Pulse or digital communications – Bandwidth reduction or expansion
Reexamination Certificate
1999-08-11
2004-05-11
An, Shawn S. (Department: 2613)
Pulse or digital communications
Bandwidth reduction or expansion
C375S240120, C375S240160, C375S240270, C382S107000, C382S236000, C382S238000, C708S008000, C708S008000, C708S008000, C708S008000
Reexamination Certificate
active
06735249
ABSTRACT:
The present invention relates generally to a manner by which to utilize motion compensation in coding a video sequence. More particularly, the present invention relates to apparatus, and an associated method, for encoding, and decoding, a video sequence utilizing motion compensated prediction. Motion fields of a segment are predicted from adjacent segments of a video frame and by using orthogonal affine motion vector field models. Through operation of an embodiment of the present invention, motion vector fields are formed with a reduced number of bits while still maintaining a low prediction error.
BACKGROUND OF THE INVENTION
Advancements in digital communication techniques have permitted the development of new and improved types of communications. Additional advancements shall permit continued improvements in communications and communication systems which make use of such advancements.
For instance, communication systems have been proposed for the communication of digital video data capable of forming video frames. Video images utilized during video conferencing are exemplary of applications which can advantageously make use of digital video sequences.
A video frame is, however, typically formed of a large number of pixels, each of which is representable by a set of digital bits. And, a large number of video frames are typically required to represent any video sequence. Because of the large number of pixels per frame and the large number of frames required to form a typical video sequence, the amount of data required to represent the video sequence quickly becomes large. For instance, an exemplary video frame includes 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.
Video sequences, like ordinary motion pictures recorded on film, comprise a sequence of still images, the illusion of motion being created by displaying consecutive images at a relatively fast rate, say 15-30 frames per second. Because of the relatively fast frame rate, the images in consecutive frames tend to be quite similar. A typical scene comprises some stationary elements, for example the background scenery and some moving parts which may take many different forms, for example the face of a newsreader, moving traffic and so on. Alternatively, the camera recording the scene may itself be moving, in which case all elements of the image have the same kind of motion. In many cases, this means that the overall change between one video frame and the next is rather small. Of course, this depends on the nature of the movement: the faster the movement, the greater the change from one frame to the next.
Problems arise in transmitting video sequences, principally concerning the amount of information that must be sent from the transmitting device to the receiver. Each frame of the sequence comprises an array of pixels, in the form of a rectangular matrix. To obtain a sharp image, a high resolution is required i.e. the frame should comprise a large number of pixels. Today, there are a number of standardized image formats, including the CIF (common intermediate format) which is 352×288 pixels and QCIF (quarter common Intermediate format) which is 176×144 pixels. QCIF format is typical of that which will be used in the first generation of mobile video telephony equipment and provides an acceptably sharp image on the kind of small (3-4 cm square) LCD displays that may be used in such devices. Of course, larger display devices generally require images with higher spatial resolution, in order for those images to appear with sufficient spatial detail when displayed.
For every pixel of the image, color information must be provided. Typically, and as noted above, color information is coded in terms of the primary color components red, green and blue (RGB) or using a related luminance/chrominance model, known as the YUV model which, as described below, provides some coding benefits. Although there are several ways in which color information can be provided, the same problem is common to all color representations; namely the amount of information required to correctly represent the color range present in natural scenes. In order to create color images of an acceptable quality for the human visual system, each color component must typically be represented with 8 bit resolution. Thus each pixel of an image requires 24 bits of information and so a QCIF resolution color image requires 176×144×(3×8)=608256 bits. Furthermore, if that QCIF image forms part of a video sequence With a frame rate of 15 frames per second, a total of 9,123,840 bits/s is required in order to code that sequence.
As such, amounts of data sometimes must be transmitted over relatively low bit-rate communication channels, such as wireless communication channels operating below 64 kilobits per second.
Video coding schemes are utilized to reduce the amount of data required to represent such video sequences. A key of many video coding schemes is a manner by which to provide motion compensated prediction. Motion compensated prediction, generally, provides a manner by which to improve frame compression by removing temporal redundancies between frames. Operation is predicated upon the fact that, within a short sequence of the same general image, most objects remain in the same location whereas others move only short distances. Such motion is described as a two-dimensional motion vector.
Some coding advantage can be obtained using the YUV color model. This exploits a property of the human visual system, which is more sensitive to intensity (luminance) variations than it is to color variations. Thus, if an image is represented in terms of a luminance component and two chrominance components (as in the YUV model), it is possible to spatially sub-sample (reduce the resolution of) the chrominance components. This results in a reduction in the total amount of information needed to code the color information in an image with an acceptable reduction in image quality. The spatial subsampling may be performed in a number of ways, but typically each block of 16×16 pixels in the image is coded by 1 block of 16×16 pixels representing the luminance information and 1 block of 8×8 pixels for both chrominance components. In other words, the chrominance components are sub-sampled by a factor of 2 in the x and y directions. The resulting assembly of one 16×16 luminance block and two 8×8 chrominance blocks is commonly referred to as a macroblock. Using this kind of coding scheme, the amount of information needed to code a QCIF image can be calculated as follows: The QCIF resolution is 176×144. Thus the image comprises 11×9 16×16 pixel luminance blocks. Each luminance block has two 8×8 pixel sub-sampled chrominance blocks associated with it, i.e., there are also 11×9 macroblocks within the image. If the luminance and chrominance components are coded with 8 bit resolution, the total number of bits required per macroblock is 1×(16×16×8)+2×(8×8×8)=3072 bits. Thus the number of bits required to code the entire QCIF image is now 99×3072=304128 bits i.e. half the number required if no chrominance sub-sampling is performed (see above). However, this is still a very large amount of information and if a QCIF image coded in this way is part of a 15 frame per second video sequence, a total of 4,561,920 bits/s are still required.
Video coding requires processing of a large amount of information. This necessarily means that powerful signal processing devices are required to code video images and, if those images are to be transmitted in their original form, a high bandwidth communication channel is required. However, in many situations it is not possible to provide a high capacity transmission channel. This is particularly true in video telephony applications, where the video signals must be transmitted over existing fixed line commu
Dobrin Bogdan-Paul
Karczewicz Marta
Lainema Jani
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