Fast Intra Prediction Algorithm with Enhanced Sampling Decision for

H.265/HEVC

Sio-Kei Im

, Mohammad Mahdi Ghandi

and Ka-Hou Chan

MPI-QMUL Information Systems Research Centre, Macao Polytechnic Institute, Macao, China

University of Essex, Essex, U.K.

{marcusim, chankahou}@ipm.edu.mo, mahdighandi@gmail.com

Keywords:

High Efﬁcient Video Coding, Fast Intra Predication, Weighted Sampling, Adaptive Thresholds.

Abstract:

H.265/HEVC is the latest video coding standard, which offers superior compression performance against

H.264/AVC at the cost of greater complexity in its encoding process. In the intra coding of HEVC, a Coding

Unit (CU) is recursively divided into a quad-tree-based structure from the Largest Coding Unit (LCU). At each

level, up to 35 potential intra modes should be checked. However, examining all these modes is very time-

consuming. In this paper, an intra mode decision algorithm is proposed that reduces the required computations

while having negligible effect on Rate-Distortion (RD) performance. A rough mode decision method based

on image component sampling is proposed to reduce the number of candidate modes for rough mode decision

and RD optimization. To balance the quality and performance, the decision to reduce the full search is made

with a thresholds that is dynamically updated based on the Quantization Parameter (QP) and CU size of each

recursive step. Experiments show that our algorithm can achieve a reasonable trade-off between encoding

quality and efﬁciency. The saving in encoding time is between 30.0% to 45.0% while BD-RATE may increase

by up to 0.5% for H.265/HEVC reference software HM 16.9 under all-intra conﬁguration.

1 INTRODUCTION

The H.264/AVC video coding standard (Wiegand

et al., 2003) is widely used in currently deployed

video broadcasting systems. However, there is a

need to deliver higher resolution and better quality of

video. To respond to this need, ISO/IEC Moving Pic-

ture Experts Group (MPEG) and ITU-T Video Coding

Experts Group (VCEG) have jointly developed a new

video coding standard named High Efﬁciency Video

Coding (H.265/HEVC) (Sullivan et al., 2012).

H.265/HEVC realizes better image quality in

comparison with H.264/AVC at the same coding bit-

rate, but also needs much larger complexity in its

encoding process. For intra coding, it has been

known that the recursive quad-tree-based structure

of the Coding Unit (CU) can improve the process-

ing efﬁciency while the encoding complexity is in-

creased signiﬁcantly (Kim et al., 2012). The com-

plexity of H.265/HEVC intra coding increases sev-

eral times compared with H.264/AVC intra coding

(Bossen et al., 2012) since the best intra prediction

mode and CU size need to be decided by the Rate-

Distortion Optimization (RDO).

1.1 Intra Prediction in H.265/HEVC

In H.265/HEVC, there are three types of coding

blocks: Coding Unit (CU), Prediction Unit (PU) and

Transform Unit (TU). Coding Tree Unit (CTU) is a

concept of Largest Coding Unit (LCU, size = 64 ×64

, depth = 0). Each CU can be encoded in the best

mode achieving the smallest Rate-Distortion (RD)

cost among all the possible modes or recursively split

into four CUs with equal sizes until the Smallest Cod-

ing Unit (SCU, size = 8 × 8. depth = 3). The parti-

tioning structure of CU and PU is shown in Fig. 1.

2N ·2N

2N ·N

N ·2N

N ·N

LCU

CU CU

Figure 1: Partitioning structure of CU and splitting of PU,

here N is half of the CU size.

After splitting the CU, then the PU and TU can

Im S., Mahdi Ghandi M. and Chan K.

Fast Intra Prediction Algorithm with Enhanced Sampling Decision for H.265/HEVC.

DOI: 10.5220/0006131400600067

In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017), pages 60-67

ISBN: 978-989-758-225-7

be split independently, and selected for the CU if the

sum of the RD costs of four sub-CUs is smaller than

the RD cost of a large CU (Kim et al., 2012; Huang

et al., 2014). In intra mode, there are up to 35 possible

intra prediction modes in H.265/HEVC while only 9

modes are allowed in H.264/AVC. Note that the PU

can only be split into a square shape, and each PU

will choose the best matching prediction mode.

