Proceedings of the 12th IASTED International Conference
Signal and Image Processing (SIP 2010)
August 23-25, 2010 Maui, Hawaii, USA

A VC-1 TO H.264/AVC INTRA TRANSCODING USING ENCODING
INFORMATION TO REDUCE RE-QUANTIZATION NOISE
Takeshi Yoshitome, Yoshiyuki Nakajima, and Kazuto Kamikura
NTT Cyber Space Laboratories,
NTT Corporation,
Yokosuka-shi, 239-0847, JAPANABSTRACT
We propose a VC-1 to H.264/AVC intra transcoding
method. This method uses the encoding information froma VC-1 stream and keeps as many DCT coefficients of theoriginal VC-1 bitstream as possible. Experimental results
show that the proposed method improves PSNR by about
0.44-1.34 dB compared with a conventional method.

bit-streams. First, we discuss the noise suppression mechanism for progressive bit-streams. Next, we show the differences between the VC-1 and H.264/AVC standards, analyze how they affect the noise reduction, and propose a VC1 to H.264/AVC transcoding method. Finally, we describe
simulation results we obtained and compare the transcoding noises generated by our method and a conventional
method.

KEY WORDS
Transcoding, VC-1, H.264, Quantization noise, Encoding
information

1

Shoji Makino and Nobuhiko Kitawaki
Graduate School of Systems
and Information Engineering
University of Tsukuba
Tsukuba, Japan, 305-8573, JAPAN

2

Noise reduction mechanism using first encoding information

Introduction
Data flow examples of transcoding with and without first
VC-1 encoding information are shown in Fig. 1. The data
flow of Enc1→Dec1→Enc2→Dec2 is with encoding information, and that of Enc1→Dec1→Enc3→Dec3 is without it. For simplicity, the macro-block (MB) size is 2x2.
In the first VC-1 encoding, an input MB that includes the
pixel values (A, B, C, and D) is processed by intra prediction and orthogonal transformation. Then, the transformed
DCT coefficients (43, 31, 24, and 13) are quantized by aquantization step ∆=10. The quantized DCT coefficients(4, 3, 2, and 1) are converted to bitstream#1 by variable
length coding (VLC). The quantization from (43, 31, 24,
and 13) to (4, 3, 2, and 1) adds quantization noise so thatthe decoded MB pixels (a, b, c, and d) differ from the input
MB pixels (A, B, C, and D). Until this point, transcoding
both with and without encoding information does the samework.
In the transcoding without encoding information,
Enc3 searches the best motion vector to minimize motion
estimation error (p’, q’, r’, and s’). If the motion search
performance of Enc3 is higher than that of Enc1, Enc3 canreduce its motion estimation error (p’, q’, r’, and s’) compared with Enc1’s motion estimation error (A’, B’, C’, andD’). In the same way, if the orthogonal transformation performance of Enc3 is higher than that of Enc1, Enc3 canreduce the size of bitstream#3 compared with that of bitstream#1. However, the re-quantization noise occurs when
DCT coefficients (34, 33, 14, and 4) are quantized to (3, 3,
1, and 0). In short, Enc3 adds re-quantization noise even
if the bitstream becomes smaller. On the other hand, in thetranscoding with encoding information, every type of en-

