EECE 541 Multimedia Systems Project Proposal: Logo ... - Courses

EECE 541 Multimedia Systems
Project Proposal:
Logo Insertion for H.264 Compressed Video
Instructor: Dr. Panos Nasiopoulos
Group members: Gopichand Yalamanchili (20322061)
Abdul K.Murad Agha (80089972)
Teresa Zhou (74417999)
Di Xu (31679079)
February 26, 2008
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TABLE OF CONTENT
TABLE OF CONTENT ............................................................................................................................... 2
I. INTRODUCTION............................................................................................................................... 3
II. NOTATION AND TERMINOLOGY............................................................................................... 3
III. VIDEO CODING AND TRANSCODING................................................................................... 4
A. BASIC TRANSCODING STRUCTURES .................................................................................................. 4
B. MPEG2 VIDEO CODING.................................................................................................................... 6
C. H.264 VIDEO CODING....................................................................................................................... 6
C.1. INTRA PREDICTION............................................................................................................................. 6
C.2. INTER PREDICTION ............................................................................................................................. 6
IV. EXISTING METHODS FOR MPEG2 COMPRESSED VIDEO LOGO INSERTION.......... 7
A. LOGO INSERTION POSITION............................................................................................................... 7
B. LOGO INSERTION IN SPATIAL DOMAIN.............................................................................................. 7
C. LOGO INSERTION IN TRANSFORM DOMAIN ...................................................................................... 9
D. LOW COST AND EFFICIENT LOGO INSERTION.................................................................................. 10
D.1. LOGO-AFFECTED RANGE OF FRAMES IN THE TEMPORAL DOMAIN .................................................. 10
D.2. MOTION INFORMATION ADJUSTMENT IN THE LOGO AND LOGO-AFFECTED PARTS.......................... 11
E. QUANTIZATION SCALE ADJUSTMENT ............................................................................................. 12
E.1. CONSTANT QUALITY AT THE LOGO PART......................................................................................... 13
E.2. BIT REALLOCATION.......................................................................................................................... 13
V. MAIN ISSUES FOR H.264 COMPRESSED VIDEO LOGO INSERTION ............................... 13
REFERENCES ........................................................................................................................................... 16
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I. INTRODUCTION
Transcoding is the process of converting the content of a compressed video stream from
one format to another. A format is determined by characteristics such as the bit rate,
frame rate, spatial resolution, coding syntax, and the content. One useful and highly
demanded application of transcoding is inserting a logo into a stream of encoded video.
There are many commercial applications for this technology. As there are now many
television networks, the inserted logo is extremely effective for the viewers to identify the
station. Throughout the years, we have come to associate the “peacock” logo with NBC,
or the “eye” logo with CBS. These logos can greatly improve a broadcaster’s chances of
viewer recognition. Several logo-insertion methods are proposed for MPEG2 [1]
compressed video, but there is not much work done for a much more complicated
situation, that is the H.264 [2] compressed video logo insertion. In this project, we aim at
inserting logos to H.264 compressed videos.
The remainder of the project proposal is structured as follows. Section II briefly
introduces the notation and terminology used herein. Then, Section III introduces some
essential background of video coding and transcoding. In Section IV, we present the
existing logo-insertion methods for MEPG2 compressed video, and point out the
weaknesses of the methods especially when they are applied to the H.264 compressed
videos. Finally, Section V states the problems need to be solved in the logo insertion for
H.264 compressed video.
II. NOTATION AND TERMINOLOGY
Before further discussing logo insertion into the H.264 video stream, we need to define
some terminology used herein. In what follows, a video frame is partitioned into logo
unrelated and related parts. The logo related part further includes the “logo part” and
“logo-affected part”. The region that is covered by logo is called logo part, and the region
outside of the logo but motion predicted based on the logo part is called logo-affected
part. In MPEG2 compressed video, the logo-affected part exists only in P and B frames,
while in H.264 compressed video, the logo-affected part exists in all I, P, and B types of
frames.
Logos have different features. Some commonly desired logos can be classified as nontransparent
(i.e., solid) logos, transparent logos, rectangular-shaped logos, and arbitraryshaped
logos.
