本文選題：無(wú)參考視頻質(zhì)量評(píng)估　切入點(diǎn)：網(wǎng)絡(luò)視頻　出處：《西安電子科技大學(xué)》2014年博士論文　論文類型：學(xué)位論文

【摘要】：IP(Internet Protocol)網(wǎng)絡(luò)和移動(dòng)通信的迅猛發(fā)展,使得視頻信息在IP網(wǎng)絡(luò)和移動(dòng)通信網(wǎng)絡(luò)中的處理和傳輸受到越來(lái)越多的關(guān)注。如何對(duì)視頻質(zhì)量進(jìn)行準(zhǔn)確有效的評(píng)估,已成為在視頻壓縮、處理以及傳輸?shù)妊芯款I(lǐng)域迫切需要解決的問(wèn)題之一網(wǎng)絡(luò)丟包是導(dǎo)致視頻質(zhì)量下降的主要原因之一,論文針對(duì)網(wǎng)絡(luò)丟包的無(wú)參考視頻質(zhì)量評(píng)估進(jìn)行了深入的研究,主要研究工作著眼于提高客觀頻質(zhì)量評(píng)估的實(shí)時(shí)性和有效性。分別從H.264/AVC編碼新特性、丟幀類型、丟包率、包丟失集中度和人眼視覺容忍特性對(duì)視頻質(zhì)量的影響等方面進(jìn)行了深入的研究。主要研究?jī)?nèi)容包括： 1. H.264/AVC網(wǎng)絡(luò)視頻的丟包失真評(píng)估。針對(duì)由H.264/AVC所使用的新編解碼技術(shù)引起信道誤碼、空時(shí)域誤碼傳播、空時(shí)域誤碼掩蓋及去方塊濾波對(duì)視頻質(zhì)量的影響,給出了一種計(jì)算網(wǎng)絡(luò)視頻丟包失真MSE(Mean Square Error)的無(wú)參考視頻質(zhì)量評(píng)估算法,該算法充分考慮了空時(shí)域誤碼傳播、誤碼掩蓋算法和編碼器特性對(duì)視頻質(zhì)量的影響,并且計(jì)算復(fù)雜度低,可以進(jìn)行實(shí)時(shí)網(wǎng)絡(luò)視頻質(zhì)量監(jiān)控。實(shí)驗(yàn)結(jié)果表明,使用該算法能夠較準(zhǔn)確地反映視頻質(zhì)量MSE。并結(jié)合視頻內(nèi)容空時(shí)域特性,對(duì)全參考視頻質(zhì)量評(píng)估方法SSIM(Structural Similarity Metric)進(jìn)行改進(jìn),給出一種基于SSIM的半?yún)⒖家曨l質(zhì)量評(píng)估算法。實(shí)驗(yàn)結(jié)果表明,使用該算法得到的客觀視頻質(zhì)量能夠較準(zhǔn)確地反映視頻的主觀質(zhì)量。 2.考慮丟幀類型的無(wú)參考視頻質(zhì)量評(píng)估模型。針對(duì)網(wǎng)絡(luò)視頻質(zhì)量評(píng)估需要滿足實(shí)時(shí)性和低資源開銷等要求,給出一種無(wú)參考網(wǎng)絡(luò)視頻質(zhì)量評(píng)估模型。該模型考慮了丟失不同幀類型、視頻內(nèi)容和丟包影響單幀時(shí)人眼視覺容忍特性對(duì)視頻質(zhì)量的影響,且不需要對(duì)視頻完全解碼,具有資源開銷小、實(shí)時(shí)性好的特點(diǎn),適合對(duì)實(shí)時(shí)傳輸?shù)囊曨l流進(jìn)行質(zhì)量評(píng)估。實(shí)驗(yàn)結(jié)果表明,使用該視頻質(zhì)量評(píng)估模型測(cè)得的視頻丟包失真質(zhì)量評(píng)分與其主觀質(zhì)量評(píng)分具有很好的一致性,相比于國(guó)際標(biāo)準(zhǔn)G.1070中的丟包視頻質(zhì)量評(píng)價(jià)模型,該模型與主觀質(zhì)量評(píng)價(jià)的相關(guān)性平均提高了6.96%。 3.考慮包丟失特性的無(wú)參考網(wǎng)絡(luò)視頻質(zhì)量評(píng)估模型。針對(duì)相同包丟失率不同包丟失集中度對(duì)視頻質(zhì)量影響不同的問(wèn)題,提出一種考慮包丟失特性的無(wú)參考網(wǎng)絡(luò)視頻質(zhì)量評(píng)估模型。該模型依據(jù)碼流信息在壓縮域計(jì)算視頻的時(shí)域復(fù)雜度,以及包丟失率對(duì)視頻質(zhì)量的影響因子；為了解決包丟失集中度對(duì)視頻質(zhì)量的影響,提出在壓縮域計(jì)算包丟失集中度的方法,進(jìn)而提出由于丟包引起的視頻質(zhì)量下降的視頻質(zhì)量評(píng)估模型,因此適用于具有版權(quán)保護(hù)的視頻序列質(zhì)量評(píng)估,并且資源開銷小。實(shí)驗(yàn)結(jié)果表明,使用該模型測(cè)得的視頻包丟失質(zhì)量評(píng)分與其主觀質(zhì)量評(píng)分有很好的一致性,相比于國(guó)際標(biāo)準(zhǔn)G.1070中的丟包視頻質(zhì)量評(píng)價(jià)模型,該模型與主觀質(zhì)量評(píng)價(jià)的相關(guān)性平均提高了6.18% 4.考慮人眼視覺容忍特性的無(wú)參考網(wǎng)絡(luò)視頻質(zhì)量評(píng)估模型。視頻通信的最終信宿是人,對(duì)視頻質(zhì)量的評(píng)價(jià)取決于人眼的主觀感受,因此合理的視頻質(zhì)量評(píng)估方法必須符合人眼的視覺特性,給出一種考慮人眼視覺特性的無(wú)參考視頻質(zhì)量評(píng)估模型。首先對(duì)網(wǎng)絡(luò)丟包、誤碼傳播以及包丟失在視頻幀內(nèi)的位置對(duì)視頻幀質(zhì)量的影響進(jìn)行了詳細(xì)的研究；然后分析了網(wǎng)絡(luò)丟包影響多幀時(shí)的人眼視覺容忍性對(duì)視頻序列質(zhì)量的影響；最后通過(guò)對(duì)視頻序列時(shí)域失真的研究進(jìn)而得到整個(gè)視頻序列的客觀質(zhì)量。該模型充分考慮人眼視覺系統(tǒng)的空時(shí)域掩蓋效應(yīng)及容忍性、視頻內(nèi)容、包丟失位置、視頻序列的時(shí)域失真對(duì)視頻質(zhì)量的影響,并且該模型只對(duì)接收的碼流進(jìn)行簡(jiǎn)單的包頭分析即可得到所需信息,因此具有資源開銷小、實(shí)時(shí)性好的特點(diǎn),適合對(duì)實(shí)時(shí)傳輸?shù)囊曨l流進(jìn)行質(zhì)量監(jiān)控。實(shí)驗(yàn)結(jié)果表明,使用該視頻質(zhì)量評(píng)估模型測(cè)得的視頻丟包失真質(zhì)量評(píng)分與其主觀質(zhì)量評(píng)分有很好的一致性。
[Abstract]:IP (Internet Protocol) the rapid development of Internet and mobile communication, the video information processing and transmission in IP network and mobile communication network has attracted more and more attention. How to accurately and effectively assess the video quality, has become a research field in video compression, processing and transmission of the urgent need to address the problem of packet loss is one of the main causes of the decline in the quality of video, the network loss no reference video quality assessment conducted in-depth research, the main research focuses on the real-time and effective improve the objective quality assessment. The frequency characteristics of H.264/AVC encoding, frame type, packet loss rate, packet loss and concentration of human vision have influences on the video quality and other aspects of the in-depth research. The main research contents include:
