域引起的雙眼效應的程度不盡相同，所以我們利用上述性質，依據BJND來決定該區域是否有過多的視覺冗餘，消除冗餘以提升編碼效益同時又能夠維持視覺上的品質。此外也利用BJND設計出接近主觀實驗結果的客觀品質評估演算法，不只用於評斷無失真的情況，也可以用於評估一般編碼後立體影像的品質。

3D entertainment device has growing recently, from 3D films to smart phones, stereoscopic video can bring users rights in the scene feeling. However, stereoscopic videos’ data are much larger than 2D’s. To solve this problem, lots of stereoscopic video standards are proposed in succession. Most of them use highly similarity between base view and non base view video to improve coding efficiency.
Traditional stereoscopic video coding scheme didn’t consider binocular perceptions caused by the distortion of base view video and non-base view video, respectively. Binocular perceptions includes binocular fusion, binocular rivalry and binocular suppression. Above all, stereoscopic video coding which considers binocular perceptions become more important. To solve the problem of stereoscopic video coding, not only coding scheme has to change, but also objective stereo video quality assessment. The quality of experience of stereoscopic video contains both binocular perceptions and the quality of 2D videos.
This paper proposed a stereoscopic image coding scheme and an objective image quality assessment both based on BJND (Binocular Just Noticeable Distortion).，BJND, which was proposed recently, could use to measure binocular perceptions occurred by distorted stereoscopic images. With BJND, we can decide there are binocular redundancies in stereo images. Through erase those redundancies, coding efficiency will be improved and maintain quality of experience at same time. And we also design an objective quality assessment algorithm based on BJND which will has highly correlation between subjective quality and proposed method.

第一章 緒論
1.1 研究動機
1.2 論文架構
第二章 基於人眼視覺的立體壓縮架構介紹
2.1 立體視訊編碼架構介紹
2.1.1 立體視訊編碼(Stereoscopic Video Coding)
2.1.2 非對稱立體視訊編碼
2.1.3 基於HEVC的立體視訊編碼標準
2.2 合乎人眼視覺的立體壓縮
2.2.1 雙眼視覺特徵分析
2.2.2 相關文獻介紹
第三章 客觀品質評估介紹
3.1 2D影像的品質評估
3.1.1 全參考源品質評估演算法
3.1.2 無參考源與部分參考源品質評估演算法
3.2 立體影像的品質評估
3.2.1 相關文獻探討
第四章 提出方法
4.1 基於BJND的立體影像壓縮
4.1.1 基於雙眼效應對立體影像的分區
4.1.2 立體影像編碼的QP決策
4.2 基於BJND的立體影像品質評估
4.2.1 以雙眼失真和特性為基礎產生BJND
第五章 實驗結果與討論
5.1 立體影像壓縮與主客觀品質評估實驗環境
5.1.1立體影像實驗環境
5.1.2客觀品質評估實驗相關設定
5.1.3主觀品質評估實驗相關設定
5.2 實驗結果與數據分析
5.2.1 提出的編碼策略之實驗結果與數據分析
5.2.2 提出的客觀品質評估之實驗結果與數據分析
第六章 結論與未來展望
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