These are the slides of my presentation at SPIE Optics and Photonics 2011, August 2011, San Diego comparing rate distortion performance of VP8 (WebP and WebM) to major image and video compression standards from subjective evaluation point of view.
Rate distortion performance of VP8 (WebP and WebM) when compared to standard image and video compression techniques
1. Performance
analysis
of
VP8
image
and
video
compression
based
on
subjec8ve
evalua8ons
Francesca
De
Simone,
Lutz
Goldmann,
Jong-‐Seok
Lee,
Touradj
Ebrahimi
Mul@media
Signal
Processing
Group,
Ecole
Polythechnique
Fédérale
de
Lausanne,
Lausanne
SPIE
Op@cs+Photonics
2011
Applica@ons
of
Digital
Image
Processing
2. Outline
• Introduc@on
• Codecs
and
configura@ons
• Subjec@ve
quality
evalua@on
– MMSPG
test
environment
– Datasets
– Test
methodology
– Score
processing
and
analysis
• Results
– Rate
distor@on
plots
(RDP)
– Mul@ple
comparison
analysis
(MCA)
– Visual
samples
• Conclusions
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
2
2011
on
Subjec@ve
Evalua@ons
4. Introduc@on
• Trends
clearly
indicate
that
the
video
consump@on
over
the
Web
is
on
the
rise.
At
the
same
@me,
users'
demand
for
increased
resolu@on
and
higher
quality
is
growing.
• Alterna@ves
for
compression
of
digital
pictures
and
video
sequences:
– interna@onally
recognized
standard
solu@ons
– VP8
open
access
image
and
video
compression
• Our
study:
methodology
and
results
of
the
rate-‐distor@on
performance
analysis
of
VP8
based
on
subjec@ve
quality
assessment
experiments
– comparison
of
VP8
to
JPEG,
JPEG
2000,
JPEG
XR
for
4:2:0
image
compression,
to
H.264/AVC
and
HEVC
for
4:2:0
video
compression
– first
study
in
the
state
of
the
art
on
formal
subjec@ve
quality
evalua@on
of
VP8
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
4
2011
on
Subjec@ve
Evalua@ons
5. CODECS
AND
CONFIGURATIONS
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
5
2011
on
Subjec@ve
Evalua@ons
6. Image
codecs
and
configura@ons
• WebP
– Intra
frame
coding
of
VP8
ini@ally
developed
by
On2
– Use
of
Google
implementa@on
0.1.2
(hep://code.google.com/speed/webp)
– Two
configura@ons
were
considered:
default,
photo
– Varying
quality
factor
to
reach
different
target
bitrates
• JPEG
– Block
based
image
compression
standard
developed
in
1992
– Use
of
the
IJG
implementa@on
8c
(hep://ijg.org/)
– Coded
using
baseline
profile
and
by
varying
the
quality
factor
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
6
2011
on
Subjec@ve
Evalua@ons
7. Image
codecs
and
configura@ons
• JPEG
2000
– Wavelet
based
image
compression
standard
with
improved
func@onality
and
coding
efficiency
– Use
of
the
Kakadu
implementa@on
6.4.1
(hep://www.kakadusojware.com/)
– Encoding
in
YUV
4:2:0
format
with
necessary
color
conversion
and
sampling
– Rate
control
op@on
to
obtain
target
bitrates
• JPEG
XR
– Latest
image
compression
standard
published
in
2009
– Considered
two
implementa@ons
• JPEG
XR
reference
sojware
1.20
• Implementa@on
provided
by
Microsoj
– Varying
quality
factor
to
reach
target
bitrates
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
7
2011
on
Subjec@ve
Evalua@ons
8. Video
codecs
and
configura@ons
• WebM
– VP8
video
codec
ini@ally
developed
by
On2
and
recently
released
by
Google
– Use
of
libvpx
implementa@on
0.9.6
(hep://www.webmproject.org/)
– Use
of
best
configura@on
from
recent
MSU
codec
benchmark
– Contant
bitrate
(CBR)
mode
to
achieve
target
bitrates
• H.264/AVC
– Very
popular
video
coding
standard
completed
by
JVT
in
2003
– Considered
two
implementa@ons
• x264
implementa@on
r2019
(hep://www.videolan.org/developers/x264.html)
• JM
reference
sojware
18.0
(hep://iphome.hhi.de/suehring/tml/)
– Use
of
one
configura@on
for
each
implementa@on
• X264:
best
performing
configura@on
from
recent
MSU
codec
benchmark
and
constant
bitrate
(CBR)
mode
to
achieve
target
bitrates
• JM:
alpha
anchor
configura@on
corresponding
to
random
access
constraint
and