1.2 Related Work

In order to reduce the complexity of intra coding in

H.265/HEVC, there have been many algorithms pro-

posed in the literature focusing on fast intra mode de-

cision and fast CU size decision. The decision mak-

ing can be modiﬁed such as in (Piao et al., 2010) to

speed up the process. The algorithms used in (Yan

et al., 2012) and (Shen et al., 2013a) are based on the

correlation of adjacent prediction costs, which speeds

up the process but the extra computation load is still

high. In (Cho and Kim, 2013), an early CU split-

ting and pruning method is discussed and the method

in (Shen et al., 2013b) replaces the ﬁxed tree-depth

range for each CU with an adaptive CU depth deci-

sion depending on the previously encoded slices and

neighbouring CUs. In (Zhao et al., 2011), a smaller

candidate set is proposed that does not lead to notice-

able quality loss, this compared various settings with

different mode candidates for the full Rate-Distortion

Optimized Quantization (RDOQ).

To reduce the complexity, (Choi and Jang, 2012)

proposed a tree pruning algorithm for fast CU deci-

sion making. It skips the further CU splitting if the

current CU chooses the SKIP mode. Such SKIP-

mode-based early termination cannot be applied to

the intra prediction. Moreover, some papers proposed

alternative thresholds condition: a local edge infor-

mation is obtained by calculating edge feature pa-

rameters in (da Silva et al., 2012) and (Jiang et al.,

2012) employed a gradient based method to speed

up CU decisions. According to (Min and Cheung,

2015; Jamali et al., 2015; Lim et al., 2015), the results

of HEVC intra coding based on different versions of

HMs are similar due to the fact that HEVC intra cod-

ing does not involve signiﬁcant changes among these

versions. Therefore, it is acceptable to compare these

methods under different HM versions. Then, a gra-

dient based fast intra mode decision is proposed in

(Chen et al., 2013), which based on the gradient direc-

tions for each CU, selects only a small set of modes

for further intra prediction. Hence, a large portion of

modes are removed from the computation.

1.3 Contribution

In this paper, we propose a fast intra mode prediction

algorithm while maintaining the RD performance by

analysing picture feature statistics. An early termi-

nation technique for CU is applied in H.265/HEVC

for experiments. Corresponding to the required en-

coding efﬁciency and the quality of encoded picture,

we use the subsampling result of deviation values of

Luma/Chroma in different sizes for video sequences.

Since there are several Chroma-Subsampling in the

standard, we propose the weight of Luma/Chroma

will depend on the ratio of common Sampling sys-

tems (explained in Sec. 2.2). Further, to balance

the quality and performance, we deﬁne a thresh-

olds (T ) without using static decision thresholds, and

rely on a comparison between the Quantization Pa-

rameter (QP) and CU size of the coding tree un-

der test, which have to be updated at each recur-

sion. The use of adaptive thresholds is fundamental

in H.265/HEVC as the number of possible partition-

ing and coding modes is more appropriate then static

thresholds for each of them.

The rest of the paper is organized as follow: Sec. 2

provides details of the idea of the fast intra prediction

algorithm including the proposed weighed sampling

operator and adaptive thresholds. Sec. 3 gives the de-

tails of the concept about the thresholds and how to

achieve this in different depth layers. The simulation

results are given in Sec. 4, and Sec. 5 concludes the

paper.

2 PROPOSED METHOD

The intra mode prediction deﬁned in the

H.265/HEVC standard allows 35 (including Pla-

nar, DC mode and 33 angular) predictions. Planar

and DC prediction modes can provide predictions

for image areas with smooth and gradually changing

content. The angular intra predictions are designed

to model different directional structures typically

present in picture (see Fig. 2).

2.1 Fast Intra Prediction Algorithm

As a range of sample methods, the angular predictions

are also useful in smooth PU blocks without high fre-

quency components for complex textures that cannot

be properly modelled with any of the directional pre-

dictors. It can easily perceive that a large size CU is

more suitable for some homogeneous or ﬂat regions

in the image. For discriminating texture, CUs that are

not split into sub-CUs are expected to have smaller

Fast Intra Prediction Algorithm with Enhanced Sampling Decision for H.265/HEVC

−30−25−20−15−10−5

0 5 10 15 20 25 30

−30

−25

−20

−15

−10

−5

Figure 2: Angle deﬁnitions of angular intra prediction in

H.265/HEVC. (H,V ) is used to indicate the displacement.

