本文關(guān)鍵詞： 高性能視頻編碼 變換編碼 自適應(yīng)多變換 模板匹配 正交匹配追蹤變換　出處：《中國(guó)科學(xué)技術(shù)大學(xué)》2017年碩士論文　論文類(lèi)型：學(xué)位論文

【摘要】：20世紀(jì)以來(lái),隨著計(jì)算機(jī)圖形圖像技術(shù),網(wǎng)絡(luò)傳輸技術(shù),多媒體技術(shù)的發(fā)展,基于視頻技術(shù)的遠(yuǎn)程醫(yī)療、遠(yuǎn)程教育、視頻會(huì)議等應(yīng)用也越來(lái)越普遍。視頻技術(shù)正在向大數(shù)據(jù)量,高分辨率的方向發(fā)展。視頻大數(shù)據(jù)的傳輸和存儲(chǔ)對(duì)視頻技術(shù)的發(fā)展提出了挑戰(zhàn)。因而高效率的視頻壓縮技術(shù)對(duì)視頻技術(shù)的進(jìn)一步發(fā)展顯得尤為重要。2003年5月由運(yùn)動(dòng)圖像專(zhuān)家組(MPEG)和視頻編碼專(zhuān)家組(VCEG)組成的聯(lián)合編碼小組JVT發(fā)布了當(dāng)前主流的編碼標(biāo)準(zhǔn)H.264/AVC。相比于之前的編碼標(biāo)準(zhǔn),H.264/AVC的視頻壓縮性能提升了 50%。十年之后,2013年1月由MPEG和VCEG組成的聯(lián)合編碼小組JCT-VC發(fā)布了新一代視頻編碼標(biāo)準(zhǔn)-高性能視頻編碼(HEVC)。HEVC在H.264的基礎(chǔ)上性能又提升了 50%。現(xiàn)有的視頻編碼標(biāo)準(zhǔn)都是通過(guò)預(yù)測(cè)編碼去除時(shí)間和空間的冗余得到殘差信號(hào),殘差信號(hào)通過(guò)變換量化后進(jìn)行熵編碼。而殘差的數(shù)據(jù)量占據(jù)整個(gè)編碼數(shù)據(jù)量的絕大部分。因此一個(gè)好的變換編碼方式將會(huì)大大提高編碼器的壓縮效率。無(wú)論是H.264還是HEVC,其變換都是采用固定的變換基,然而不同圖像的紋理特性不一樣,其預(yù)測(cè)殘差的統(tǒng)計(jì)特性存在差異。對(duì)于不同統(tǒng)計(jì)特性的殘差采取相同的變換方式,顯然無(wú)法有效地消除殘差的相關(guān)性。本文從變換編碼出發(fā),做了兩方面的研究。一方面通過(guò)增加未來(lái)視頻編解碼器(Future Video Codec,FVC1)變換基的種類(lèi)來(lái)改進(jìn)FVC的變換編碼效率。另一方面希望通過(guò)自適應(yīng)的變換基來(lái)改進(jìn)變換編碼的效率。具體來(lái)說(shuō),本文的主要?jiǎng)?chuàng)新點(diǎn)如下:1、提出自適應(yīng)多變換技術(shù),在FVC現(xiàn)有的編碼框架上,通過(guò)增加DCT-Ⅴ,DCT-Ⅷ,DST-Ⅰ三種變換基,編碼器通過(guò)遍歷不同的變換基找出一個(gè)最適合編碼的變換基作為當(dāng)前的變換基,自適應(yīng)多變換技術(shù)為變換內(nèi)容提供了不同的變換方式,相比于之前只有固定變換基的變換方式,自適應(yīng)性更高。本文同時(shí)統(tǒng)計(jì)和分析變換基的使用情況,提出了快速的自適應(yīng)多變換技術(shù)。實(shí)驗(yàn)表明,本文提出的自適應(yīng)多變換算法可以提升壓縮效率2%～3%左右。2、本文提出正交匹配追蹤變換技術(shù),在HEVC現(xiàn)有編碼框架上,通過(guò)模板匹配,在線訓(xùn)練的方法得到與當(dāng)前待變換內(nèi)容相關(guān)的自適應(yīng)變換基。然后通過(guò)與現(xiàn)有變換編碼對(duì)比,找出一種最優(yōu)的變換方式進(jìn)行變換編碼。相比于之前變換編碼對(duì)于所有變換內(nèi)容均采用相同的變換方式,正交匹配追蹤變換技術(shù)考慮了變換內(nèi)容的多樣性。實(shí)驗(yàn)表明,本文提出的正交匹配追蹤變換技術(shù)可以提升壓縮效率1%～3%左右。
[Abstract]:Since 20th century, with the development of computer graphics and image technology, network transmission technology and multimedia technology, the application of tele-medicine, distance education and video conference based on video technology is becoming more and more common. The transmission and storage of video big data pose a challenge to the development of video technology. Therefore, the efficient video compression technology is particularly important for the further development of video technology. JVT, a joint coding group made up of moving image experts (MPEGG) and video coding expert group (VCE), released the current mainstream coding standard H.264 / AVC.Compared with the previous coding standard H.264 / AVC, the video compression performance of H.264 / AVC improved by 50. 10 years, January 2013. JCT-VC, a joint coding group composed of MPEG and VCEG, has released a new generation of video coding standards-high performance video coding / HEVCU. HEVC has improved the performance of H.264 based on H.264. existing video coding standards are all based on predictive coding removal time. And the redundancy of the space to get the residual signal, The residual signal is encoded by entropy after transform quantization, and the residual data amount accounts for the majority of the total encoded data. Therefore, a good transform coding method will greatly improve the compression efficiency of the encoder, regardless of H. 264. Or HEVCwhose transformation is based on a fixed transformation basis, However, the texture characteristics of different images are different, and the statistical characteristics of the prediction residuals are different. It is obvious that the correlation of the residuals can not be effectively eliminated by using the same transformation method for the residuals of different statistical characteristics. On the one hand, we improve the transform coding efficiency of FVC by adding the kinds of the future Video Codecor FVC 1) transform basis, and on the other hand, we hope to improve the efficiency of transform coding by adaptive transform basis. The main innovations of this paper are as follows: 1. Adaptive multi-transform technology is proposed. In the existing coding framework of FVC, DCT- 鈪，

本文編號(hào)：1526200