Recently, it has become important to re-compress video
contents to decrease bitstream size by using a higher performance encoding tool such as H.264[2]. In this decade,a number of video transcoding studies have been reported[5, 6, 7] that aim to reduce the H.264 encoding time, which
is several times larger than that of old compression tools,
such as MPEG-2[1] and VC-1[3]. For example, [8, 9]
have reported that the use of an MPEG-2 motion vector
and compression mode information helps to reduce the processing time of H.264 re-encoding. A direct mathematicalmatrix conversion from the 8x8 real DCT of MPEG-2 tothe 4x4 integer DCT of H.264 has also been reported[10].
However, the image quality obtained with these approaches
becomes lower than that of conventional approaches using
a directly connected MPEG-2 or VC-1 decoder and H.264
encoder.
We have focused on the fact that all decisions of thefirst encoding procedure are repeated during the transcoding procedure to reduce re-quantization noise[4], where”all decisions” means decisions on picture type, macroblock type, motion vectors, DCT type, and so on. This
noise suppression mechanism is effective when the compression standards of the first and second encoding are
identical, such as for MPEG-2/MPEG-2 or H.264/H.264
conversion. We have tried to expand this approach to apply it to MPEG-2/H.264 transcoding for progressive bitstreams[11, 12], because the image quality obtained withthis approach may become higher than that of conventional
method mentioned above. This paper reports our attempt
to apply this noise suppression mechanism to VC-1 intra

710-020170

Input MB

Enc1

B

C

D

c

d

ME
(left)

Enc2

Quantized
DCT
coefficient

A’ B’

42 31

4

3

2

1

C’ D’

a’

b’

c’

d’

a’

b’

c’

d’

DCT
(8x8)

24 13

Q
( =10)

40 30

re-useb

DCT
coefficient

re-useaME(left)

re-useDec1

AIntra-prediction
Error

20 10

DCT
(8x8)

Q
40 30
( =10)
20 10

Table 1. Major differences between VC-1 and H.264 forintra encoding

VLC
Bit
stream
#1

4

3

2

1

Intra prediction
block size
Directionof intraprediction
Orthogonaltransformation
Size of orthogonaltransformation
Specification ofquantization matrix
Interval ofquantization stepDeadzone inquantization

VLD

Almost same
4

3

2

1

VLC
Bit
stream
#2

Dec2

a

b

a’

b’

40 30

4

3

c

d

c’

d’

20 10

2

1

VLD

No quantization noise
ME
(up)

Enc3

p’

q’

r’

s’

DCT
(4x4)

Q
34 33
( =10)
14 4

3

3

1

0

VLC
Bit
stream
#3

Dec3

p

q

p’

q’

30 30

3

3

r

s

r’

s’

10

1

0

0

VLD

VC-1

H.264

8x8

no

4x4
8x8
8 directions
without
no-pred.
integerDCT
8x8(*1)4x4
yes(*1)linearlogarithmic?

yes/no
(*2)

no

?

left
up
no-pred.
unique8x8

H.264
re-enact
OK

?
?
OK
OK

(*1): only high-profile(*2): depends on encoder setting

Quantization noise
Transcoding with Enc1’s info. : Enc1+Dec1 + Enc2+Enc2
Transcoding without Enc1’s info. : Enc1+Dec1 + Enc3+Dec3

Figure 1. Transcoding with and without first VC-1 encoding information

first encoder is VC-1 and the second encoder is H.264. The
two encoders are similar but are not upper compatible. The
differences between them are listed in Table 1. The ”ok”
means that H.264 can recreate the same VC-1 function in
the table. The ”?” means that H.264 can process the function only in a similar but not identical way that VC-1 does.
The following four functions are not exactly the same between VC-1 and H.264, and are not investigated: (1) Intra
prediction, (2) Available quantization step, (3) Orthogonaltransformation, (4) Quantization with and without deadzone. In the next section, we describe these differencesin detail and show a way to overcome them.

coding information, such as MB type, motion vector, DCT
mode, and quantization step, is re-used in Enc2. This re-useof encoding information does not produce any significant
difference between motion compensation errors of the firstencoding and those of the second encoding, nor does it produce any notable difference between the DCT coefficientsof the two encodings. This means that the re-quantizationnoise added in the second encoding phase is almost zero.
As a result, the same motion estimation error and the same
DCT quantization coefficients are obtained. Unfortunately,
there is no bit reduction because the sizes of bitstream#1
and #2 are almost the same when these encodings make useof the same compression tool. But transcoding using different compression tools, such as VC-1 to H.264 transcoding, may reduce the bitstream size because the performanceof H.264’s entropy coding (CABAC) is higher than that of
VC-1’s entropy coding (VLC).