Logo insertion in the pixel domain can be performed by combing the pixel of the
background image B(x,y) with the logo L(x,y) to obtain the output image P(x, y). The
operation is usually expressed as a linear combination of the form:
P(x, y) = α × (L(x,y)) + (1 – α) × (B(x,y)) , (1)
where the transparency factor α determines the transparency of the logo. The value α is
in the range of 0 < α ≤ 1. In particular, when α = 1, all pixels of the background image
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are replaced by the logo, giving rise to an opaque overlapping of the logo over the input
image.
A logo often occupies a small portion of a frame, and is static over a frame sequence.
Logos often appear in a corner of a frame (e.g. the top left corner, bottom right corner).
They, however, can be anywhere in a slice for H.264 compressed video, since slice
partition is rather flexible in H.264 standard. Moreover, logos may present only in groups
of successive frames, as opposite to all frames in a video sequence.
III. VIDEO CODING AND TRANSCODING
Having introduced some logo-related terminology, in this section, we will present several
essential concepts for video coding and video transcoding. We first introduce three
commonly used transcoding structures in what follows.
A. Basic Transcoding Structures
One straightforward transcoding structure is the cascaded form. For the cascaded
structure as shown in Figure 1, the decoder decodes the compressed video stream
completely, and the encoder re-encodes the reconstructed video into the target format.
The cascaded architecture achieves high video quality, but it is computationally very
expensive. Therefore, the cascaded structure is not often used, especially in the real-time
transcoding. It is better to re-use the information contained in the original bit stream to
simplify the architecture.
Figure 1. Cascaded architecture in pixel domain.
Open-loop structure is another commonly used transcoding structure. In the open-loop
system, the bit stream is first variable-length decoded (VLD) to reconstruct the quantized
discrete cosine transform (DCT) coefficients, motion vectors, prediction modes, and
other macroblock-level information. The quantized coefficients are then inverse
quantized and modified according to the transcoding requirements. Finally, the modified
data is re-quantized and variable length coded to achieve the new output format. Figure 2
shows a requantization transcoder as an open-loop structure example.
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Figure 2. Open-loop architecture.
Open-loop systems are relatively simple. They do not include motion estimation, motion
compensation, DCT, and inverse DCT (IDCT). Therefore, open-loop structures are
computationally very efficient, but they suffer from low video quality due to the drift
problem. The drift problem is caused by the mismatch between the actual reference frame
used for motion estimation in the encoder and the degraded reference frame used for
motion compensation in the decoder. The drift problem accumulates and causes severe
degradation to the video quality.
To avoid the high complexity problem in the cascaded architecture and the poor video
quality problem in the open-loop structure, closed-loop systems provide a good tradeoff
between quality and computational complexity. In closed-loop structure, significant
complexity saving can be achieved while still maintaining acceptable video quality.
Closed-loop systems provide drift compensation for re-quantized data. They aim at
eliminating the mismatch between predictive and residual components by approximating
the cascaded transcoding architecture. In the simplified closed-loop structure as shown in
Figure 3, only one reconstruction loop is required with one DCT and one IDCT. Some
architecture inaccuracy is introduced due to the non-linear nature in which the reconstruction
loops are combined. However, it has been found that the approximation has
little effect on the video quality.
Figure 3. Closed-loop architecture.
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B. MPEG2 Video Coding
Since we are relatively familiar with MPEG2 coding process, we only present a point that
is easily overlooked. In MPEG2, the frame to be compressed is divided into 16×16 pixel
macroblocks. Then, for each of these macroblocks in P and B frames, the reconstructed
reference frame is searched to find a macroblock that best matches the macroblock to be
compressed. The offset is encoded as a motion vector. The match between the two
macroblocks will often not be perfect. To correct this, the encoder computes the residual
of the original pixel values and the predicted pixel values. The residual for each
macroblock is appended to the motion vector, and the spatial redundancy is further
reduced by the DCT transform. Sometimes, no suitable match is found. Then, the
macroblock is treated like an I-frame macroblock. Therefore, both inter and intra modes
can be used to compress macroblocks in MPEG2 P and B frames.
C. H.264 Video Coding
In this project, we aim to add logos into H.264 coded video streams. The H.264 standard
is the latest video coding standard. A brief description of the H.264 standard is described
below.
C.1. Intra Prediction
If a block or macroblock is encoded in the intra mode, a prediction block is formed based
on previously encoded and reconstructed (but un-filtered) blocks from the same slice.