Prediction mode 2 to 17 is index by (H, −32), and mode 18

to 34 is index by (−32,V ).

RD costs than would occur if the CUs were split,

while an area with colourful edges or object bound-

aries is usually split into small CUs. Since the feature

of a homogeneous region is that the sampling result

approaches the mean value, the Sum of Absolute Dif-

ference (SAD) can represent the image complexity.

In extreme cases, if (SAD = 0), it means there is full

homogeneity: i.e. there is exactly same sample value

in the whole region. Applying to intra prediction, we

design to calculate the image complexity before the

33 angular intra predictions as:

mean =

N × N

N,N

∑

i=1, j=1

C (i, j) (1)

SAD =

N,N

∑

i=1, j=1

mean −C (i, j)

(2)

where N ∈

{

64, 32, 16

}

is the size of the current CU,

C (i, j) is the (sub)-sampling method that is exploited

by a weighted sampling operator and SAD represents

the image complexity and can be used to determine

whether it is necessary to do the angular prediction.

After the texture calculation, if the SAD is smaller

than or equal to the corresponding thresholds, the

image is thought to be smooth enough to terminate

the prediction early. Therefore, this algorithm avoids

checking SCU sizes when they are not likely to be

selected by the brute force RDO process.

2.2 Weighted Sampling Operator

For each CU at a given depth, all the allowed cod-

ing modes are tested and the mode with the minimum

RD cost is selected, then the early termination stops

the CU splitting process if the minimum SAD is al-

ready lower than a given threshold. This mean that a

good coding conﬁguration has already been obtained

and searching for smaller CUs may only slightly im-

prove the overall performance or, indeed, may even

provide a lower performance as smaller CU sizes may

imply less compression in transformation. In order

to enhance the sampling to the reference results, we

must consider the weighted sampling/subsampling of

Luma and Chroma components in prediction block.

According to the efﬁciency of different conﬁgurations

scenario at quantization settings, we used a weighted

sum of the average sampling values for the Luma and

Chroma components, deﬁned by

C =

, w

) · (Luma, Chroma)

+ w

(3)

where the weights value (w

, w

) must satisfy the

conditions w

> 0, w

> 0 and w

6= 0, depend-

ing on the colour sampling modes,

, w

) =











(8, 0), type = 4 : 0 : 0

(8, 2), type = 4 : 1 : 1

(8, 2), type = 4 : 2 : 0

(8, 4), type = 4 : 2 : 2

(8, 4), type = 4 : 4 : 0

(8, 8), type = 4 : 4 : 4

(4)

where type means the type of Luma sampling and

Chroma subsampling. To approximate the accurate

quality using the PSNR and the average bit-rate of

generated bitstreams, the weighted sampling better

identiﬁes the homogeneous area which characterizes

the coding efﬁciency.

2.3 Adaptive Thresholds

Since our algorithm avoids checking the RD costs

when early termination occurs, the values for the

thresholds (T ) play a central role in the trade-off be-

tween encoding quality and efﬁciency. With different

QP and CU sizes, the use of adaptive thresholds is

fundamental in H.265/HEVC as the number of possi-

ble partitioning and coding modes is so high that it is

impossible to set up appropriate static thresholds for

each of them. In order to ﬁnd suitable thresholds, we

ﬁrst analyse the SAD of different sizes of CU in ref-

erence software (see Fig. 3). When the CU texture is

complex, then CU is split into smaller subunits to ﬁnd

the best size but if the CU texture is ﬂat enough it will

not be divided further into subunits.

