基于HEVC的低復雜度幀內(nèi)幀間壓縮算法研究
發(fā)布時間：2019-06-29 14:02
【摘要】：當今信息化的時代,隨著計算機及互聯(lián)網(wǎng)技術(shù)的發(fā)展,視頻應用越來越廣泛而頻繁。無線視頻傳輸是無線射頻收發(fā)和視頻信息處理技術(shù)的結(jié)合,適用于許多難以靠有線傳輸視頻的場合。當今各領域各應用場合對無線視頻傳輸提出了更高的需求,視頻分辨率和幀率的增大直接導致壓縮后的視頻碼率驟然上升。為實現(xiàn)視頻的及時傳送,在提升無線收發(fā)能力的同時,采用新一代視頻壓縮標準HEVC能夠節(jié)約一半的碼率。為在無線視頻傳輸系統(tǒng)中應用HEVC,需要解決其計算復雜度高的問題。目前的基于HEVC的低復雜度幀內(nèi)幀間算法,一般針對的環(huán)節(jié)有限,雖然保證了率失真性能幾乎不變,但編碼時間的降低也比較有限。考慮到無線視頻傳輸?shù)膽脤嶋H,本文在略微犧牲率失真性能的情況下,節(jié)約了更多的編碼時間�；趯瑑�(nèi)幀間視頻壓縮原理的理解和對最優(yōu)率失真算法流程的研究,本文對幀內(nèi)幀間的CU劃分環(huán)節(jié)和模式預測環(huán)節(jié)都進行了低復雜度改進。本文首先提出了基于圖像空間相關性的CU快速劃分算法,利用相鄰CU的深度信息為當前CU設定深度范圍,該算法可以同時應用于幀內(nèi)預測與幀間預測的情形。對于幀內(nèi)預測,本文首先根據(jù)參考像素方差和幀內(nèi)模式之間的統(tǒng)計規(guī)律,提出了可以跳過RMD過程并排除角度模式的快速算法。在RMD與RDO模式選擇過程中,本文利用圖像紋理特征以及MPM統(tǒng)計特征實現(xiàn)了幀內(nèi)模式的快速優(yōu)選。接著利用幀內(nèi)最終預測模式的RD代價實現(xiàn)了CU劃分的提前終止,最后結(jié)合上述各改進點設計了低復雜度幀內(nèi)預測綜合算法。對于幀間預測,本文基于對率失真代價與預測殘差及量化參數(shù)的理解,認為當滿足Skip條件或CBF為零的條件時,為實現(xiàn)更高的編碼時間節(jié)約比率,可以不加約束地跳過后續(xù)其他模式。另外,考慮到非對稱分割模式(AMP)起到的作用較小,本文禁用了非對稱模式。最后結(jié)合上述幀間預測策略及CU快速劃分算法,設計了低復雜度幀間預測綜合算法。實驗表明,相對于現(xiàn)有低復雜度算法,本文提出的幀內(nèi)幀間綜合算法,在率失真性能損失略微提升的前提下,可以降低更多的編碼時間。
[Abstract]:Nowadays, with the development of computer and Internet technology, video application is more and more extensive and frequent. Wireless video transmission is a combination of radio frequency transceiver and video information processing technology, which is suitable for many occasions where it is difficult to transmit video by cable. Nowadays, there is a higher demand for wireless video transmission in various fields. The increase of video resolution and frame rate directly leads to the sudden increase of video rate after compression. In order to realize the timely transmission of video, the new generation video compression standard HEVC can save half the bit rate while improving the wireless transceiver ability. In order to apply HEVC, in wireless video transmission system, it is necessary to solve the problem of high computational complexity. The current low complexity intra-frame algorithm based on HEVC is generally limited. Although the rate-distortion performance is almost unchanged, the reduction of coding time is also limited. Considering the application practice of wireless video transmission, this paper saves more coding time under the condition of slightly sacrificing rate-distortion performance. Based on the understanding of the principle of intra-frame video compression and the research of the optimal rate-distortion algorithm, this paper improves the CU partition and mode prediction of intra-frame frames with low complexity. In this paper, a fast CU partition algorithm based on image spatial correlation is proposed. Using the depth information of adjacent CU to set the depth range for the current CU, the algorithm can be applied to both intra-frame prediction and inter-frame prediction. For intra prediction, according to the statistical law between reference pixel variance and intra mode, a fast algorithm which can skip RMD process and exclude angle mode is proposed in this paper. In the process of RMD and RDO mode selection, this paper uses image texture features and MPM statistical features to achieve fast intra mode selection. Then the early termination of CU partition is realized by using the RD cost of the final intra prediction mode. Finally, a low complexity intra prediction synthesis algorithm is designed according to the above improved points. For inter-frame prediction, based on the understanding of rate-distortion cost, prediction residual and quantification parameters, it is considered that when the Skip condition or CBF is zero, in order to achieve a higher coding time saving ratio, the following other modes can be skipped without constraint. In addition, considering that asymmetric segmentation mode (AMP) plays a small role, asymmetric mode is disabled in this paper. Finally, combined with the above inter-frame prediction strategy and CU fast partition algorithm, a low complexity inter-frame prediction synthesis algorithm is designed. The experimental results show that compared with the existing low complexity algorithms, the intra-frame synthesis algorithm proposed in this paper can reduce the coding time with the slight improvement of rate-distortion performance loss.