This prediction block is subtracted from the current block prior to encoding. For the
luminance (luma) samples, a prediction block may be formed for each 4×4 subblock or
for a 16×16 macroblock. There are a total of nine optional prediction modes for each 4×4
luma block; four optional modes for a 16×16 luma block; and four optional modes for
each 8×8 chroma block. Note that the same mode is always applied to both chroma
blocks.
C.2. Inter Prediction
Inter prediction creates a prediction model from one or more previously encoded video
frames. The model is formed by shifting samples in the reference frame(s) (i.e., motion
compensated prediction). The H.264 codec uses block-based motion compensation. The
H.264 standard supports motion compensation block sizes ranging from 16×16 to 4×4
luminance samples with many options in between. The luminance component of each
macroblock (16×16 samples) may be split up in four ways: 16×16, 16×8, 8×16 or 8×8.
Each of the sub-divided regions is a macroblock partition. If the 8×8 mode is chosen,
each of the four 8×8 macroblock partitions within the macroblock may be split into a
further four ways: 8×8, 8×4, 4×8 or 4×4 (known as macroblock sub-partitions). These
partitions and sub-partitions give rise to a large number of possible combinations within
each macroblock.
A separate motion vector is required for each partition or sub-partition. Each motion
vector must be coded and transmitted. In addition, the choice of partition(s) must be
encoded and stored in the compressed bit stream. Choosing a large partition size (e.g.
16×16, 16×8, 8×16) means that a small number of bits are required to signal the choice of
motion vector(s) and the type of partition; however, the motion compensated residual
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may contain a significant amount of energy in frame areas with high detail. Choosing a
small partition size (e.g. 8×4, 4×4, etc.) may give a lower-energy residual after motion
compensation, but requires a larger number of bits to signal the motion vectors and
choice of partition(s). The choice of partition size, therefore, has a significant impact on
compression performance. In general, a large partition size is appropriate for
homogeneous areas of the frame and a small partition size may be beneficial for detailed
areas.
IV. EXISTING METHODS FOR MPEG2 COMPRESSED VIDEO LOGO INSERTION
Most methods for logo insertion are developed for MPEG2 compressed video. In what
follows, we will introduce such methods presented in several difficult papers, which
handle logo insertion from different perspectives. We will also analyze whether the
methods are appropriate to be adopted in logo insertion for H.264 compressed video.
A. Logo Insertion Position
For logo insertion, the first step is that the position of the logo needs to be determined.
Liu’s paper has placed the logo on the top left hand corner. Another major issue is that
the best logo position needs to be searched so that the effect on the coded macroblocks
can be minimized. In Liu’s paper [3], the logo is aligned to the macroblocks to minimize
the amount of macroblocks affected. If the logo is not aligned, then nine macroblocks
are affected whereas if it is aligned to the macroblocks, then only four macroblocks are
affected as shown in Figure 4.
Figure 4. Diagram of logo aligned to macroblocks.
B. Logo Insertion in Spatial Domain
As explained in [3], one of the approaches for logo insertion is to insert the logo in the
spatial domain. Figure 5 gives the block diagram for spatial domain logo insertion
structure.
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Figure 5. Logo insertion in spatial domain.
The transcoding works as follows. First, the input video stream (containing the motion
vectors and the residuals for the P and B frames, and I frame) goes through entropy
decoding to get the quantized versions. Then, the residual component for the P and B
frames are sent through an inverse quantizer for dequantization; then, it will be fed
through an inverse DCT transform. The motion vectors goes through two different paths.
The first path is through motion compensation, where it will be combined with the
feedback of the previous frame to form a prediction of the current frame without the
residual. The output of the first motion compensation is then added to the residual to form
the complete picture for the current frame. The output is also placed into a buffer so that
the next frame can use the previous frame’s picture for motion compensation. The motion
vector also goes through the second motion compensation block in the encoder part of the
loop. It is used to correct the logo insertion errors since the encoder uses the same
motion vector of the inputted video.
After the output of the first motion compensation block has been added with the residual
of the current frame, we will add the logo at this point using the formula (1). That is
P(x, y) = α × (L(x,y)) + (1 – α) × (B(x,y)) .
