以小波轉換為基礎的可調式視壓縮之流量控制機制

Abstract

在以小波為基礎的嵌入式的圖像或影像壓縮過程中，可調變的特性和壓縮效能之間的平衡點可由階層式的封裝，即對於不同階層給予特定的壓縮比的方式達到部份的最佳化。這個過程稱為流量控制機制。一般典型的流量控制機制可歸類為兩個重要的過程，一是壓縮大小和失真度之間的最佳化問題，另一為簡單但收斂速度慢的搜尋方法。而在此篇論文中所提出的提案目標，為一個以建立模組化的方式達成高度效能的流量控制系統。此演算法的基本精神為以動態分析的過程，精確地建立圖像或影像的壓縮大小和失真度之間的關係。實驗為在一套嵌入式可調變的壓縮、解壓縮的方法中實作此演算法，結果顯示搜尋所須的時間明顯減少，且所取得的壓縮內容仍接近最佳化的效能。此技術可應用至各類以小波為基礎的嵌入式圖像或影像壓縮過程，如JPEG2000及以MCTF架構為基礎的可調變式影像壓縮方法。

In wavelet-based embedded coding for still images and/or videos, a trade-off between scalability and coding efficiency is achieved via layered-packetization of the embedded bitstreams optimized for several target operating bitrate points. This process is called rate allocation (tier-2 coding). The typical rate allocation mechanism is formulated as a rate-distortion optimization problem and a simple searching method with slow convergence rate is used. In this paper, a highly efficient model-based rate allocation mechanism is proposed. The algorithm is based on adaptive analysis of the relationship between source-coding rate and distortion of the image/video data. Experiments conducted on a scalable video codec show that the proposed technique greatly reduces the search time for the optimal solution. The techniques can be applied to various wavelet-based embedded image and video coding schemes, such as the JPEG2000 codec and the MCTF-based scalable video codecs.