Fast Coding Quad-Tree Decisions Using Prediction Residuals Statistics for High Efficiency Video Coding (HEVC)

Tan, Hui Li; Ko, Chi Chung; Rahardja, Susanto

doi:10.1109/tbc.2015.2505406

Cited by 48 publications

(26 citation statements)

References 13 publications

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“…For each type of frame I, P, and B (depending on the temporal level), authors proposed an algorithm that decreases the encoding time reaching 64% [17]. In [18], a HEVC coding quad-tree was early terminated by using residuals statistics at the PUs level. The prediction residuals statistics was computed as the absolute difference between the prediction residuals variances for the two Nx2N and for the two 2NxN.…”

Section: Related Workmentioning

confidence: 99%

“…The prediction residuals statistics was computed as the absolute difference between the prediction residuals variances for the two Nx2N and for the two 2NxN. The introduced residual based method allowed reducing the encoding time by an average of about 44% [18]. A statistical analysis of coding units was chosen by the encoder for HEVC in [19].…”

Section: Related Workmentioning

confidence: 99%

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Depth Partitioning and Coding Mode Selection Statistical Analysis for SHVC

Wali¹,

Kessentini²,

Ayed³

et al. 2017

ijacsa

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Abstract-The Scalable High Efficiency Video Coding (SHVC) has been proposed to improve the coding efficiency. However, this additional extension generally results an important coding complexity. Several studies were performed to overcome the complexity through algorithmic optimizations that led to an encoding time reduction. In fact, mode decision analysis is imperatively important in order to have an idea about the partitioning modes based on two parameters, such as prediction unit size and frame type. This paper presents statistical observations at two levels: coding units (CUs) and prediction units (PUs) selected by the encoder. Analysis was performed for several test sequences with different motion and texture characteristics. The experimental results show that the percentage of choosing coding or prediction unit size and type depends on sequence parameters, frame type, and temporal level.

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Depth Partitioning and Coding Mode Selection Statistical Analysis for SHVC

Wali¹,

Kessentini²,

Ayed³

et al. 2017

ijacsa

View full text Add to dashboard Cite

show abstract

“…Therefore the address of the northwest level-2 quad is 00 which is also the address of the northwest quadrant of level-1 quad. Thus the level-2 quads are denoted as quad(00), quad(01), quad (10) and quad (11) as shown with blue borders in Fig. 1 (b).…”

Section: Address Assignment For Quads and Quadrantsmentioning

confidence: 99%

“…The main strength of a quadtree scheme is spatial indexing and addressing. They are used for data clustering [2][3] , network routing schemes [4][5] , advanced image processing [6][7] , data compression [8][9][10] , video coding [11][12][13] and spatial addressing of geographical regions [14] . Therefore, quadtree is a powerful technique for problem solving in diverse fields.…”

Section: Introductionmentioning

confidence: 99%

Lossless address data compression using quadtree clustering of the sensors in a grid based WSN

Thomas

Mathew

2017

Ad Hoc Networks

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“…The splitting decision in [29] is based on skipping some specific depth levels rarely used in the previous frame and neighboring CUs in addition to using termination methods based on motion homogeneity checking, RD cost checking and SKIP mode checking. An early pruning method based on statistics of the prediction residuals is used in [33] to produce significant time gain. A fast CU decision approach is proposed in [36] based on an exponential model expressing the relationship between the motion compensation R-D cost and the SAD cost for the upper CU and its sub-CUs.…”

Section: Related Workmentioning

confidence: 99%

Inter Prediction Complexity Reduction for HEVC based on Residuals Characteristics

Saurty¹,

Cartigny²,

Krishnaraj³

2016

ijacsa

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Abstract-High Efficiency Video Coding (HEVC) or H.265 is currently the latest standard in video coding. While this new standard promises improved performance over the previous H.264/AVC standard, the complexity has drastically increased due to the various new improved tools added. The splitting of the 64×64 Largest Coding Unit (LCU) into smaller CU sizes forming a quad tree structure involves a significant number of operations and comparisons which imposes a high computational burden on the encoder. In addition, the improved Motion Estimation (ME) techniques used in HEVC inter prediction in order to ensure greater compression also contribute to the high encoding time. In this paper, a set of standard thresholds are identified based on the Mean Square (MS) of the residuals. These thresholds are used to terminate the CU splitting process and to skip some of the inter modes processing. In addition, CUs with large MS values are split at a very early stage. Experimental results show that the proposed method can effectively reduce the encoding time by 62.2% (70.8% for ME) on average, compared to HM 10, yielding a BD-Rate of only 1.14%.

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Fast Coding Quad-Tree Decisions Using Prediction Residuals Statistics for High Efficiency Video Coding (HEVC)

Cited by 48 publications

References 13 publications

Depth Partitioning and Coding Mode Selection Statistical Analysis for SHVC

Depth Partitioning and Coding Mode Selection Statistical Analysis for SHVC

Lossless address data compression using quadtree clustering of the sensors in a grid based WSN

Inter Prediction Complexity Reduction for HEVC based on Residuals Characteristics

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