3

3.1

Intra prediction

There are three intra prediction modes, including the no
prediction mode, in the VC-1 specification. Adjoining pixels in the upper or left blocks are referred to in this prediction. H.264 has eight prediction angles to increase compression efficiency. The two prediction modes (mode=up
and mode=left) in VC-1 can be converted to the mode=0
and mode=1 in H.264, as shown in Fig.2. But it is impossible to exactly equalize the VC-1 and H.264 intra blocks
when VC-1 selects the no prediction mode because H.264
does not have this mode. The best way to imitate this mode
is to use the DC prediction mode in H.264. If this is used,
the orthogonal transformation will change only the DC coefficient. None of the coefficients except the DC one areaffected by the difference between the VC-1 and H.264
predictions. Intra prediction mode mapping from VC-1 to
H.264 is shown in Table2.

Differences between VC-1 and H.264

As depicted in Fig. 1, there is a close resemblance between
the decoded images of the first and second decoders when
the compression standards of the first and second encodings are exactly the same. To re-enact the effect of thisnoise reduction mechanism, we must control H.264 behavior to imitate VC-1 behavior as much as possible when the

171

Up

5

0

No
prediction
8

by one. Thus, there are 39 available quantization steps in
VC-1. In contrast, there are 51 available quantization steps
in H.264. The minimum value is 0.625 and the maximum
value is 224. The ratio of the two proceeding quantization
steps is an almost constant value in H.264.
Available quantization steps in VC-1 and in H.264 areshown in Table3. ∆ value of ”O” means there is availability. There are 14 cases in which VC-1 can specify ∆ and
H.264 can not. In these cases, the nearest quantization stepof H.264 is used in place of that of VC-1. The ratio difference between the VC-1 and H.264 quantization steps isfrom 3.2% to 8.3%. The negative effects caused by thisdifference will be described in detail in Section 5.2. The
amount of this difference is within the acceptable level.

7

4

3

6
Left
1
8

8 pixcels

VC-1

mode 2:DC prediction

H.264

Figure 2. Intra 8x8 prediction of VC-1 and H.264

Table 2. Intra prediction mode mapping from VC-1 to
H.264
VC-1 prediction mode
Up
Left
No prediction

3.2

H.264 prediction mode012 (DC)

3.3

Orthogonal transformation

In VC-1 intra compression, the orthogonal transformation
which has 8x8 size is used. The transformation, and thequantization and de-quantization, are given in the following
Eqs. (1) and (2) :Available quantization step size

The derivation manner from the quantization code to thequantization step in VC-1 is similar to that of MPEG2 when the parameter q scale type is equal to zero in
MPEG-2. The quantization step equals the quantization
code in MPEG-2. The quantization step equals twice thequantization code in VC-1. Additionally, VC-1 can also
use the quantization steps, (3, 5, 7, .. , 15 , 17 ) using its 1bit
parameter, HALFQP , which increases the quantization step

H.264
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O

VC-1
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O

∆
20
22
24
26
28
30
32
34
36
38
40
42
44
46
48
50
52
54
56
58
60
62
64
72
80
88
104
112
128
144
160
176
208
224
-

H.264
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
-

VC-1
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
O
-

(1)

Yd = Dequantvc1 ( Quantvc1 (Y ))(2)

The inverse orthogonal transformation in VC-1 is describedin Eqs. (3) and (4):E = (Yd · V + 4) >> 3

(3)

X̂ = V t · E + C8 · 18

(4)

where X is the input image, Y is the transformed coefficient, N is the normalization matrix, the operator “V t ”
represents a transposition of matrix V , the operator “>>”represents an arithmetic right shift performed by entrywiseon a matrix, the operator “·” represents matrix multiplication, the operator “◦” is a component-wise multiplication, Yd is the de-quantized transformed coefficient thatwas quantized, X̂ is the decoded image, V is the transfer matrix, Dequantvc1 () and Quantvc1 () are the quantization and de-quantization functions of VC-1, V t is thetransposed matrix of V , E is an intermediate matrix, C8 =(0 0 0 0 1 1 1 1)t , and 18 is an eight length row vectorof ones. The (i,j) component of V is described in Eq.5 asfollows:
 12
12
12
12
12
12
12
12 