varying
QP
to
achieve
target
bitrates
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
8
2011
on
Subjec@ve
Evalua@ons
9. Video
codecs
and
configura@ons
• HEVC
– Recently
started
ini@a@ve
of
JCT-‐VC
to
develop
more
efficient
video
coding
standard
with
extended
and
new
coding
tools
– HM
sojware
(hep://hevc.hhi.fraunhofer.de/svn/svn_HEVCSojware/)
v3.2
– Use
of
the
high
efficiency
configura@on
sa@sfying
the
random
access
scenario
– Varying
QP
to
achieve
target
bitrates
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
9
2011
on
Subjec@ve
Evalua@ons
10. SUBJECTIVE
QUALITY
EVALUATION
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
10
2011
on
Subjec@ve
Evalua@ons
11. MMSPG
test
environment
• 3
high
quality
LCD
monitors
(Eizo
CG301W)
– na@ve
resolu@on
of
2560x1600
pixels
– gray-‐to-‐gray
response
@me
of
6
ms
– black-‐white-‐black
response
@me
of
12
ms
– calibrated
using
an
EyeOne
Display2
color
calibra@on
device
• 1
high
performance
video
server
with
SSD
• controlled
ligh@ng
system
(neon
lamps
with
6500
K
color
temperature)
• mid
gray
background
walls
and
curtains
• S a m e
e n v i r o n m e n t
u s e d
f o r
evalua@on
and
selec@on
of
best
performing
proposals
submieed
for
H E V C
s t a n d a r d i z a @ o n
[DeSimone2011]
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
11
2011
on
Subjec@ve
Evalua@ons
12. Image
dataset
• Use
8
images
from
the
JPEG
XR
Evalua@on
Dataset
• Resolu@on
of
1280x1600
pixels,
4:4:4
RGB
format
• 2
images
(p30,
cafe)
for
training
and
6
images
for
tes@ng
• Coded
using
4
different
codecs
and
6
overall
codec
configura@ons
• 5
different
bitrates
(bpp):
0.125,
0.250,
0.500,
0.750,
1.000
• A
few
codec
configura@ons
(JPEG,
VP8)
did
not
reach
the
lower
bitrates
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
12
2011
on
Subjec@ve
Evalua@ons
13. Video
dataset
• Use
5
video
from
the
VQEG
HDTV
SVT
Dataset
• Various
resolu@ons
available
(2160p50,
1080p50,
1080i25,
etc.)
• Spa@al
and
temporal
subsampling
of
1080p50
to
854x480@25
• 1
video
(ParkJoy)
for
training
and
4
videos
for
tes@ng
• Coded
using
4
different
codecs
and
4
overall
codec
configura@ons
• 5
different
bitrates
(kbps):
250,
500,
750,
1250,
2250
• A
few
codec
configura@ons
(VP8)
did
not
reach
the
lower
bitrates
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
13
2011
on
Subjec@ve
Evalua@ons
14. Subjec@ve
image
quality
evalua@on
• Adopted
methodology
which
was
recently
developed
within
the
context
of
the
JPEG
XR
evalua@on
[DeSimone2009]
• Modified
double
s@mulus
con@nuous
quality
scale
(DSCQS)
[ITU
BT.500-‐11]
• Implicit
reference
(SRC)
and
compressed
i m a g e
( H R C )
a r e
p r e s e n t e d
simultaneously
• The
quality
of
both
s@muli
is
rated
on
a
con@nuous
quality
scale
from
0
to
100
with
5
quality
levels
(bad,
poor,
fair,
good,
excellent)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
14
2011
on
Subjec@ve
Evalua@ons
15. Subjec@ve
video
quality
evalua@on
• Double
s@mulus
impairment
scale
(DSIS)
[ITU
BT.500-‐11]
• Explicit
reference
(SRC)
and
compressed
video
(HRC)
are
presented
sequen@ally
• Amount
of
ar@facts
with
respect
to
the
reference
is
rated
on
a
con@nuous
scale
from
0
to
100
with
5
impairment
levels
(very
annoying,
annoying,
slightly
annoying,
percep@ble,
impercep@ble)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
15
2011
on
Subjec@ve
Evalua@ons
16. Sessions
and
subjects
• Training
session
for
naïve
subjects
– Oral
instruc@ons
to
explain
the
subjec@ve
evalua@on
task
– Training
session
to
explain
methodologies
to
the
subjects
– Training
samples
for
each
quality/impairment
level
selected
by
expert
viewer
• Number
of
image
and
videos
samples
to
large
for
a
single
session
– Image:
4
sessions
of
14
minutes
each
– Video:
3
sessions
of
13
minutes
each
– 10
minutes
break
for
a
subject
between
two
sessions
• 3
dummy
pairs
and
1
repe@@on
for
stability
and
reliability
check
• 18
different
subjects
with
an
average
age
of
24
