Pulse or digital communications – Bandwidth reduction or expansion – Television or motion video signal
Reexamination Certificate
2000-05-08
2004-03-23
Diep, Nhon (Department: 2713)
Pulse or digital communications
Bandwidth reduction or expansion
Television or motion video signal
Reexamination Certificate
active
06711211
ABSTRACT:
The present invention relates to video coding. In particular, it relates to compression of video information using motion compensated prediction.
BACKGROUND OF THE INVENTION
A video sequence typically consists of a large number video frames, which are formed of a large number of pixels each of which is represented by a set of digital bits. Because of the large number of pixels in a video frame and the large number of video frames even in a typical video sequence, the amount of data required to represent the video sequence quickly becomes large. For instance, a video frame may include an array of 640 by 480 pixels, each pixel having an RGB (red, green, blue) color representation of eight bits per color component, totaling 7,372,800 bits per frame. Another example is a QCIF (quarter common intermediate format) video frame including 176×144 pixels. QCIF provides an acceptably sharp image on small (a few square centimeters) LCD displays, which are typically available in mobile communication devices. Again, if the color of each pixel is represented using eight bits per color component, the total number of bits per frame is 608,256.
Alternatively, a video frame can be presented using a related luminance/chrominance model, mown as the YUV color model. The human visual system is more sensitive to intensity (luminance) variations that it is to color (chrominance) variations. The YUV color model exploits this property by representing an image in terms of a luminance component Y and two chrominance components U, V, and by using a lower resolution for the chrominance components than for the luminance component In his way the amount of information needed to code the color information in an image can be reduced with an acceptable reduction in image quality. The lower resolution of the chrominance components is usually attained by spatial sub-sampling. Typically a block of 16×16 pixels in the image is coded by one block of 16×16 pixels representing the luminance information and by one block of 8×8 pixels for each chrominance component. The chrominance components are thus sub-samples by a factor of 2 in the x and y directions. Tie resulting assembly of one 16×16 pixel luminance block and two 8×8 pixel chrominance blocks is here referred to as a YUV macroblock. A QCIF image comprises 11×9 YUV macroblocks. The luminance blocks and chrominance blocks are represented with 8 bit resolution, and the total number of bits required per YUV macroblock is (16×16×8)+2X(8×8×8)=3072 bits. The number of bits needed to represent a video frame is thus 99×3072=304,128 bits.
In a video sequences comprising a sequence of frames in YUV coded QCIF format recorded/displayed at a rate of 15-30 frames per second, the amount of data needed to transmit information about each pixel in each frame separately would thus be more tan 4 Mbps (million bits per second). In conventional videotelephony, where the encoded video information is transmitted using fixed-line telephone networks, the transmission bit rates are typically multiples of 64 kilobits/s. In mobile videotelephony, where transmission takes place at least in part over a radio communications link, the available transmission bit rates can be as low as 20 kilobits/s. Therefore it is clearly evident that methods are required whereby the amount of information used to represent a video sequence can be reduced, Video coding tackles the problem of reducing the amount of information that needs to be transmitted in order to present the video sequence with an acceptable image quality.
In typical video sequences the change of the content of successive frames is to a great extent the result of the motion in the scene. This motion may be due to camera motion or due to motion of the objects present in the scene. Therefore, typical video sequences are characterized by significant temporal correlation, which is highest along the trajectory of the motion. Efficient compression of video sequences usually takes advantage of this property of video sequences. Motion compensated prediction is a widely recognized technique for compression of video. It utilizes the fact that in a typical video sequence, image intensity/chrominance values in a particular frame segment can be predicted using image intensity/chrominance values of a segment in some other already coded and transmitted frame, given the motion trajectory between these two frames. Occasionally, it is advisable to transmit a frame that is coded without reference to any other frames, to prevent deterioration of image quality due to accumulation of errors and to provide additional functionality such as random access to the video sequence. Such a frame is called an INTRA frame.
A schematic diagram of an example video coding system using motion compensated prediction is shown in
FIGS. 1 and 2
of the accompanying drawings.
FIG. 1
illustrates an encoder
10
employing motion compensation and
FIG. 2
illustrates a corresponding decoder
20
. The operating principle of video coders using motion compensation is to minimize the prediction error frame E
n
(x,y), which is the difference between the current frame I
n
(x,y) being coded and a prediction frame P
n
(x,y). The prediction error frame is thus
E
n
(
x,y
)=
I
n
(
x,y
)−
P
n
(
x,y
). (1)
The prediction frame P
n
(x,y) is built using pixel values of a reference frame R
n
(x,y), which is one of the previously coded and transmitted frames (for example, a frame preceding the current frame), and the motion of pixels between the current frame and the reference frame. More precisely, the prediction frame is constructed by finding the prediction pixels in the reference frame R
n
(x,y) and moving the prediction pixels as the motion information specifies. The motion of the pixels may be presented as the values of horizontal and vertical displacements &Dgr;x(x,y) and &Dgr;y(x,y) of a pixel at location (x,y) in the current frame I
n
(x,y), The pair of numbers [&Dgr;x(x,y), &Dgr;y(x,y)] is called the motion vector of this pixel.
The motion vectors [&Dgr;x(x,y), &Dgr;y(x,y)] are calculated in the Motion Field Estimation block
11
in the encoder
10
. The set of motion vectors of all pixels of the current frame [&Dgr;x(·), &Dgr;y(·)] is called the motion vector field. Due to the very large number of pixels in a frame it is not efficient to transmit a separate motion vector for each pixel to the decoder. Instead, in most video coding schemes the current frame is divided into larger image segments S
k
and information about the segments is transmitted to the decoder.
The motion vector field is coded in the Motion Field Coding block
12
of the encoder
10
. Motion Field Coding refers to the process of representing the motion in a frame using some predetermined functions or, in other words, representing it with a model. Almost all of the motion vector field models commonly used are additive motion models. Motion compensated video coding schemes may define the motion vectors of image segments by the following general formula:
Δ
x
(
x
,
y
)
=
∑
i
=
0
N
-
1
a
i
f
t
(
x
,
y
)
(
2
)
Δ
y
(
x
,
y
)
=
∑
i
=
0
N
-
1
b
i
g
t
(
x
,
y
)
(
3
)
where coefficients a
1
and b
i
are called motion coefficients. They are transmitted to the decoder (information stream
2
in FIGS.
1
and
2
). Functions ƒ
i
and g
i
are called motion field basis fictions, and they are known both to the encoder and decoder. An approximate motion vector field ({tilde over (&Dgr;)}x(x,y),{tilde over (&Dgr;)}y(x,y)) can be constructed using the coefficients and the basis functions.
The prediction frame P
n
(x,y) is constructed in the Motion Compensated Prediction block
13
in the encoder
10
, and it is given by
P
n
(
x,y
)=
R
n
[x+{tilde over (&Dgr;)}x
(
x,y
),
y+{tilde over (&Dgr;)}y
(
x,y
)], (4)
where the reference frame R
n
(x,y) is available in the
Diep Nhon
Nokia Mobile Phones Ltd.
Perman & Green LLP
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