Table 3. Available ∆ in VC-1 and in H.264∆
0.625
0.68750.8125
0.875
1
1.125
1.25
1.375
1.625
1.75
2
2.25
2.5
2.75
3
3.25
3.5
4
4.5
5
5.5
6
6.5
7
8
9
10
11
12
13
14
15
16
17
18

Y = (V · X · V t ) ◦ N

16

 16
V = 15
 12

9
6
4

15
6
−4
−12
−16
−16
−9

9
−6
−16
−12
4
16
15

4
−16
−9
12
15
−6
−16

−4
−16
9
12
−15
−6
16

−9
−6
16
−12
−4
16
−15

−15
7
4
−12
16
−16
9

−16
16 
−15 
12 
−9
6
−4

(5)

The (i,j) component of V is described as follows:
Nij = cj cti( 8
where c = 288

172

8
289

8
292

8
289

8
288

8
289

8
292

)

B

C

VC-1
Tran/Q/IQ/ITranA

VC-1
Tran/Q/IQ/ITran

50

45

B

C

H.264(4x4)Tran/Q/IQ/ITran

A

45

40

45

40

PSN

35

PSN

R(A,

(A,C

)

35

PSN

R(A,
B)

B)

30

PSN

R(B,

5

10

15 20
Step size

25

30

35

H.264(8x8)Tran/Q/IQ/ITran

C

R(B,

PSN

R(A
,C)

35

C)

30
0

PSN

B

C)

40

PSN
R

R(A

,C)

VC-1
Tran/Q/IQ/ITran50
PSNR (dB)

PSNR (dB)50

VC-1
Tran/Q/IQ/ITranPSNR (dB)

A

PSN

R(A,

B)

30

0

5

Figure 3. PSNR of VC- 1/VC- 1
re-encoding

10

15 20
Step size

25

30

Figure 4. PSNR of VC-1/H.264(H=4x4) re-encoding

0

5

10

15 20
Step size

25

30

35

Figure 5. PSNR of VC-1/H.264(H=8x8) re-encoding

To compare the 64 components of Y and Z, an example image is processed by two consecutive stages using
mathematical operations. In the first stage, the image isprocessed by the VC-1’s transformation , the quantizationand de-quantization, and the VC-1’s inverse transformationin Eq.(1) - Eq(4). In the second stage, the output image ofthe first stage is processed by following the different functions.

In H.264, if we assume that Z is the integer DCT output and H is the integer DCT matrix, DequantH264 ()and QuantH264 () are the quantization and de-quantization
functions of H.264, and Zd is the de-quantized integer DCT
coefficient that was quantized. Then the integer DCT, thequantization and de-quantization, and the inverse integer
DCT are described in Eqs. (6), (7), (8) below:
Z = HXH t

35(6)
1. VC1-Trans/quantize/de-quantize/VC1-InverseTrans(Eq.1-Eq.4, PSNR is shown in Fig. 3)

Zd = DequantH264 ( QuantH264 (Z))(7)

tX̂ = H Zd H

2. 4x4int-DCT/quantize/de-quantize/4x4int-IDCT(Eq.6-8 with N=4 . PSNR is shown in Fig. 4)(8)

H with N=4 is shown in Eq. (9).


