自適性可變碼率之預測性移動向量量化器設計之研究

Adaptive Entropy-Constrained Predictive Motion Vector Quantization

王俊偉(Chun-Wei Wang)

指導教授 ： 黃文吉

中原大學/工學院/電機工程研究所/碩士(2001年)

https://doi.org/10.6840/cycu200100334

摘要

移動向量量化器在視訊編碼中是個相當有效的法則，不過雖然移動向量量化器擁有較低的計算複雜度與碼率，但卻有以下兩個主要的缺點：其中一個是它需要花費額外的時間在碼簿訓練上，另外一個則是它無法控制指標碼率。為了克服這兩個缺點，於是我們提出「自適性可變碼率之預測性移動向量量化器」。

接下來我們可以將這個法則分為三個部分來分析它。第一個是「自適性」，這部份的特色是在於本法則可以隨著編碼過程而自行更新碼簿，因此它是可以被應用在即時編碼上的。第二個部分「熵編碼」則讓我們可以個別獨立指定碼率與碼簿大小，由於這部份中我們使用了算術編碼，因此本法則比移動向量量化器節省了更多的指標碼率。最後一個部份則是「預測性」，它的特色在於集中碼字指標的使用率，因此它可以使算術編碼執行的更有效率、得到更低的碼率。

模擬結果顯示本法則在碼率相同的情形下，其影像品質的確優於其它法則，尤其在低碼率的時候，本法則的領先會更明顯。

關鍵字

即時編碼 ； 視訊編碼 ； 自適性 ； 熵編碼 ； 預測性

並列摘要

Motion vector quantization (MVQ) is an effective algorithm for video coding. It has low computational complexity for block matching and low average rate for motion vector delivery. However, the algorithm has two major shortcomings. One is MVQ needs high computational complexity for codebook training, the other is MVQ can’t control index rate. To overcome these two defects, this thesis presents a novel algorithm named “Adaptive Entropy-Constrained Predictive Motion Vector Quantization” (AECPMVQ).

This AECPMVQ algorithm can be separated into three parts. The first is “Adaptive”. The property of this part is that this algorithm can update the codebook online. So AECPMVQ is suitable for real-time coding. The second part, “Entropy-Constrained”, allows index rate and codebook size to be pre-specified independently. Because arithmetic coding is used in this part, AECPMVQ can save more index rate than MVQ. The finial one is “Predictive”. It centralizes the utilization of indices. Hence, the efficiency of arithmetic coding can be further enhanced.

The simulation results show that AECPMVQ has better rate- distortion performance than other algorithms. Especially in low-rate coding, the leading of performance of AECPMVQ will be more obvious.

並列關鍵字

Adaptive ； Real-Time Coding ； Video Coding ； Entropy-Constrained ； Predictive

參考文獻

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