As shown in Fig. 3, coding with higher QP will

lose the detail in video reconstruction, which may

VISAPP 2017 - International Conference on Computer Vision Theory and Applications

(a) QP = 20

(b) QP = 40

Figure 3: Indicating the CU splitting by intra mode decision

with difference QP in HM reference software.

cause lots of homogeneous area that can be split into

bigger CU then coding with lower QP case. By this

reason, we consider the SAD as a thresholds (T ) to

determine the CU splitting and ﬁnd the relation about

the thresholds as T (QP,CU

size

). According to statis-

tics from various videos, the thresholds is adaptive to

video content, CU size and QP, given by,

T (QP, CU

size

) =



E (C) −



· CU

size

(5)

where E (C) is the expected value of sampling, and

the partial differential equation of Eq. 5 about QP and

size

as follows:

∂T

∂QP

= −

size

(6)

∂T

∂CU

size

= 2 ·



E (C) −



· CU

size

(7)

Therefore, the relationship between the SAD and CU

size is not very sensitive to QP. As the depth in-

creases, the CU will be evenly split into four sub-

CUs, while the thresholds are scaled down into ap-

proximately one quarter. Using large thresholds will

achieve a highly accurate decision but the complexity

reduction for intra mode decisions will be very small,

and using small thresholds will reduce the complexity

but lose accuracy. Thresholds should be determined

to provide a good trade-off between encoding qual-

ity and efﬁciency. In order to make the thresholds(T )

more adaptive to recent changes, a weighting function

is adopted which, similar to Eq. 4, corresponds to the

(sub)-sampling method. Thus, it smoothly allows up-

dating the expected values to better take into account

the most recent Luma and Chroma components, de-

ﬁned by

E (C) =

, w

) · (E (Luma) , E (Chroma))

+ w

(8)

3 IMPLEMENTATION

To verify our method, experiments were conducted

by using various test sequences under different QP

settings for investigating the RD cost distribution

for CUs resulting from the exhaustive search of the

H.265/HEVC Test Model (HM 16.9) and using our

modiﬁed HM software with the fast intra prediction

added.

3.1 Fast Intra Predication Walkthrough

The algorithm presented in this paper was imple-

mented in the HM 16.9 reference software. Since

the number of intra modes available for the predic-

tion of each CU can be reduced, the number of can-

didate modes selected in the HM 16.9 intra prediction

method is also modiﬁed. The overall proposed fast in-

tra predication process for each CU is now presented

as pseudo code, integrating the weighting sampling

and adaptive thresholds.

We ﬁrst start from the Planar and DC mode since

these modes occur with high probability. Then we

calculate the SAD of CU that is used to compare with

the thresholds (T ) by considering the current QP and

size

. If the SAD is smaller than the thresholds,

it means that the texture is ﬂat enough so that there

needs to be no further CU splitting, just ﬁnding the

smallest RD cost between intra Planar, DC and 33 an-

gular modes in the current depth layer. Otherwise,

it means that the texture is too complex to be intra

predicated in the current Depth, so we can skip the

remaining angular predication and there is no need to

check the intra mode in the current depth layer any-

more. We then consider the next Depth to ﬁnd the

smallest RD cost between intra Planar, DC and sum

of sub-CUs RD cost.

Fast Intra Prediction Algorithm with Enhanced Sampling Decision for H.265/HEVC

Algorithm 1: FastIntraPred(CU, QP, Depth).

Data: CU: object

Data: QP: int

Data: Depth: int

Result: RD

cost

: unsigned int

1 /* determine the best intra modes

and provide smallest RD cost */

2 begin

3 /* first find better intra mode

between Planar an DC */

4 RD

cost

←smaller RD cost between mode 0, 1;

5 SAD ← calculate the SAD of CU;

6 /* compare with thresholds

condition */

7 if SAD < T (QP, CU

size

) then

8 /* if condition is verified

that means there are lots

of homogeneous area */

9 for all the CU to be coded at Depth do

10 /* find best intra angular

modes */

11 RD

cost

←ﬁnd the smallest RD cost;

12 end

13 else

14 /* CU is evenly split into

four units as CU

0,1,2,3

15 RD

cost

← sum of FastIntraPred(CU

0,1,2,3

QP, Depth + 1);

16 end

17 return RD

cost

;

18 end

4 EXPERIMENT RESULTS AND

DISCUSSION

The H.265/HEVC reference software HM 16.9 was

modiﬁed to handle our proposed method, and a se-

ries of simulations were carried out to measure the

improvement offered by accurate bit estimation. For

most of the comparisons, the Bjontegaard PSNR and

bit-rate differences (BD-PSNR and BD-RATE) be-

tween the proposed and the reference method are

shown in the following.