years
for
both
image
(5
women,
11
men)
and
video
(9
women,
9
men)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
16
2011
on
Subjec@ve
Evalua@ons
17. Score
processing
and
analysis
• Adopted
established
procedure
described
in
[DeSimone2011]
• Outlier
detec@on
for
each
session
in
order
to
discard
inconsistent
subjects
(no
outliers
detected
for
both
image
and
video)
• Computa@on
of
sta@s@cal
measures
for
each
combina@on
of
content,
coding
condi@on
and
bitrate
– Mean
opinion
scores
(MOS)
for
both
DSIS
and
DSCQS
– 95%
confidence
intervals
(CI)
using
Student’s
t-‐distribu@on
• Rate
distor@on
plots
(RDP)
for
each
content
across
all
bitrates
• Mul@ple
comparison
analysis
(MCA)
to
iden@fy
sta@s@cal
significant
differences
among
different
codecs
for
the
same
bitrate
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
17
2011
on
Subjec@ve
Evalua@ons
18. RESULTS
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
18
2011
on
Subjec@ve
Evalua@ons
19. Image
coding
RDP
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
19
2011
on
Subjec@ve
Evalua@ons
20. Image
coding
RDP
(bike)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
20
2011
on
Subjec@ve
Evalua@ons
21. Image
coding
RDP
(p01)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
21
2011
on
Subjec@ve
Evalua@ons
22. Image
coding
RDP
(p06)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
22
2011
on
Subjec@ve
Evalua@ons
23. Image
coding
RDP
(p10)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
23
2011
on
Subjec@ve
Evalua@ons
24. Image
coding
RDP
(p14)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
24
2011
on
Subjec@ve
Evalua@ons
25. Image
coding
RDP
(woman)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
25
2011
on
Subjec@ve
Evalua@ons
26. Image
coding
MCA
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
26
2011
on
Subjec@ve
Evalua@ons
27. Image
coding
MCA
(0.125
bpp)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
27
2011
on
Subjec@ve
Evalua@ons
28. Image
coding
MCA
(0.250
bpp)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
28
2011
on
Subjec@ve
Evalua@ons
29. Image
coding
MCA
(0.500
bpp)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
29
2011
on
Subjec@ve
Evalua@ons
30. Image
coding
MCA
(0.750
bpp)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
30
2011
on
Subjec@ve
Evalua@ons
31. Image
coding
MCA
(1.000
bpp)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
31
2011
on
Subjec@ve
Evalua@ons
32. Bpp
0.25
Original
JPEG
JPEG2k
JPEG-‐XR
VP8
(MS)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
32
2011
on
Subjec@ve
Evalua@ons
33. Bpp
0.5
Original
JPEG
JPEG2k
JPEG-‐XR
VP8
(MS)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
33
2011
on
Subjec@ve
Evalua@ons
34. Bpp
0.25
Original
JPEG
JPEG2k
JPEG-‐XR
VP8
(MS)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
34
2011
on
Subjec@ve
Evalua@ons
35. Bpp
0.5
Original
JPEG
JPEG2k
JPEG-‐XR
VP8
(MS)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
35
2011
on
Subjec@ve
Evalua@ons
36. Bpp
0.25
Original
JPEG
JPEG2k
JPEG-‐XR
VP8
(MS)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
36
2011
on
Subjec@ve
Evalua@ons
37. Bpp
0.5
Original
JPEG
JPEG2k
JPEG-‐XR
VP8
(MS)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
37
2011
on
Subjec@ve
Evalua@ons
38. Video
coding
RDP
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
38
2011
on
Subjec@ve
Evalua@ons
39. Video
coding
RDP
(CrowdRun)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
39
2011
on
Subjec@ve
Evalua@ons
40. Video
coding
RDP
(DucksTakeOff)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
40
2011
on
Subjec@ve
Evalua@ons
41. Video
coding
RDP
(InToTree)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
41
2011
on
Subjec@ve
Evalua@ons
42. Video
coding
RDP
(OldTownCross)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
42
2011
on
Subjec@ve
Evalua@ons
43. Video
coding
MCA
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
