A Motion Estimation based Algorithm for Encoding Time Reduction in HEVC

High Efficiency Video Coding (HEVC) is a video compression standard that offers 50% more efficiency at the expense of high encoding time contrasted with the H.264 Advanced Video Coding (AVC) standard. The encoding time must be reduced to satisfy the needs of real-time applications. This paper has proposed the Multi- Level Resolution Vertical Subsampling (MLRVS) algorithm to reduce the encoding time. The vertical subsampling minimizes the number of Sum of Absolute Difference (SAD) computations during the motion estimation process. The complexity reduction algorithm is also used for fast coding the coefficients of the quantised block using a flag decision. Two distinct search patterns are suggested: New Cross Diamond Diamond (NCDD) and New Cross Diamond Hexagonal (NCDH) search patterns, which reduce the time needed to locate the motion vectors. In this paper, the MLRVS algorithm with NCDD and MLRVS algorithm with NCDH search patterns are simulated separately and analyzed. The results show that the encoding time of the encoder is decreased by 55% with MLRVS algorithm using NCDD search pattern and 56% with MLRVS using NCDH search pattern compared to HM16.5 with Test Zone (TZ) search algorithm. These results are achieved with a slight increase in bit rate and negligible deterioration in output video quality

Efficient video coding using visual sensitive information for HEVC coding standard

The latest high efficiency video coding (HEVC) standard introduces a large number of inter-mode block partitioning modes. The HEVC reference test model (HM) uses partially exhaustive tree-structured mode selection, which still explores a large number of prediction unit (PU) modes for a coding unit (CU). This impacts on encoding time rise which deprives a number of electronic devices having limited processing resources to use various features of HEVC. By analyzing the homogeneity, residual, and different statistical correlation among modes, many researchers speed-up the encoding process through the number of PU mode reduction. However, these approaches could not demonstrate the similar rate-distortion (RD) performance with the HM due to their dependency on existing Lagrangian cost function (LCF) within the HEVC framework. In this paper, to avoid the complete dependency on LCF in the initial phase, we exploit visual sensitive foreground motion and spatial salient metric (FMSSM) in a block. To capture its motion and saliency features, we use the dynamic background and visual saliency modeling, respectively. According to the FMSSM values, a subset of PU modes is then explored for encoding the CU. This preprocessing phase is independent from the existing LCF. As the proposed coding technique further reduces the number of PU modes using two simple criteria (i.e., motion and saliency), it outperforms the HM in terms of encoding time reduction. As it also encodes the uncovered and static background areas using the dynamic background frame as a substituted reference frame, it does not sacrifice quality. Tested results reveal that the proposed method achieves 32% average encoding time reduction of the HM without any quality loss for a wide range of videos

Fast Motion Estimation Based on Diamond Refinement Search and Mode Decision Algorithm for High Efficiency Video Coding Standard

