本文選題：HEVC + 環(huán)內(nèi)濾波算法��； 參考：《西安電子科技大學(xué)》2014年碩士論文

【摘要】：隨著人們對視頻更高質(zhì)量不斷追求,高清或超高清視頻處理已成為現(xiàn)代視頻技術(shù)的發(fā)展趨勢。然而,高清視頻的大量應(yīng)用給視頻傳輸與存儲(chǔ)帶來了巨大的挑戰(zhàn)。為獲得更高的壓縮效率,最新一代視頻編碼標(biāo)準(zhǔn)HEVC延續(xù)了H.264標(biāo)準(zhǔn)中混合編碼框架與核心思想,同時(shí)增加了很多新的視頻壓縮技術(shù),例如環(huán)內(nèi)濾波算法相比于H.264有了很大改進(jìn)。環(huán)內(nèi)濾波算法旨在消除編碼過程中預(yù)測、變換和量化等環(huán)節(jié)產(chǎn)生的失真,為運(yùn)動(dòng)補(bǔ)償預(yù)測提供更高質(zhì)量的參考幀,它主要包括去方塊濾波算法和樣值自適應(yīng)偏置算法。本文通過分析HEVC環(huán)內(nèi)濾波算法的基本原理,并在HM12.0軟件環(huán)境中對參考視頻序列進(jìn)行測試對比,發(fā)現(xiàn)針對4:4:4格式和位深度大于10比特的兩種視頻序列,HEVC通常均無法獲得理想的效果,而且存在編碼效率下降的問題�；谶@一問題,本文分別設(shè)計(jì)4:4:4格式色度去方塊濾波優(yōu)化算法和高位深度SAO偏移值自適應(yīng)伸縮算法,可以有效地提升視頻主觀質(zhì)量和編碼效率。1.在4:4:4格式色度去方塊濾波優(yōu)化算法中,為提升4:4:4格式色度去方塊濾波的性能,本文分別設(shè)計(jì)了兩種算法來進(jìn)行色度分量去方塊濾波優(yōu)化。第一種是基于濾波強(qiáng)度去方塊濾波算法,該算法是將亮度去方塊濾波運(yùn)用于色度分量;第二種是基于濾波范圍色度去方塊濾波算法,該算法則是根據(jù)合適的濾波范圍,啟動(dòng)色度濾波算法。上述兩種算法都是充分利用色度分量所包含的信息進(jìn)行濾波,并為色度分量增加獨(dú)立的去方塊濾波控制參數(shù)。進(jìn)一步,利用JCT-VC通用的測試條件對4:4:4格式色度去方塊濾波優(yōu)化算法進(jìn)行驗(yàn)證,實(shí)驗(yàn)結(jié)果表明在RA和LB Main-tier下編碼效率得到了提升:第一種算法提升了0.2/2.3/2.2和0.4/2.1/1.9(Y/U/V BD-rate(%)),第二種算法提升了0.1/0.5/0.6和0.0/0.4/0.5。2.在SAO偏移值自適應(yīng)伸縮算法中,繼續(xù)采用SAO技術(shù)思想,即在LCU內(nèi)部將重建像素劃分為帶狀偏移(Band Offset)和邊緣偏移(Edge Offset)類型,并為它們加上相應(yīng)的偏移值來減少各個(gè)區(qū)域像素失真,不同的是,本算法通過使用合適的伸縮因子對SAO偏移值進(jìn)行自適應(yīng)伸縮變換,其核心思想是分段線性變換。該方法處理靈活,并且易于硬件實(shí)現(xiàn),當(dāng)位深度大于10比特時(shí),SAO偏移值在較低幅值時(shí)有更精確的伸縮,同時(shí)兼顧較大幅值,從而提高了編碼濾波效率。實(shí)驗(yàn)結(jié)果表明,當(dāng)在All-Intra-HE-Main-Tier,IBDI=2和IBDI=4時(shí),編碼效率分別提升了0.3/0.2/0.2(Y/U/V BD-rate(%)),0.3/0.4/0.4(Y/U/V BD-rate(%))。采用該自適應(yīng)伸縮算法能夠更加靈活地適應(yīng)不同特征輸入序列。
[Abstract]:With the continuous pursuit of higher video quality, HD or UHD video processing has become the development trend of modern video technology. However, the application of HD video brings great challenges to video transmission and storage. In order to achieve higher compression efficiency, the latest generation video coding standard HEVC extends the hybrid coding framework and core idea of H.264 standard, and adds a lot of new video compression techniques, such as the improvement of the filtering algorithm in the loop compared with H. 264. In order to eliminate the distortion caused by prediction, transformation and quantization in the coding process, the intra-loop filtering algorithm provides a better reference frame for motion compensation prediction. It mainly includes the de-block filtering algorithm and the sample value adaptive offset algorithm. In this paper, the basic principle of HEVC filter algorithm is analyzed, and the reference video sequences are tested and compared in the HM12.0 software environment. It is found that the two kinds of video sequences with 4:4:4 format and bit depth greater than 10 bits can not get ideal results, and the coding efficiency is reduced. Based on this problem, this paper designs the 4:4:4 format chroma de-block filtering optimization algorithm and the high depth SAO offset adaptive scaling algorithm, which can effectively improve the subjective quality and coding efficiency of video. In order to improve the performance of 4:4:4 format chroma de-block filter, two algorithms are designed to optimize the chrominance component de-block filtering in 4:4:4 format. The first is based on the filter intensity debonding algorithm, which applies the luminance de-block filter to the chrominance component, and the second is based on the filtering range chroma de-block filtering algorithm, which is based on the appropriate filtering range. Start chrominance filtering algorithm. Both of the above algorithms make full use of the information contained in the chrominance component to filter and add independent de-block filter control parameters to the chrominance component. Furthermore, the 4:4:4 chrominance de-block filtering optimization algorithm is verified by using the general test conditions of JCT-VC. The experimental results show that the coding efficiency is improved in RA and LB Main-tier: the first algorithm increases 0.2 / 2.3 / 2.2 and 0.4/2.1/1.9(Y/U/V BD-rate2, and the second improves 0.1 / 0.5 / 0.6 and 0.00.4 / 0.5.2. In the adaptive scaling algorithm of SAO offset, the idea of SAO technology is adopted, that is, the reconstructed pixels are divided into banded offset sets and edge offset edge offsets in LCU, and the corresponding offset values are added to them to reduce the pixel distortion in each region. The main idea of this algorithm is piecewise linear transformation. The method is flexible in processing and easy to be implemented in hardware. When the bit depth is more than 10 bits, the Sao offset value has a more accurate scaling when the amplitude is lower, and at the same time, it takes into account the larger amplitude, thus improving the efficiency of coding filtering. The experimental results show that at All-Intra-HE-Main-Tiern IBDI2 and IBDI2 = 4, the coding efficiency is improved by 0.3 / 0.4 / 0.4 / 0.4Y / U / V BD-rate2, respectively. The adaptive scaling algorithm can adapt to different feature input sequences more flexibly.
【學(xué)位授予單位】：西安電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TN919.81;TN713

【參考文獻(xiàn)】

相關(guān)碩士學(xué)位論文 前1條

1 盛希;基于HEVC視頻編碼標(biāo)準(zhǔn)的后處理技術(shù)的研究[D];北京工業(yè)大學(xué);2013年

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本文編號：1828494