視訊壓縮技術為主的大型時變容積多層次解析度顯像法

Abstract

我們提出一個結合多層次解析度階層表示法(multi-resolution hierarchical representation)與影片式壓縮 (video-based compression)的新架構，以管理與顯像大型時變容積資料。此方法首先在預先處理的步驟中對每個時間點的資料建構出多層次解析度的八元樹階層架構，之後再對這些八元樹的節點實施運動補償式預測(motion-compensation-based prediction)的壓縮法。在顯像時這些資料將被即時的解壓縮還原並以硬體貼圖繪畫的方式來顯像。相較於傳統上使用階層式小波轉換的方法，我們的方法移除了階層式解壓縮的相依性並且使得在時間軸上的解壓縮還原更有效率。此系統提供了使用者控制空間興趣區域(spatial region-of-interest)以調整空間上的多層細緻程度(level-of-detail)選擇；並提供控制時間興趣區域(temporal region-of-interest)以只選擇出部分區域進行播放，在一個合適的興趣區域控制下，我們的系統可以到達互動速度的播放，這樣的結果提供了使用者可以觀察到大型時變容積在時間上的動態變化。

We present a new framework that combines the multi-resolution hierarchical representation with video-based compression to manage and render large scale time-varying data. In preprocessing step, the proposed method firstly construct a multi-resolution octree hierarchy for each individual time step, and then apply motion-compensation-based prediction to compress these octree nodes. During rendering, the data is decompressed on-the-fly and rendered using hardware texture mapping. The proposed approach breaks the hierarchical decompression dependency in the conventional hierarchical wavelet representation methods, and allows a more efficient reconstruction of data along time axis. The system provide the user spatial region-of-interest (ROI) to adjust the spatial level-of-detail selection, and provide the user temporal ROI to choose only a sub-region for playback. With a suitable control of both ROI, our system can reach an interactive playback. This provides the user to observe the dynamic change of the large time-varying data set.