Table 1: Mean of SAD of difference CU size and QP in HM

reference software.

64 × 64, 32 × 32, 16 × 16, 8 × 8,

depth = 0 depth = 1 depth = 2 depth = 3

20 481236.87 120007.25 30044.54 7479.20

24 472784.87 118100.85 29540.11 7030.81

28 464040.13 115765.73 29057.78 5899.01

32 455679.14 113168.00 28498.35 6827.27

36 448174.94 111326.90 28006.23 6987.15

40 437079.86 108763.22 27449.52 5667.41

As expected in Tab. 1 corresponding to Fig. 3,

QP values are taken into consideration as the QP will

scale the range of sample values. Note that these re-

sults are matched to Eq. 6 and 7, so the difference

between each sample and the mean of sampling CU

becomes smaller as QP increases.

4.1 Performance Veriﬁcation

The procedure detailed in (Senzaki et al., 2010) is

used to calculate BD-PSNR and BD-RATE with QP ∈

{

20, 24, 28, 32, 36, 40

}

. For all tests the the main-

proﬁle features of HM in progressive format are en-

abled, also 100 frames are coded (frame rates given

in the table captions) with one intra update every sec-

ond.

Table 2: H.265/HEVC, proposed vs. reference HM 16.9,

QCIF@30Hz, all Intra pictures with BD-RATE, BD-PSNR

and time reduction.

QCIF IIIII

BD-RATE BD-PSNR Time

(%) -Y (dB) Reduction (%)

akio +0.441 -0.015 -44.99

carp +0.471 -0.014 -45.12

coast +0.219 -0.007 -43.98

fore +0.042 -0.091 -43.86

mobile +0.123 -0.059 -43.21

news +0.404 -0.099 -42.71

paris +0.253 -0.077 -41.88

silent +0.108 -0.044 -42.90

Table 3: H.265/HEVC, proposed vs. reference HM 16.9,

4CIF@30Hz, all Intra pictures with BD-RATE, BD-PSNR

and time reduction.

4CIF IIIII

BD-RATE BD-PSNR Time

(%) -Y (dB) Reduction (%)

aspen +0.118 -0.005 -30.44

blue sky +0.447 -0.028 -49.90

controlled burn +0.176 -0.010 -42.42

crowd run +0.352 -0.021 -44.59

in to tree +0.103 -0.004 -42.35

life +0.176 -0.010 -47.66

park joy +0.181 -0.012 -44.56

riverbed +0.095 -0.004 -31.22

rush hour +0.086 -0.003 -46.70

sunﬂower +0.264 -0.015 -31.63

Tab. 2 and 3 results of the proposed method for

all intra coding, 4CIF and QCIF videos respectively.

As expected, since the proposed fast intra-prediction

mode decision and fast intra-transform skip-mode

decision have been added into the H.265/HEVC

scheme, and the weighted sampling and adaptive

thresholds condition can ﬁnd an approximate result

with HM reference software, so the BD-Rate just in-

creases by up to 0.5%.

VISAPP 2017 - International Conference on Computer Vision Theory and Applications

Table 4: H.265/HEVC, proposed vs. reference HM 16.9, QCIF@30Hz, all Intra pictures with difference QP and coding time

reduction.

QCIF IIII QP = 20 (%) QP = 24 (%) QP = 28 (%) QP = 32 (%) QP = 36 (%) QP = 40 (%) AVERAGE

akio -46.40 -45.83 -45.60 -44.06 -44.12 -43.92 -44.99

carp -45.88 -46.24 -44.67 -45.83 -44.77 -43.30 -45.12

coast -45.17 -46.08 -45.89 -41.61 -41.38 -43.74 -43.98

fore -46.62 -47.30 -46.14 -40.24 -41.99 -40.89 -43.86

mobile -44.88 -45.85 -44.45 -42.55 -40.11 -41.39 -43.21

news -44.22 -45.38 -45.07 -41.20 -41.14 -39.27 -42.71

paris -41.68 -44.37 -42.49 -42.92 -40.09 -39.72 -41.88

silent -44.57 -45.37 -41.21 -44.47 -43.30 -38.45 -42.90

Table 5: H.265/HEVC, proposed vs. reference HM 16.9, 4CIF@30Hz, all Intra pictures with difference QP and coding time

reduction.

