Pulse or digital communications – Bandwidth reduction or expansion – Television or motion video signal
Reexamination Certificate
1999-11-03
2003-09-30
Kelley, Chris (Department: 2613)
Pulse or digital communications
Bandwidth reduction or expansion
Television or motion video signal
Reexamination Certificate
active
06628717
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
The present invention relates to a lossless coding method and a video compression coding method using the same, and more particularly, to method and device for compressing and encoding a digital data by processing an input symbol suitable for, application of the Golomb Rice Coding thereto.
2. Background of the Related Art
There is the wavelet transform in one of transform methods for coding a video signal, which is means for disassembling a signal in time(space) domain into respective frequency components, that is similar to the Fourier Transform. The wavelet transform improves a locality of the time domain in a high frequency region and a locality of a frequency domain in a low frequency region.
FIG. 1
illustrates a structure of a sub-band region when, a video signal is wavelet transformed.
Referring to
FIG. 1
, it is well known that, as a result of subjecting a video signal to a wavelet transform, a sub-band region division structure becomes to have a low frequency region containing relatively more meaningful information on the video signal being concentrated to one side thereof and a high frequency region containing relatively less meaningful information on the video signal being concentrated to the other side thereof. That is, low frequency components of an original video is gathered to the most coarse band(F
0
) and fine high frequency components are gathered to bands(F
1
~F
9
) other than the coarse band. All the coefficients for given bands except the lowest frequency band have relations with coefficients for the next sub-band in a similar direction. For example, of the nine sub-band regions F
1
~F
9
in the wavelet transformed sub-band regions shown
FIG. 1
, F
1
, F
4
and F
7
regions show horizontal edge components of the video signal, and F
2
, F
5
and F
8
regions show vertical edge components, and F
3
, F
6
and F
9
regions show diagonal components. Therefore, if the wavelet transformed respective sub-band regions are scanned in different paths(horizontal, vertical and diagonal) by using such a characteristic, a more effective video compression is available. That is, by scanning the F
1
, F
4
and F
7
regions which have horizontal edge components in a horizontal direction, the F
2
, F
5
and F
8
regions which have vertical edge components in a vertical direction, and the F
3
, F
6
and F
9
regions which have diagonal edge components in a diagonal direction, a better compression ratio can be obtained in an arithmetic coding conducted later owing to a statistical characteristic(a probability is increased, in which consecutive zero runs are occurred by scanning in a direction that shows the edge components).
As another transform method for coding a video signal, there is the DCT(Discrete Cosine Transform). That is, the DCT also transforms respective blocks of video from spatial domains into frequency domains, to remove correlation of data. To do this, a received frame is divided into block units, and subjected to two dimensional axial transformation. The data thus subjected to DCT has a tendency to gather to one side(low frequency band). Only data gathered thus is. quantized.
FIG. 2
illustrates an example of a related art video compression coder, which is an MPEG(Moving Picture Experts Group) compression coder based on the DCT.
Referring to
FIG. 2
, there is a DCT unit
101
for subjecting a input digital video signal or a signal difference between the input digital video signal and a motion compensated signal of a previous input digital video signal to DCT. There is a quantizing unit
102
for quantizing an output of the DCT unit
101
, i.e., DCT coefficients under the control of a bit rate control unit
105
and providing to a VLC(Variable Length Coding) unit
103
. The VLC unit
103
uses the Huffman Coding, which is a noiseless coding for approaching to an entropy of a source data, and the Run Length Coding in compressing the quantized DCT coefficients and providing as a video data stream(MPEG Video Bitstream) through a buffer
104
. The quantized signal is subjected to inverse quantizing in an inverse quantizing unit
106
and IDCT in an IDCT unit, and provided to an adder
108
. The adder
108
adds the data motion compensated in the motion compensating unit
110
to the data subjected to IDCT, and stores in a frame memory
109
. The motion compensating unit
110
uses both the data stored in the frame memory
109
and the input digital video signal in producing a motion vector, and conducts a motion compensation using the same. The subtracter
111
calculates a difference between the motion compensated data and the input digital video signal and provides to the DCT unit
101
. Thus, the MPEG compression coder conducts a compression coding of the input digital video signal meeting the MPEG standards. In this instance, the VLC unit
103
maps DCT coefficients to code words provided in advance using the Huffman Coding and the Run Length Coding. The Huffman Coding reversely compresses data by assigning the shorter code word as the data has the higher probability of occurrence, to make an average code length(data amount) the smaller, that is known as a method for providing a minimum average code length for information of a given probability distribution.
However, the related art for compression coding a digital data, such as the Huffman Coding, has a limitation in improving a compression performance while reducing a number of bits and lowering a complexity. Therefore, a technology is in need, in which a digital data including a video data is compression coded in a better performance while a number of bits and a complexity are reduced.
SUMMARY OF THE INVENTION
Accordingly, the present invention is directed to a lossless coding method and a video compression coding method using the same that substantially obviates one or more of the problems due to limitations and disadvantages of the related art.
An object of the present invention is to provide a lossless coding method in which an input symbol is subjected to a forward classification processes to a form application of the Golomb Rice Coding is easy, and to the Golomb Rice Coding.
Another object of the present invention is to provide a lossless coding method and a video compression coder, in which input symbols are sorted into data greater than a threshold value and data smaller than the threshold value, producing a binary mask value assigning a position value to the sorted data, and applying the Golomb Rice Coding to each of the sorted data, for compression coding of the video.
Other object of the present invention is to provide a lossless coding method and a video compression coder, in which a process for sorting a digital video data by comparing to a preset threshold value to a level closest to apply the Golomb Rice Coding thereto is repeated more than one stage, for compression coding of a motion picture or a still picture.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be apparent from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
To achieve these and other advantages and in accordance with the purpose of the present invention, as embodied and broadly described, the lossless coding method includes the steps of(1) comparing input data which are objects of coding to a threshold value, to classify the input data into values greater than the threshold value and values smaller than the threshold value, and, on the same time, obtaining positional information on the respective classified values which represent positions in input data groups, and (2) coding the values greater than the threshold value, the values smaller than the threshold value, and the positional information.
The values greater than the threshold value, the values smaller than the threshold value,
Jeong Je Chang
Yoo Hoon
Kelley Chris
Senfi Behrooz
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