43
2011
on
Subjec@ve
Evalua@ons
44. Video
coding
MCA
(250
kbps)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
44
2011
on
Subjec@ve
Evalua@ons
45. Video
coding
MCA
(500
kbps)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
45
2011
on
Subjec@ve
Evalua@ons
46. Video
coding
MCA
(750
kbps)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
46
2011
on
Subjec@ve
Evalua@ons
47. Video
coding
MCA
(1250
kbps)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
47
2011
on
Subjec@ve
Evalua@ons
48. Video
coding
MCA
(2250
kbps)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
48
2011
on
Subjec@ve
Evalua@ons
49. Video
coding
RS
(CrowdRun
500
kbps)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
49
2011
on
Subjec@ve
Evalua@ons
50. Video
coding
RS
(CrowdRun
500
kbps)
NOTE:
for
this
content
webM
did
not
reach
the
target
bitrate
of
500
kbps
so
this
frame
has
been
extracted
from
the
webM
sample
with
bitrate
closest
to
500
kbps
(see
slide
39)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
50
2011
on
Subjec@ve
Evalua@ons
51. Video
coding
RS
(CrowdRun
500
kbps)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
51
2011
on
Subjec@ve
Evalua@ons
52. Video
coding
RS
(CrowdRun
500
kbps)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
52
2011
on
Subjec@ve
Evalua@ons
53. Video
coding
RS
(CrowdRun
500
kbps)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
53
2011
on
Subjec@ve
Evalua@ons
54. Video
coding
RS
(CrowdRun
1250
kbps)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
54
2011
on
Subjec@ve
Evalua@ons
55. Video
coding
RS
(CrowdRun
1250
kbps)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
55
2011
on
Subjec@ve
Evalua@ons
56. Video
coding
RS
(CrowdRun
1250
kbps)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
56
2011
on
Subjec@ve
Evalua@ons
57. Video
coding
RS
(CrowdRun
1250
kbps)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
57
2011
on
Subjec@ve
Evalua@ons
58. Video
coding
RS
(CrowdRun
1250
kbps)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
58
2011
on
Subjec@ve
Evalua@ons
59. Video
coding
RS
(CrowdRun
1250
kbps)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
59
2011
on
Subjec@ve
Evalua@ons
60. Video
coding
RS
(DucksTakeOff
500
kbps)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
60
2011
on
Subjec@ve
Evalua@ons
61. Video
coding
RS
(DucksTakeOff
500
kbps)
NOTE:
for
this
content
webM
did
not
reach
the
target
bitrate
of
500
kbps
so
this
frame
has
been
extracted
from
the
webM
sample
with
bitrate
closest
to
500
kbps
(see
slide
40)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
61
2011
on
Subjec@ve
Evalua@ons
62. Video
coding
RS
(DucksTakeOff
500
kbps)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
62
2011
on
Subjec@ve
Evalua@ons
63. Video
coding
RS
(DucksTakeOff
500
kbps)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
63
2011
on
Subjec@ve
Evalua@ons
64. Video
coding
RS
(DucksTakeOff
500
kbps)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
64
2011
on
Subjec@ve
Evalua@ons
65. Video
coding
RS
(DucksTakeOff
1250
kbps)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
65
2011
on
Subjec@ve
Evalua@ons
66. Video
coding
RS
(DucksTakeOff
1250
kbps)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
66
2011
on
Subjec@ve
Evalua@ons
67. Video
coding
RS
(DucksTakeOff
1250
kbps)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
67
2011
on
Subjec@ve
Evalua@ons
68. Video
coding
RS
(DucksTakeOff
1250
kbps)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
68
2011
on
Subjec@ve
Evalua@ons
69. Video
coding
RS
(DucksTakeOff
1250
kbps)
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
69
2011
on
Subjec@ve
Evalua@ons
70. CONCLUSION
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
70
2011
on
Subjec@ve
Evalua@ons
71. Conclusion
• VP8
image
compression
showed
performance
comparable
to
JPEG
XR
and
JPEG
2000,
all
significantly
outperforming
JPEG
compression.