1

√2


2

5
H =
1

√ 2
1
10

1

√ 2

1
10
− 12
√
− 25

1

√ 2
1
− 10
− 12
√
2
5


1
√2

− 25 

1 
√ 2
1
− 10

H with N=8 is shown in Eq.(10).

a
a
a
a
a
a
a
5c
3c
3c
3c
3c
5c
 3c
−
−
4
4
8
8
4
4
 2
b
b
 b
− 2b
−b
−b − 2b
2
2
 5c
3c
3c
3c
3c
3c
3c

−8 −2 −4
−2
4
4
8
H =
 a −a −a
a
a
−a −a
 3c
3c
3c
5c
3c

− 5c
− 3c
8
4
4
8
2
 4b − 2bb−bb −2 −2
b
−b
2
3c
5c
3c
3c
− 3c
− 3c
− 5c
8
4
4
2
2
4
4
√
where

a=

1
, b=
8

√

3. 8x8int-DCT/quantize/de-quantize/8x8int-IDCT(Eq.6-8 with N=8 . PSNR is shown in Fig. 5)

1
, c=
5

√

In the second stage, the quantization and dequantization use the same quantization step used in the firststage. The quantization and de-quantization without deadzone are used because only the difference between the orthogonal transformations of VC-1 and H.264 reflects the
PSNR results. From Fig. 3 to Fig. 5, A means the input
image, B means the decoding image of the first encoding,
C means the decoding image of the second encoding, and
PSNR (A, B) means the PSNR value between A and B. Figure 3 shows that PSNR (A, B) equals PSNR (A, C). This
indicates that the repetition of orthogonal transformationsof VC-1 does not decrease the PSNR, as mentioned in Section 2. We omitted PSNR (B, C) from Fig. 3 because there-quantization noise showed the lowest value and PSNR
(B, C) rose to over 100 dB. When the second encoding is
the 4x4 integer DCT of H.264 (Eq.(6) - Eq.(8), N=4), the
PSNR (A, B) is slightly higher than the PSNR (B, C) shownin Fig.4, because the amount of quantization noise of the

(9)

a




− 3c
2 
b

5c 
−4 
a

3c 
−4 
b 
2
3c
−8

32
289

(10)

173

second encoding is slightly lower than that of the first encoding. This indicates there is a slight similarity between
the VC-1’s 8x8 transform matrix and the H.264’s 4x4 transform matrix. The final PSNR (A, C) is lower than PSNR
(A, B) by nearly 3 dB because the similarity is not large.
On the other hand, when the second encoding is the 8x8
integer DCT of H.264 (Eq. (6) - Eq. (8),N=8), PSNR (A,B) < PSNR (B, C) and the difference becomes larger as ∆becomes larger, as shown in Fig. 3. This indicates there
is a large similarity between the VC-1’s 8x8 transform matrix and the H.264’s 8x8 transform matrix. Figure. 5 also
shows that a large ∆ decreases the PSNR reduction causedby the difference between the VC-1’s 8x8 transformationand the H.264’s 8x8 transformation. The differences between PSNR (A, B) and PSNR (A, C) are (1.2, 1.2, 1.0,
0.8, and 0.3) when ∆ = (2, 4, 8, 16, and 32).
3.4