【學位授予單位】：哈爾濱工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TN919.81
本文編號：2507868
[Abstract]:Nowadays, with the development of computer and Internet technology, video application is more and more extensive and frequent. Wireless video transmission is a combination of radio frequency transceiver and video information processing technology, which is suitable for many occasions where it is difficult to transmit video by cable. Nowadays, there is a higher demand for wireless video transmission in various fields. The increase of video resolution and frame rate directly leads to the sudden increase of video rate after compression. In order to realize the timely transmission of video, the new generation video compression standard HEVC can save half the bit rate while improving the wireless transceiver ability. In order to apply HEVC, in wireless video transmission system, it is necessary to solve the problem of high computational complexity. The current low complexity intra-frame algorithm based on HEVC is generally limited. Although the rate-distortion performance is almost unchanged, the reduction of coding time is also limited. Considering the application practice of wireless video transmission, this paper saves more coding time under the condition of slightly sacrificing rate-distortion performance. Based on the understanding of the principle of intra-frame video compression and the research of the optimal rate-distortion algorithm, this paper improves the CU partition and mode prediction of intra-frame frames with low complexity. In this paper, a fast CU partition algorithm based on image spatial correlation is proposed. Using the depth information of adjacent CU to set the depth range for the current CU, the algorithm can be applied to both intra-frame prediction and inter-frame prediction. For intra prediction, according to the statistical law between reference pixel variance and intra mode, a fast algorithm which can skip RMD process and exclude angle mode is proposed in this paper. In the process of RMD and RDO mode selection, this paper uses image texture features and MPM statistical features to achieve fast intra mode selection. Then the early termination of CU partition is realized by using the RD cost of the final intra prediction mode. Finally, a low complexity intra prediction synthesis algorithm is designed according to the above improved points. For inter-frame prediction, based on the understanding of rate-distortion cost, prediction residual and quantification parameters, it is considered that when the Skip condition or CBF is zero, in order to achieve a higher coding time saving ratio, the following other modes can be skipped without constraint. In addition, considering that asymmetric segmentation mode (AMP) plays a small role, asymmetric mode is disabled in this paper. Finally, combined with the above inter-frame prediction strategy and CU fast partition algorithm, a low complexity inter-frame prediction synthesis algorithm is designed. The experimental results show that compared with the existing low complexity algorithms, the intra-frame synthesis algorithm proposed in this paper can reduce the coding time with the slight improvement of rate-distortion performance loss.
【學位授予單位】：哈爾濱工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TN919.81
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