- 學位論文
低複雜度空間紋理量測之高效率視訊編碼單位大小和模式快速決策方法
A Low Complexity Spatial Texture Measurement for Fast CU Size Decision and Mode Decision in HEVC
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摘要
高效率視訊編碼是新一代的視訊壓縮標準.因為大量的新模式和四元樹的編碼單位架構,它能提供比前一代的標準大約兩倍的編碼效率,但是同時也使得計算複雜度大幅度上升。所以如何在幾乎不影響編碼效率的前提下,去減少計算複雜度是必須的。在我的論文中,根據影片內容複雜程度與否的特性在影格內編碼和影格間編碼提出了一個快速模式選擇方法。我首先分析了影片的內容複雜度跟模式選擇之間的關係,接著利用這個關係去進一步的加快編碼的速度。 在編碼效率只有微小下降的情況下,我所以提出的方法在影格內編碼可以節省最高53.4%,平均46.5%的編碼時間;在影格間編碼方面,我的方法可以節省最高38.6%, 平均31.2%的編碼時間。
並列摘要
Abstract— High Efficiency Video Coding (HEVC) [1] is a new video compression standard which reduces bitrate by half compared with H.264/AVC. But the computational complexity increases due to the quadtree based structure, which contributes to significant coding efficient improvement. As a result, reducing this complexity and maintaining negligible loss in bitrate and peak signal-to-noise (PSNR) simultaneously is a must. In this work, we design a fast mode decision scheme for inter and intra prediction in HEVC based on the texture complexity. We show that the relation between texture complexity and mode decision, then use this relation to speed up the encoding process. The proposed scheme provides a decrease of up to 53.4% and by averagely 46.5% for intra coding, with negligible loss in bitrate and PSNR. On the other hand, the proposed scheme for inter coding also provides a decrease of up to 38.6% and by averagely 31.2% with negligible loss in bitrate and PSNR.
參考文獻
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