1. packet loss H.264/AVC network video distortion evaluation. According to the new decoding technique used by H.264/AVC caused by channel error, spatial and temporal error propagation, spatial and temporal error concealment and deblocking filter effects on the video quality, a calculating network video packet loss MSE (Mean Square Error) distortion no reference video quality assessment algorithm. This algorithm considers the spatial and temporal error propagation, error concealment algorithm and the influence on the quality of video encoder characteristics, and low computational complexity, real-time network video quality monitoring. The experimental results show that this algorithm can accurately reflect the quality of the video and video content with MSE. space-time domain characteristics, method of SSIM to evaluate the reference video quality (Structural Similarity Metric) was improved, given an evaluation algorithm of semi reference video quality based on SSIM. The experimental results show that The objective video quality obtained by this algorithm can accurately reflect the subjective quality of the video.
2. consider no reference video quality assessment model for frame type. In view of the network video quality assessment needs to meet the real-time and low resource cost requirements, presents a no reference video quality assessment model. The model considers the loss of different frame types, video content and loss effect of single frame of human visual tolerance affect the characteristics of video the quality, and does not need to fully decode the video resources, with small overhead, good real-time performance, suitable for real-time transmission of video stream quality assessment. The experimental results show that the use of the evaluation model of the measured packet loss of video quality score and subjective quality score distortion is well consistent with the video quality, packet loss video quality assessment model compared to the international standard of G.1070, the correlation model and subjective quality evaluation by an average of 6.96%.
3. consider the non reference video quality assessment model of packet loss characteristics. According to the loss rate of different concentration of packet loss on the video quality of different problems with the same package, a new no reference video quality assessment model considering the packet loss characteristics. The model based on information stream video in the compressed domain time domain computational complexity. The impact factor and packet loss on the video quality; in order to solve the packet loss concentration effects on the video quality, put forward to calculate the concentration of the lost packet in the compressed domain, and then put forward the evaluation model of packet loss caused by the decline due to the video quality of video quality, so it is suitable for video quality assessment with copyright protection, and resources low cost. The experimental results show that using this model the measured packet loss quality score and subjective quality scores are in good agreement, compared to the international The quality evaluation model of packet loss video in standard G.1070, the correlation between the model and the subjective quality evaluation is increased by 6.18%.
4. consider the non reference video quality assessment model of human visual tolerance characteristics. The final destination of video communication is one of the video quality evaluation on subjective feelings in the human eye, so the video quality assessment method is reasonable and must be consistent with the human visual characteristics, gives a kind of considering human visual characteristics no reference video quality assessment model. Firstly, the network packet loss, packet loss and error propagation effects in the video frame position within the frame of video quality are studied in detail; and then analyzes the human visual effects of multi frame network loss tolerance effect on the quality of the video sequence; finally, through the research on objective quality distortion of video sequence to obtain the entire video domain sequence. This model fully considers the space-time domain of human visual system and masking tolerance, video content, packet loss, video sequence The time domain distortion effect on the video quality, the required information and get the model only on the received bit stream by simple analysis to Baotou, so it has low cost of resource, good real-time performance, suitable for real-time transmission of video stream quality monitoring. Experimental results show that the video packet loss using the video quality assessment model the measured distortion quality score and subjective quality scores are in good agreement.

【學(xué)位授予單位】：西安電子科技大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2014
【分類號(hào)】：TN919.81

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本文編號(hào)：1556374