【摘要】：視頻信息的直觀性、確切性、高效性、廣泛性等一系列優(yōu)點(diǎn)使其在通信領(lǐng)域受到極大青睞。但是,視頻信息量大又極大的限制了其在Internet和移動網(wǎng)絡(luò)中的處理與傳輸。自20世紀(jì)90年代以來Internet和移動通信技術(shù)迅猛發(fā)展,視頻壓縮問題也吸引了眾多學(xué)者的眼球,并在視頻編解碼技術(shù)上取得了很大成就。2006年,我國擁有自主知識產(chǎn)權(quán)的先進(jìn)音視頻編碼標(biāo)準(zhǔn)AVS開始實(shí)施,為我國視頻通信技術(shù)開辟了廣闊的的發(fā)展空間。 隨著網(wǎng)絡(luò)技術(shù)越來越成熟、應(yīng)用越來越廣泛,如今的視頻應(yīng)用已從過去面向存儲的視頻編解碼應(yīng)用轉(zhuǎn)向面向網(wǎng)絡(luò)傳輸?shù)囊曨l編解碼。面向網(wǎng)絡(luò)傳輸?shù)囊曨l編解碼主要受帶寬以及終端設(shè)備多樣化的限制。如何使網(wǎng)絡(luò)視頻業(yè)務(wù)具有足夠的靈活性,以適應(yīng)網(wǎng)絡(luò)的帶寬需求,以及滿足不同用戶、不同設(shè)備終端的不同需求,成為現(xiàn)下亟待解決的問題,因此可伸縮編解碼應(yīng)運(yùn)而生。 可伸縮視頻編碼(Scalable Video Coding, SVC)經(jīng)過一次性壓縮編碼后產(chǎn)生的碼流能被可伸縮解碼器解得不同碼率、幀率、空間分辨率和視頻質(zhì)量的視頻圖像。因此,產(chǎn)生的視頻流具有能夠適應(yīng)網(wǎng)絡(luò)和終端變換的特性,可在規(guī)定的碼率范圍內(nèi)提供較高的解碼質(zhì)量,具有碼率可變等優(yōu)點(diǎn)。但是,好的伸縮性能也造成可伸縮視頻編解碼的計(jì)算復(fù)雜度較高、實(shí)踐應(yīng)用的難度較大。 基于上述問題本課題主要目的是設(shè)計(jì)一套可伸縮編解碼系統(tǒng),在提高可伸縮視頻質(zhì)量的同時(shí)最大限度的降低視頻編解碼的計(jì)算復(fù)雜度。主要工作與創(chuàng)新點(diǎn)如下： 深入研究AVS編解碼原理及官方發(fā)布的參考編、解碼軟件的基礎(chǔ)上,提出了保持運(yùn)動變換的可伸縮編、解碼系統(tǒng)設(shè)計(jì)思想。該系統(tǒng)針對傳統(tǒng)分級可伸縮編碼運(yùn)動搜索復(fù)雜度高的缺點(diǎn)提出了保持運(yùn)動的可伸縮編解碼。該算法只對基本層進(jìn)行運(yùn)動搜索,對上采樣得到的增強(qiáng)層使用基本層對應(yīng)參考幀的運(yùn)動矢量MV (Motion Vector)。因此,減少了增強(qiáng)層的運(yùn)動搜素,不僅減少了傳輸比特而且大大降低了計(jì)算復(fù)雜度。由此帶來的信噪比PSNR的降低則由更加精準(zhǔn)的濾波器與相匹配的量化來補(bǔ)償。
[Abstract]:Video information has a series of advantages, such as intuitiveness, accuracy, efficiency, extensiveness and so on, which make it very popular in the field of communication. However, the amount of video information greatly limits its processing and transmission in Internet and mobile networks. With the rapid development of Internet and mobile communication technology since 1990s, video compression has attracted the attention of many scholars, and has made great achievements in video coding and decoding technology. AVS, an advanced audio and video coding standard with independent intellectual property rights, has opened up a broad space for the development of video communication technology in China. With the network technology becoming more and more mature and widely used, today's video applications have changed from storage oriented video codec applications to network transmission-oriented video codec applications. Video coding and decoding for network transmission is mainly limited by bandwidth and diversity of terminal devices. How to make the network video service flexible enough to meet the bandwidth requirements of the network, and to meet the different needs of different users and different device terminals, becomes an urgent problem, so scalable coding and decoding emerge as the times require. The bitstream generated by the scalable video coding (Scalable Video Coding, SVC) can be resolved by the scalable decoder to obtain video images of different rates frame rate spatial resolution and video quality. Therefore, the generated video stream can adapt to the network and terminal transformation, can provide high decoding quality within the specified bit rate range, and has the advantages of variable bit rate and so on. However, good scalability also results in high computational complexity of scalable video coding and decoding, and great difficulty in practical application. The main purpose of this paper is to design a scalable codec system to improve the quality of scalable video at the same time to reduce the computational complexity of video coding and decoding. The main work and innovations are as follows: on the basis of deeply studying the principle of AVS coding and decoding and the official reference coding and decoding software, this paper puts forward the design idea of scalable coding and decoding system to maintain the motion transformation. Aiming at the high complexity of the traditional scalable coding, the system proposes a scalable codec to preserve the motion. The algorithm only searches the motion of the basic layer, and uses the motion vector MV (Motion Vector). Of the reference frame of the base layer to obtain the enhancement layer from the upper sampling. Therefore, the motion search in the enhancement layer is reduced, which not only reduces the transmission bits, but also greatly reduces the computational complexity. The resulting reduction in SNR PSNR is compensated by more accurate filters and matched quantization.
【學(xué)位授予單位】：太原理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TN919.81

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