This is then fed in for error correction. After that, it will be encoded using a DCT block,
quantized, and then entropy encoded for output. There is a rate control mechanism to
keep a consistent bit rate output for the stream. This mechanism increases or decreases
the quantizer parameter for Q2 as a means of controlling the bit and also the quality of
the output frame.
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In [4], it shares the same architecture as described above except for the definition of the
motion vectors (MV). The early transcoders re-uses the motion vector from the input bitstream.
However, this motion vector may not be pointer to the best match of
macroblock’s that are close to the insertion area since part of the content is always static.
To maintain a high coding efficiency, paper [4] suggested the motion vector to be set to
zero for logo macroblocks that are dominated by logo content and the original motion
vector from the input bit-stream is used for logo macroblocks that are dominated by video
content. For example,
MV(x, y) = (0, 0), when α is greater than or equal to a threshold, e.g., 0.5.
MV(x, y) = MV’(x, y), otherwise. That is, using MV’s decoded from input bit-stream.
The above scheme is developed for MPEG2 coded video. For H.264 coded video,
however, this logo insertion architecture needs to be modified due to the multireferencing
capability in H.264. The above motion vector redefinition concept can
probably be used in the H.264 video stream logo insertion. However, the threshold of
transparency factor α needs to be refined carefully in order to achieve a good coding
efficiency for H.264 coded video.
C. Logo Insertion in Transform Domain
The transform domain insertion algorithm is a little less complicated than the spatial
domain one, as described by Liu [3]. There is less DCT block to worry about on the
decoding and the encoding sides. Because of the linearity property of the DCT transform
as shown in (2), transform domain additions are the same as spatial domain.
DCT(m+n) = DCT(m) + DCT(n) and
DCT{α(m(x,y))+(l-α)(n(x,y))} = αDCT{m(x,y)} + (l-α)DCT{n(x,y)}. (2)
The architecture of the logo insertion in the transform domain is shown in Figure 6. The
video stream is first entropy decoded and inverse quantized. This is similar to the spatial
domain strategy. The logo is then inserted in the DCT domain. Next, motion vectors are
fed back for DCT motion compensation, and subtraction is done for error correction.
These steps are all done in DCT domain. Then, the output is quantized before entropy
decoding and rate control. The quantized version is also inversely quantized and fed back
to the buffer for motion compensation of the next frame and error correction.
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Figure 6. Logo insertion in transform domain.
D. Low Cost and Efficient Logo Insertion
High accuracy and efficiency are two important criteria for logo insertion. One efficient
logo-insertion method proposed by Shu Xiao, etc, is shown in [5]. In this paper, the
authors presented efficient logo insertion methods for transparent and non-transparent
logos for MPEG2 compressed video. They considered the refinement of prediction modes
and motion vectors for different types of macroblocks. The method should be able to
apply in both spatial and transform domains.
In logo-insertion transcoding for MPEG2 compressed video, we need to compensate the
changes caused by the logo insertion. Such changes propagate through frames when P
and B frames refer to the reference frames in motion prediction process. For H.264
compressed video, however, change propagation happens also for I frames due to the use
of intra prediction as described in Section III. Sometimes, logos are not inserted in all
frames of a video sequence. Now, we start to introduce the method used in [5] for
determining the affected range of frames caused by logo insertion for MPEG2 coded
video.
D.1. Logo-Affected Range of Frames in the Temporal Domain
Let [l, h] denote the range of the video sequence where a logo is required to be inserted.
That is, the indices l and h are the lowest and highest frame numbers of this range,
respectively. We further let [L, H] represent the range of video sequence which is
affected by the logo insertion due to the change propagation caused by frame reference.
Clearly, we have [l, h] being a subset of [L, H]. Reference frames are frames of a
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compressed video that are used to define future frames. In MPEG2 video coding standard,
reference frames are I and P frames. The previous reference frame lr and next reference
frame hr of the range [l, h] are defined to be the reference frames outside the range [l, h]
with the largest and smallest frame numbers, respectively. Then, the indices L and H can
be determined using (3) and (4), as follows:
L = lr
+ 1,
(3)
⎧ hr
if hr
is not I frame,
H = ⎨
(4)
⎩hr
−1
otherwise.