4CIF IIII QP = 20 (%) QP = 24 (%) QP = 28 (%) QP = 32 (%) QP = 36 (%) QP = 40 (%) AVERAGE

aspen -31.91 -33.30 -33.72 -29.19 -27.80 -26.72 -30.44

blue sky -49.37 -48.45 -48.02 -51.52 -51.07 -50.97 -49.90

controlled burn -43.70 -36.18 -39.90 -43.19 -44.76 -46.76 -42.42

crowd run -42.58 -43.17 -48.39 -45.05 -44.92 -43.40 -44.59

in to tree -48.70 -37.62 -38.43 -42.19 -43.97 -43.17 -42.35

life -50.68 -43.32 -45.20 -48.94 -48.62 -49.18 -47.66

park joy -51.35 -47.75 -36.46 -42.11 -45.59 -44.08 -44.56

riverbed -38.73 -31.00 -29.38 -28.74 -28.80 -30.64 -31.22

rush hour -51.26 -49.97 -47.90 -47.87 -45.44 -37.78 -46.70

sunﬂower -36.34 -30.84 -30.49 -30.21 -30.77 -31.11 -31.63

As shown in Tab. 4 and 5, the encoding bit stream

size for different values of QP with QCIF and 4CIF

samples, and encoding time reduction is derived by

∆t =

proposed

−t

reference

× 100.00% (9)

where t

reference

and t

proposed

are the encoding time of

the original intra mode decision and the proposed fast

intra mode decision scheme. Results show that pro-

posed method can generate a speed-up on average of

40.0% and up to 45.0% with the BD-PSNR degrada-

tion less than 0.1dB in QCIF, with 4CIF the average

speed-up is 30.0% up to 50.0% with BD-PSNR degra-

dation of less than 0.03dB. As discussed in Sec. 2.3,

these simulation results are not very sensitive to the

QP value, but the percentage of time reduction should

decrease with increasing QP value. Because the tex-

tures could be more complex when using small QP

(which often requires more CU splitting) our pro-

posed approach can be effective to skip lots of an-

gular predication when the coding block is complex

enough.

As shown in Fig. 4 to 7, the performance of the

proposed method gives a more signiﬁcant gain in the

higher resolution sequence with all inter mode. Our

method performs better in terms of BD-RATE and

thresholds, and our results approximate very well to

the HM reference. It can be seen that the proposed

method achieves a reduction in encoding time of be-

tween 30.0% to 45.0%. According to the result for

each sequence, the average BD-RATE increase for

our method is 0.5% while the BD-RATE increase is

0.9% in (Zhang et al., 2016). Both (Zhang et al.,

2016) and our method provide a good trade-off be-

tween BD-PSNR and encoding time saving.

5 CONCLUSION

This paper proposed a fast intra prediction algorithm

to lead to faster encoding time that more accurately

approximates the original H.265/HEVC standard re-

sults. Our algorithm introduces the weighted sam-

pling and adaptive thresholds condition to determine

CU-splitting. The proposed algorithm offers no di-

vergence from the H.265/HEVC standards and can

be used in current systems. The result of the per-

formance is shown to offer a more signiﬁcant gain

in the higher resolution sequence with all inter mode.

Simulations also show that the proposed method can

speed up processing by 30.0% to 45.0% with little

BD-PSNR degradation and only 0.5% BD-RATE in-

crease while incurring a controlled precision and ad-

justable complexity overhead.

Fast Intra Prediction Algorithm with Enhanced Sampling Decision for H.265/HEVC

20 24 28 32

coding time (second)

reference

proposed

Figure 4: H.265/HEVC, coding time curves proposed vs.

reference HM 16.9, paris QCIF@30Hz, all Intra pictures.

20 24 28 32

coding time (second)

reference

proposed

Figure 5: H.265/HEVC, coding time curves proposed vs.

reference HM 16.9, carp QCIF@30Hz, all Intra pictures.

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