X -2 = -25

X0 = 0

X1= 15 X2 = 25

Quantized
outputQuantization
bin

(a)
b -2
-30

b -1

-20

b0

-10

0

b1

10

b2

20

Quantized
output

(b)
b -2
-30

-20

b -1

b0

-10

0

b1
10

Quantization
bin

b2
20

Input

30

X -2= -20 X -1 = -10 X0 = 0 X1= 10 X2 = 20

30

Input

Figure 6. Examples of uniform and non-uniform
quantization

Table 4. Proposed VC-1/H.264 intra transcoding rule

Quantization

For intra MB quantization, VC-1 can use the two different
quantization modes shown in Fig. 6. Figure 6 (a) showsa non-uniform quantization and Fig. 6 (b) shows a uniform quantization. Xi means quanization output and bimeans quanization bin. If the input is in bi , the quantized
output equals Xi . In a uniform quantization, the size ofquanization bin is constant. In a non-uniform quantization, the size of b0 is larger than that of the others. The
non-uniform quantization decreases the bit-stream size because it increases the number of X0 . The uniform quantization enables accurate quantization, so it is suitable forhigh bitrate encoding. H.264 uses only uniform quantization that has no deadzone. The noise reduction effect, mentioned in Section.2, decreases when VC-1 selects the nonuniform quantization. Although the VC-1 specification allows the use of these two quantization modes in the same
intra picture, most VC-1 bit-streams are quantized using
the uniform quantization because the intra picture needs tobe more accurate in terms of encoding quality than the inter picture. The negative effects caused by this uniformity
difference between the first VC-1 encoding and the second
H.264 re-encoding will be described in detail in Section 5.
The amount of this difference is within the acceptable level.

4

X -1= -15

MB type
Encoder flag setting

VC-1
simple/main/
advanceup
left
no pred.
intra-

Quantization matrix
Quantization step-

ProfileIntra
prediction

H.264
high
0
1
2(DC)
I8x8
transf orm size f lag=1flat matrix
nearest to VC-1’s stepis either 4x4, 8x8, or 4x4. The proposed method uses only
the I8x8 mode because its DCT matrix size is the same asthat of VC-1.

5

Simulation

5.1

Conditions

We used experimental simulation to compare our proposed
method with a conventional method. The conventional
method we used is the ordinary VC-1/H.264 transcoding
method. It does not re-use the first encoding information,and but does intra MB mode selection. The VC-1 sample program[14] was used for first encoding under the following conditions: The quantization step ∆ was fixed in
the picture. VC-1 encoding was done twice for all simulations using uniform and non-uniform quantization. We
modified the VC-1 decoder in ffmpeg[15] to extract the first
VC-1 encoding information from the VC-1 bitstream. The
jm12.1 was used for the conventional second H.264 encoding under the following conditions: The profile was highprofile, the RD optimization was off, the UseHadamrd wason, and the quantization matrix was the H.264 default setting matrix. The conventional second encoding had no restrictions with regard to selecting MB mode and intra prediction mode, so its output bit-streams included the all-MB

Proposed Method

The proposed VC-1 to H.264 conversion rules are listed inTable 4. The H.264 high profile enables the use of an 8x8
integer DCT that has the same orthogonal transformation
size as that of VC-1. All coefficients of the H.264 quantization matrix are set to sixteen to equalize the flat VC-1’squantization characteristics. The proposed method chooses
the H.264’s quantization step whose value is nearest to thatof the VC-1’s quantization step. The intra prediction modeis set to the DC mode to imitate the VC-1 standard. The
H.264 standard can select one of the intra MB modes fromamong I4x4, I8x8, and I16x16 and each DCT matrix size

174

33

38

7

10
11

35

Proposed
Conventional
Input VC-1( 1 = 8)

14
18 16

33
32

32

13

34

20

0

20

40

18
2 =22

31
30

20

9
13

29.5

32

0

10

20

29

30 40 50 60
Picture Bits (KByte)∆1 = 822

11 10

Proposed
Conventional
Input VC-1( 1 = 16)

36

70

8
13 11
7 6
10 9

26

26

29
28

30

5.5

14

28

60 80 100 120 140
Picture Bits (KByte)

7 6.5

PSNR (dB)

PSNR (dB)36

16

PSNR (dB)

4 3.25 2.75 2.5
4.5 3.5
2= 8
5.5 5
9 6.5

37

8

20

2 =32 28

28.5

16

18

28
36

27.5

Proposed
Conventional
Input VC-1( 1 = 26)

27
40

26.5
26

80

14

0

10

20
30
40
Picture Bits (KByte)∆1 = 1650

60∆1 = 26

Figure 7. PSNR of proposed method and conventional method when VC-1 uses uniform quantization