Figure 7 gives two examples of logo-affected range of frames. In this example, we use
the typical group of picture (GOP) structure: IBBPBBPBBP…, where I and P frames are
reference frames. The frame dependencies are also drawn in the figure. In the logo range
example one, [5, 16] is the range of frames [l, h] where logos are added. The previous
reference frame lr of the range [l, h] is 3, and the next reference frame hr of the range [l, h]
is 18. According to (3) and (4), we got the logo-affected range of frames [L, H] as [4, 18].
Similarly, in example two, the range [L, H] is [4, 14].
Figure 7. Examples of logo affected range of frames.
Once the logo affected frame range [L, H] is identified, we can focus on compensating
the changes induced by logo insertion within this range of frames. The frames outside the
range [L, H] are not affected, and therefore remain unchanged.
The scheme described above cannot be directly applied to H.264 compressed video. This
is because, in H.264 video coding standard, all three types of frames (i.e., I, P, and B
frames) can be used as reference frames. Multiple reference frames are also used, which
makes determining the range [L, H] more challenging. The affected-frame range for
H.264 coded video needs to be wisely adjusted.
D.2. Motion Information Adjustment in the Logo and Logo-Affected Parts
Having introduced the logo-affected range of frames, we now state the motion
information adjustment in [5]. As mentioned earlier in Section II, a frame can be
partitioned into the logo part, logo affected part, and logo unrelated part. For simplicity,
in [5], the authors assume that the logo is rectangular and covers integer number of
macroblocks. The coding modes and motion vectors for macroblocks at the logo
unrelated part shall remain unchanged. In what follows, we discuss the motion-vector
refinement of macroblocks in the logo and logo-affected parts, respectively.
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For I and P frames in the logo part, if the first reference frame in the range of [l, h] is a P
frame, then set the macroblock mode (of those macroblocks in the logo part) to be intracoded.
If the first reference frame in the range of [l, h] is an I frame instead, the
macroblock modes for all I and P frames remain the same.
For B frames in the logo part, if its frame number is smaller than the first reference frame
in the range of [L, H], set the macroblock mode to be backward predicted. If its frame
number is larger than the last reference frame in the range of [L, H], set the macroblock
mode to be forward predicted or intra coded. Then, set the prediction mode for all other B
frames in [L, H] to be forward predicted.
Having the prediction modes refined, we set all motion vectors for inter-coded
macroblocks in the logo part to be zero. Clearly, this scheme is suitable for nontransparent
logos. For transparent logos, however, especially for logos with their
transparency factor α being small (e.g., α

E.1. Constant Quality at the Logo Part
We begin to discuss the non-transparent logo situation. Non-transparent logos should
look still in the video sequence. Therefore, we set the quantization scales for all the intracoded
macroblocks in the logo area to be the same value, so that the logo region has
approximately the same quality. For inter-coded macroblocks, the zero motion vector and
stationary logo content ensure the prediction accuracy. No residual information is needed.
Hence, we use the skip mode for P frames, and the maximum quantization scales for B
frames due to the lack of skip mode for B frames.
Unlike non-transparent logos, transparent logos are superimposed on the original video
frames. Therefore, the logo parts are not identical over different frames. To ensure
approximately the same quality in the logo area, we still use the same quantization scales
for all the intra-coded macroblocks in the logo area. For the inter-coded macroblocks, the
prediction residuals are not zero nor negligible any more. In [5], a slightly bigger
quantization scale is used for inter-coded macroblocks than intra-coded macroblocks.
Both quantization scales for the intra and inter macroblocks are inverse-proportional to
the total output bit rate. In doing so, we prevent the logo parts from consuming too many
bits for a low bit rate situation.
E.2. Bit Reallocation
Rate control is also an important requirement for video transcoding. It is usually
accomplished by adjusting the quantization scales. The transcoded video with logo may
consume more bits than the original coded video. In order to control the overall bit rate of
the encoded video while achieving a constant visual quality in the logo area, we need to
adjust the quantization scales for the macroblocks not covered by logo. One simple
practical scheme proposed in [5] is to pre-encode the logo part, then deduct the consumed
bits from the total target bits, and adjust the bit allocation of the non-logo-covered area
according to the left bit rate.