隨著科技的進步，不論在專業視頻、網路視頻或是日常消費視頻，對於高解析度的需求，都在不斷的日益增加，HD畫質已經全面普及化，而隨著4K 技術已經漸漸成熟，將迎接著更高畫質的4K時代來臨。HEVC可以支持各類規格的視頻，從CIF (320 × 288) 到HD (1920 × 1080)，及高解析度的4K (3840 × 2160) 與最高的8K UHD (7680 × 4320)。 H.264的編碼單位有4 × 4和16 × 16兩種尺寸，HEVC 提升至最大64 × 64 到最小8 × 8，依照不同的需求配置不同的大小區塊，HEVC主要以三個重要的單元進行，引進了更大的編碼單元CU(Coding Unit)、預測單位(Prediction Unit) 以及轉換單位(Transform Unit)，HEVC 與H.264 相比可以節省50 %的壓縮效能，而在視訊壓縮中，為了找到最小的RD-Cost的匹配區塊，動作估計往往需要花費相當高的運算量，因此本論文提出一個新的HEVC快速搜尋動作估計演算法，減少複雜度計算提高壓縮效率。 在本篇論文中，提出一種新的快速搜尋動作估計演算法方法，包含Diamond Refinement Search、Mode Decision 以及Inter Prediction Min Block Size 三個部份的修改，在鑽石細化搜索利用AMVP預測的動作向量IMV作為搜尋的起始點，檢查原點零向量與IMV比較，選擇較小的RD-Cost ，當作第一次搜尋的起始點，利用第一次搜尋(4 Round Diamond Search)，取得其RD-Cost最小位置，當原點與最佳點距離不為0 或1 時，判定距離是否大於4，若距離大於4進行Diamond Refinement Search 方案搭配Concentric Diamond Search 細化搜索；若距離小於或等於4，以Small Diamond Search 方法進行快速搜索。 在模式的決定中Mode 的選擇，透過統計而只選用2N x 2N Mode，以及N x N Mode 使用率最高的兩種，可以省去比較少使用到的Mode，以此可以大幅的加速整體運算時間，然而針對Inter Prediction Min Block Size 縮小，由原本的8 x 8改為4 x 4，可將原本Block Size切割為更小區塊搜索，以提升只選用2N x 2N Mode及N x N Mode 後的影像品質。 實驗結果本論文所提出的，基於鑽石細化搜索和模式決定的高效視頻編碼標準快速運動估計演算法，在加入Inter Prediction Min Block Size 的修改後，可於Bit-Rate提升1.45 %，及PSNR 下降微乎其微的 -0.03 情況下，可節省整體編碼時間46.15 %。With the advancement of science and technology, the demand for high-definition video is constantly increasing both in professional video, online video and daily consumer videos, and HD quality has been fully popularized. With the gradual maturation of 4K technology , will meet the 4K era of higher quality advent. HEVC can support a wide range of video formats from CIF (320 × 288) to HD (1920 × 1080), high resolution 4K (3840 × 2160) and up to 8K UHD (7680 × 4320). The encoding unit is increased from the size of (4 × 4) and (16 × 16) of H.264 to the maximum (64 × 64) to the minimum (8 × 8) of HEVC, and different size blocks are configured according to different requirements. HEVC mainly in three important units, the introduction of a larger coding unit CU (Coding Unit), the prediction unit (Prediction Unit) and the conversion unit (Transform Unit), HEVC compared with H.264 can save 50% of the compression In the video compression, in order to find the matching block with the smallest RD-Cost, the motion estimation often takes a relatively high amount of computation. Therefore, this paper presents a new HEVC algorithm for fast motion estimation and reduces the computational complexity improve compression efficiency. In this paper, a new fast search motion estimation algorithm is proposed contains changes to the three parts of Diamond Refinement Search, Mode Decision, and Inter Prediction Min Block Size. In the diamond refinement search, the motion vector IMV predicted by the AMVP is used as the starting point of the search, the origin zero vector is compared with the IMV, and the smaller RD-Cost is selected as the starting point of the first search, using the first 4 round diamond Search to obtain the minimum RD-Cost position. When the distance between the origin and the best point is not 0 or 1, the distance is determined to be greater than 4. If the distance is greater than 4, the Diamond Refinement Search solution is matched with the Concentric Diamond. Search refines the search; if the distance is less than or equal to 4, use the Small Diamond Search method for a quick search. In the mode selection, using statistics only 2N x 2N Mode, and the highest N x N Mode usage rate, can save the less used Mode, which can greatly accelerate the overall operation time , However, Inter Prediction Min Block Size reduction, the original 8 x 8 is changed to 4 x 4. The original block size can be cut into smaller blocks to improve the image quality after only using 2N x 2N Mode and N x N Mode. Experimental results This paper proposes a high-speed video coding standard fast motion estimation algorithm based on diamond refinement search and mode decision. After adding the Inter Prediction Min Block Size modification, the overall coding time can be saved by 46.15% with a 1.45% increase in Bit-Rate and a -0.03 drop in PSNR.摘要........................................................... i Abstract........................................................iii 目錄........................................................... v 表 目 錄...................................................... vii 圖 目 錄........................................................x 第一章 緒論.................................................... 1 1.1研究背景 ................................................1 1.2研究動機與目的...........................................2 1.3研究架構.................................................3 第二章 HEVC視訊編碼核心技術...................................4 2.1 HEVC編碼流程......................................... 4 2.1.1 HEVC 規格與壓縮性能..............................5 2.1.2 編碼單元..........................................5 2.1.3 預測單元..........................................7 2.1.4 轉換單元..........................................8 2.1.5 熵編碼............................................9 2.1.6 環形濾波器........................................10 2.2 動作估計與動作補償.................................... 11 2.2.1 動作估計與動作補償...............................11 2.2.2 預測動作估計模式.................................13 2.2.3 模式選擇之快速跳離...............................16 2.3 編碼環境參數及影像序列模式介紹.........................18 2.3.1 HEVC測試序列介紹...............................18 2.3.2 編碼環境參數配置.................................20 2.3.3 HEVC編碼序列模式................................20 第三章 HEVC 快速搜尋動作估計探討.............................23 3.1相關之動作估計文獻.....................................23 3.1.1 Fast Motion Estimation Based on Content Property for Low-Complexity H.265 Encoder [13] ...............24 3.1.2 Early Skip Mode Decision for HEVC Encoder With Emphasis on Coding Quality [32]...........................28 3.1.3 Fast Inter Mode Decision Based on Motion Estimation and Texture Feature for HEVC [34]......................28 3.2參考軟體的動作估計流程(TZ-Search) ......................30 第四章 基於鑽石細化搜索和模式決定的高效視頻編碼標準快速運動估計演算法................................................38 4.1基於鑽石細化搜索和模式決定的高效視頻編碼標準快速運動估計演算法.............................................38 4.1.1鑽石細化搜索 (Diamond Refinement Search).........39 4.1.2 模式決定 (Mode Decision) .........................47 4.1.3 幀間預測最小塊大小(Inter Prediction Min Block Size) ..49 4.2實驗平台與參數設定......................................50 第五章 實驗結果與數據分析討論..................................51 5.1實驗數據討論........................................... 51 5.2本論文與文獻之分析比較................................ 87 第六章 結論....................................................91 參考文獻.......................................................9