• VP8
video
compression
showed
performance
compe@@ve
with
x264,
while
the
new
HEVC
technology
under
defini@on
usually
showed
the
best
performance.
• For
some
contents,
both
for
image
and
video
compression,
it
could
be
no@ced
that
the
current
implementa@on
of
VP8
seemed
to
have
difficul@es
reaching
low
bit
rates
condi@ons
that
most
other
codecs
reached.
• Future
studies
will
consider
other
resolu@ons
of
the
same
test
material,
as
well
as
other
subjec@ve
evalua@on
methodologies.
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
71
2011
on
Subjec@ve
Evalua@ons
72. References
• De
Simone,
F.,
Goldmann,
Baroncini
V.,
and
Ebrahimi,
T.,
“Subjec@ve
evalua@on
of
JPEG
XR
image
compression,"
SPIE
7443
(2009).
• De
Simone,
F.,
Goldmann,
L.,
Lee,
J.
S.,
and
Ebrahimi,
T.,
“Towards
High
Efficiency
Video
Coding:
Subjec@ve
Evalua@on
of
Poten@al
Coding
Technologies,"
Journal
of
Visual
Communica@on
and
Image
Representa@on
(2011).
SPIE
Op@cs+Photonics
Performance
Analysis
of
VP8
Image
and
Video
Compression
Based
72
2011
on
Subjec@ve
Evalua@ons
73. Thank
you
for
your
aeen@on!
Visit
us
at:
hep://mmspg.epfl.ch
Editor's Notes
Performance analysis of WebP and VP8 based on subjective evaluations Paper 8135-20 Time: 11:20 AM - 11:40 AMAuthor(s): Francesca De Simone, Jong-Seok Lee, Lutz Goldmann, TouradjEbrahimi, Ecole Polytechnique Fédérale de Lausanne (Switzerland)
Performance analysis of WebP and VP8 based on subjective evaluations Paper 8135-20 Time: 11:20 AM - 11:40 AMAuthor(s): Francesca De Simone, Jong-Seok Lee, Lutz Goldmann, TouradjEbrahimi, Ecole Polytechnique Fédérale de Lausanne (Switzerland)
Performance analysis of WebP and VP8 based on subjective evaluations Paper 8135-20 Time: 11:20 AM - 11:40 AMAuthor(s): Francesca De Simone, Jong-Seok Lee, Lutz Goldmann, TouradjEbrahimi, Ecole Polytechnique Fédérale de Lausanne (Switzerland)
Performance analysis of WebP and VP8 based on subjective evaluations Paper 8135-20 Time: 11:20 AM - 11:40 AMAuthor(s): Francesca De Simone, Jong-Seok Lee, Lutz Goldmann, TouradjEbrahimi, Ecole Polytechnique Fédérale de Lausanne (Switzerland)
Performance analysis of WebP and VP8 based on subjective evaluations Paper 8135-20 Time: 11:20 AM - 11:40 AMAuthor(s): Francesca De Simone, Jong-Seok Lee, Lutz Goldmann, TouradjEbrahimi, Ecole Polytechnique Fédérale de Lausanne (Switzerland)
Performance analysis of WebP and VP8 based on subjective evaluations Paper 8135-20 Time: 11:20 AM - 11:40 AMAuthor(s): Francesca De Simone, Jong-Seok Lee, Lutz Goldmann, TouradjEbrahimi, Ecole Polytechnique Fédérale de Lausanne (Switzerland)
Performance analysis of WebP and VP8 based on subjective evaluations Paper 8135-20 Time: 11:20 AM - 11:40 AMAuthor(s): Francesca De Simone, Jong-Seok Lee, Lutz Goldmann, TouradjEbrahimi, Ecole Polytechnique Fédérale de Lausanne (Switzerland)