Note that the bit reallocation method described above is not the most efficient under some
circumstances. If the logo is inserted in the top left corner of a frame, the pre-encoding of
the logo part is not necessary. This is because the logo part is coded before most of the
other macroblocks are coded in this case, and the bits consumed by the logo-part are
known before most adjustment can be done. Furthermore, if the logo transparency is high,
adopting the original motion vectors might be more efficient than using zero motion
vectors for the inter-coded macroblocks.
V. MAIN ISSUES FOR H.264 COMPRESSED VIDEO LOGO INSERTION
As indicated earlier, most existing methods for logo insertion are developed for MPEG2
compressed video. The H.264 standard is much more complex and flexible, and therefore
more difficult to handle and introduces more challenges.
In H.264, intra prediction is used for coding the Intra macroblocks in the frames. Hence, I
frame has logo-affected part due to the dependence within the same slice. This challenge
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did not exist in MPEG2. The logo-affected areas caused by intra prediction needs to be
solved and properly compensated. The intra predication issue implies a complex
challenge. Because every intra macroblock depends on neighboring macroblock pixels
(i.e. the bottom-right corner pixel of top-left neighboring macroblock, and bottom row of
pixels of top neighboring macroblock or right column of pixels of left macroblock) the
border (boundary) pixels of the logo-affected area should remain the same otherwise a
drift error will accumulate over time.
H.264 utilizes better half-pixel approximation (6-tap bicubic interpolation) to find better
match in the motion estimation stage where MPEG2 uses bilinear interpolation. There are
many proposals to reuse motion vectors from the decoder, however, directly using those
motion vectors is not optimal and an extra process is needed to compensate the difference
between bicubical and bilinear interpolation. In addition H.264 supports quarter-pixel
samples accuracy to further refine the motion vectors. This did not exist in MPEG2. This
introduces another challenge. The challenges of half-pixel and quarter-pixel make many
of the MPEG2 motion vectors transcoding solution inapplicable (not easily usable) for
H264 transcoding.
There are papers discussing and proposing a logo insertion in the DCT domain for
MPEG2. DCT is done in 8×8 macroblocks. In H.264 the block size is different (i.e. 4×4)
and the transform is integer-DCT-like transform. The issues here are: 1) different
transform sizes. 2) MPEG2 DCT is independent process where in H.264 the transform is
combined with quantization. 3) MPEG2 DCT logo insertion is efficient for intra
macroblocks only because they are absolutely independent. These issues make transform
domain logo insertion for H.264 extremely hard.
MPEG2 quantization has 32 quantization steps with some dead zone assumptions.
MPEG2 quantization is applied by division operations. In H.264 quantization is mixed
with the transform. It also uses 52 quantization steps and applied by lookup tables and
shifts. There are several suggestions for MPEG2 quantization and requantization
mapping for rate control purposes. Almost all those are inapplicable because the whole
process is too different in terms of steps ranges, quantization error approximation, and
corresponding quality of each quantization step. Another related issue is the rate control
distortion approximation is completely different. This makes the optimization equation
for MPEG2 very suboptimal for H.264.
The wide variety of the block size in H.264 is important feature that in general can
improve the coding efficiency. However, in case of logo insertion, some of the modes
might not have an effect on quality because the transcoder is encoding previously
encoded frames. There are some existing techniques for mode selection in case of
MPEG2 logo insertion. However, wider range of modes and macroblock sizes in H.264
make so hard to apply any of MPEG2 current methods to H.264.
H.264 uses variable width in-loop deblocking filter affecting up to 2-3 border pixels of
each macroblock. This means the deblocked frames are used as references for feature
frames. This creates a significant challenge which manifests as more boundary pixels are
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not to be changed. In other words after logo insertion more boundary pixel have to be
identical to before logo insertion.
Another issue with H.264, multiple reference frames can be used as references for motion
prediction in the inter prediction mode. The prediction modes and motion vectors have
more combinations and possibilities. There is also multiple backward reference frames
for Inter modes in B frames. The issue alone will multiply the resources requirement (i.e.
temp memory) of the H.264 transcoder versus MPEG2.
H264 complexity offers new features which did not exist before such as I_PCM (lossless
compression) and arbitrary slices shapes and sizes. These features might make logo
insertions in H.264 completely different than MPEG2 current work. These feature to be
investigated to study the efficiency of using them. In this project, we aim at solving logoinsertion
transcoding issues for H.264 coded video.
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