36

32

2 =16

34
33

14
13

6.5 5 4.5

8

26
28

30

0

20

2 = 32

Proposed
Conventional
Input VC-1( 1 = 8)2240

60 80 100 120 140
Picture Bits (KByte)∆1 = 8

28.5

5.5

28

22 20 18 13

10

20

22
36 28

14 13 11 10 9

8 7 6.5 5.5 5

16

44 26

27

26.5

Proposed
Conventional
Input VC-1( 1 = 16)40

0

2 = 52

27.5

36

28
27

7 6.5

26 16

29

20

31

14 1110 9

30

18

32

8

31

PSNR (dB)

11 10 97

PSNR (dB)

PSNR (dB)35

29

4 3.5 2.75 2.530 40 50 60
Picture Bits (KByte)∆1 = 167080

Proposed
Conventional
Input VC-1( 1 = 26)

26
25.5
25

0

10

20
30
40
Picture Bits (KByte)

5060∆1 = 26

Figure 8. PSNR of proposed method and conventional method when VC-1 uses non-uniform quantization

method. The quantization step of the first encoding, ∆1 ,was set to 8, 16, or 26. That of the second encoding, ∆2 ,varied from 0.625 to 52. The x-axis means PSNR and the yaxis means picture bits. When input streams were encodedusing uniform quantization, Fig. 7 shows that the proposed
method showed two peaks when ∆2 =∆1 and ∆2 =0.5∆1 .
At these points, the PSNR of the proposed method washigher than that of the conventional method from about
0.98-1.28 dB. The PSNR of the proposed method drops
when 0.5∆1 < ∆2 < ∆1 and ∆1 < ∆2 < 2.0∆1 . This
PSNR drop is similar to that reported in MPEG-2/MPEG-2transcoding. Figure 7(a)-(c) shows that the PSNR of the
proposed method is always higher than that of the conven-mode and DC prediction, and also included all available
DCT sizes. We used the modified jm12.1, which can input
the first encoding information, for our proposed transcoding method. The quantization step ∆ was fixed for the simulations of both the conventional and proposed methods.
5.2 Results for VC-1 bitstreams encoded by uniform
quantization
The PSNR of transcoding from input VC-1 bitstreams encoded using uniform quantization to H.264 bitstreams areshown in Fig.7(a)-7(c). The solid line indicates the proposed method and the dotted line indicates the conventional

175

Table 5. Comp. ratio and PSNR of proposed method when VC-1 used uniform quantization
Image
Cheer
LeaderBus
MobileandCalendarInput VC-1
∆ PSNR(dB)
8 37.28
16 32.77
26 29.91
8 36.99
16 32.26
26 29.30
8 35.96
16 30.75
26 27.44

MB size
(kB)
84.9
49.6
31.8
79.7
47.3
28.1
124.6
77.7
51.1

Proposed transcoder
MB sizecomp. PSNR
(kB)
ratio
(dB)
82.00
0.966 36.44
45.30
0.914 32.24
29.44
0.925 29.20
72.66
0.911 36.20
39.90
0.844 31.80
24.15
0.861 28.76
120.64
0.968 34.71
72.47
0.933 30.10
48.01
0.939 26.75

Conv.
PSNR
(dB)
35.29
30.96
28.22
35.14
30.84
28.19
33.86
28.76
25.72

PSNR

diff.
(dB)
1.16
1.28
0.98
1.05
0.96
0.56
0.85
1.34
1.03

Table 6. Comp. ratio and PSNR of proposed method when VC-1 used non-uniform quantization
image
Cheer
LeaderBus
MobileandCalendarInput VC-1
∆ PSNR(dB)
8 35.45
16 31.01
26 28.17
8 35.01
16 30.29
26 27.53
8 34.05
16 28.71
26 25.41

