針對可調視訊編碼粗略可調性之模式相依的失真解析模型

Abstract

在失真模型的研究中，位元和失真模型在加速決定參數演算法扮演很重要的角色。大多數的模型適用於畫面層級的單層視訊壓縮結構，僅有少數模型可以解釋可調式視訊編碼（H.264/SVC）的失真行為，而更進一步針對可調視訊編碼中不同的區塊切割模式分析其失真關係的研究更是缺乏，因此我們推導出針對可調視訊編碼粗略可調性之模式相依的失真解析模型，對於失真行為加以解析。此模型同時考量區塊分割、層間預測、轉化效應與量化效應，並透過以相鄰畫面及相鄰區塊的失真資訊調適模型參數，達到對於空間和時間區塊內容變異的適應性。為了讓此模型更適合應用，我們根據一些實驗發現簡化模型方程式，以降低模型的複雜度。最後，由實驗結果應證我們的模型在區塊及畫面層級估測失真皆有相當的準確性。

In real-time video encoding applications, rate and distortion models play an important role in speeding up parameter decision. Most of the rate and distortion models are built for the single-layer video coding in the frame level. Only few models were developed to estimate the rate and distortion for multiple-layer video coding, not to mention models that are able to do mode-dependent estimation in the MB level. This thesis presents a mode-dependent distortion model for H.264/SVC coarse grain SNR scalability. It estimates the base-layer and enhancement-layer’s distortions with particular consideration of their prediction modes and inter-layer residual prediction. Based on a parametric signal model, the variances of the transformed prediction residual at both layers are first formulated analytically and approximated empirically. The results are then incorporated into the assumption that the transform coefficients are distributed according to the Laplacian distribution to obtain the final distortion estimates. Experimental results confirm its fairly good ability to predict the actual distortions in both the frame and macroblock levels.