MB size
(kB)
68.6
38.4
23.8
65.0
35.5
19.7
105.2
61.2
36.9

Proposed transcoder
MB sizecomp. PSNR
(kB)
ratio
(dB)
61.30
0.893 34.31
33.02
0.859 30.21
20.77
0.872 27.54
53.98
0.830 34.01
27.26
0.768 29.67
15.43
0.782 27.06
94.05
0.894 32.54
53.63
0.877 27.85
33.29
0.902 24.86

tional method. As ∆2 becomes smaller, the PSNR improvement of the proposed method decreases because thenoise reduction effect mentioned in Section 2 maximizes
when ∆1 = ∆2 . As we mentioned in Sec.3.2, if the firstencoding VC-1 uses the quantization step ∆1 that is notallowed in H.264, an approximate quantization step must
be used in H.264 transcoding. However, the difference
between the true value and the approximation value is ashigh as 8.3%. The range in which the proposed method
is superior to the conventional method exceeds this 8.3%
error in Fig.7(a) - (c). This indicates that the proposed
method is superior to the conventional method even if theapproximate quantization step is used in H.264 transcoding. The compression ratio and PSNR of the proposed
method when the quantization step ∆2 is equal to ∆1 arelisted in Table 5. The conventional PSNR column is the interpolation value when the conventional method generates
the same bitstream in terms of size. These interpolation
values were calculated using the simulation results of theconventional method. The PSNR of the proposed method
is about 0.56-1.34 dB better than that of the conventional
method when the quantization step ∆2 is equal to ∆1 . The
re-compression ratio of the H.264 bitstream size to the VC1 bitstream size ranges from 0.844 to 0.968.

5.3

Conv.
PSNR
(dB)
33.42
29.25
26.70
33.26
29.15
26.62
31.75
26.82
23.96

PSNR

diff.
(dB)
0.89
0.97
0.84
0.75
0.52
0.44
0.79
1.03
0.91

Results for VC-1 bitstreams encoded using nonuniform quantization

The PSNR values of transcoding from input VC-1 bitstreams encoded using non-uniform non-quantization to
H.264 bitstreams are shown in Fig.8(a)-8(c). When thefirst VC-1 encoding is done by non-uniform quantization,
the PSNR improvement is less than that obtained with uniform quantization. Figure 8 shows the PSNR values obtained with the proposed method when ∆2 =θ∆1 (θ=1.11.3) . This shift in the optimum ∆2 was generated by thedifference between the quantization uniformities of VC-1
and H.264. This phenomenon was also reported in MPEG2/H.264 inter transcoding research [13]. Despite the difference in quantization uniformity, Fig.8(a)-(c) shows that the
PSNR of the proposed method is always higher than that of
the conventional method. The compression ratio and PSNR
of the proposed method when the quantization step ∆2 isequal to 1.2∆1 are listed in Table.6. At these shifted points,
the PSNR of the proposed method is higher than that of theconventional method from about 0.44-1.03 dB.

6Conclusion

We proposed a re-quantization noise reduction method for
VC-1 to H.264 intra transcoding. This method uses encoding information from the VC-1 stream and keeps as many

176

DCT coefficients of the original VC-1 bitstream as possible. We analyzed the difference between VC-1 and H.264
regarding the intra prediction and quantization steps and orthogonal transformation to reduce the re-quantization noisein H.264. Experimental results showed that the proposed
method improves PSNR by about 0.44-1.34 dB comparedwith the conventional method. The advantages of the proposed method are that it not only results in high PSNR but
also that it does not require complex calculation to selectan MB mode and an intra prediction mode.

[11] T. Yoshitome, et al, ”A study of MPEG-2 to H.264 Intra Transcoding for Progressive Contents” ITE Journal, 62,11,pp1819-1824 (Nov. 2008) (in Japanese)[12] T. Yoshitome, K. Kamikura, and N. Kitawaki, ”A Requantization Noise Reduction Method in MPEG-2 to
H.264 Intra Transcoding” IEEE Symposium on Industrial Electronics and Application (ISIEA 2009),
Kuala Lumpur, Malaysia, pp.94-99, Oct 4-6, 2009[13] T. Yoshitome, et al, ”An MPEG-2 to H.264 Transcoding Method Preserving DCT Information for Progressive Contents” ITE Journal, 63,6,pp.837-846 (June2009) (in Japanese)

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