Image signal encoding apparatus using adaptive 1D/2D DCT compression technique

An improved image signal encoding apparatus for processing a digitized image signal for transmission thereof in a compressed form, comprising a horizontal one-dimensional compression path for compressing the digitized image signal utilizing a horizontal correlation therein to provide a first compression signal, a vertical one-dimensional compression path for compressing the digitized image signal utilizing a vertical correlation therein to provide a second compression signal, a two-dimensional compression path for compressing the digitized image signal utilizing the horizontal and the vertical correlations to provide a third compression signal; and a comparator for comparing a first compression error contained in the first compression signal, a second compression error contained in the second compression signal and a third compression error contained in the third compression signal so as to enable the selection of the compression signal having the least error.

FIELD OF THE INVENTION 
The present invention relates to an image signal encoding apparatus for 
compressing image signals; and, more particularly, to an improved image 
signal encoding apparatus capable of compressing image signals for the 
transmission thereof through the use of a combined one/two dimensional 
(1D/2D) DCT compression technique. 
DESCRIPTION OF THE PRIOR ART 
In various electronic/electrical applications such as high definition 
television and video telephone systems, an image signal may need be 
transmitted in a digitized form. When the image signal comprising a 
sequence of image "frames" is expressed in a digitized form, there is 
bound to occur a substantial amount of digital data: for each line of an 
image frame is defined by a sequence of digital data elements referred to 
as "pixels". Since, however, the available frequency bandwidth of a 
conventional transmission channel is limited, in order to transmit the 
substantial amounts of digital data through the limited channel, the use 
of an image signal encoding apparatus often becomes necessary to compress 
the image signal. 
The image signal can be normally compressed without seriously affecting its 
integrity because there usually exist certain correlationships among some 
of the pixels in a single frame and also among those of neighboring 
frames. From the image signal compression perspective, such correlation 
may be considered as a redundancy. 
Accordingly, most image signal encoding apparatus of prior art employ 
various compression techniques(or coding methods) built on the idea of 
utilizing or reducing the redundancies. Such compression techniques can be 
classified into three categories. 
A first category of compression techniques is the so-called predictive 
method, also known as the interframe coding, which is based on the concept 
of reducing the redundancy between neighboring frames. In the predictive 
method, the luminance value of a pixel in a current frame to be 
transmitted is predicted from the luminance value of its corresponding, 
previously transmitted pixel in its previous frame, then the predictive 
error signal, which represents the differences between the luminance 
values of the pixels in the current frame and the predicted values, is 
compressed(or coded); and the compressed data is then transmitted. 
A predictive method of late utilizes a motion estimation and compensation 
method. This method is described, for example, in Staffan Ericsson, "Fixed 
and Adaptive Predictors for Hybrid Predictive/Transform Coding", IEEE 
Transactions on Communications, COM-33, No. 12(December 1985); and in 
Ninomiya and Ohtsuka, "A Motion-Compensated Interframe Coding Scheme for 
Television Pictures", IEEE Transactions on Communications, COM-30, No. 
1(January 1982), both of which are incorporated herein by reference. In 
this method, an image frame is divided into a plurality of subimages(or 
blocks). The size of a subimage typically ranges between 8.times.8 and 
32.times.32 pixels. The motion estimation and compensation is a process of 
determining the movement of objects between a current frame and its 
previous frame, and predicting the current frame according to the motion 
flow to produce a predictive error signal representing the difference 
between the current frame and its prediction. 
A second category of coding methods comprises a transform technique which 
utilizes the redundancies existing in a single frame. This coding 
technique, which exploits only the spatial correlation, is called the 
intraframe coding. One of such transform methods is a two-dimensional 
DCT(Discrete Cosine Transform). This technique is described in Chen and 
Pratt, "Scene Adaptive Coder", IEEE Transactions Communications, COM-32, 
No. 3(March 1984), which is incorporated herein by reference. The 
two-dimensional DCT converts a block of digital image signal, for example, 
a block of 8.times.8 pixels, into a set of transform coefficient data. By 
processing such transform coefficient data with a variable length 
coding(VLC) method such as run-length Huffman coding, the amount of data 
to be transmitted can be effectively compressed. 
A third category of compression techniques makes use of the so-called 
hybrid coding, which is a combination of the first and the second 
categories of techniques. 
Currently, the hybrid coding method is most commonly employed. Also, to 
increase the compressibility of image signals, the apparatus may employ 
other additional compression algorithms adapted to specific conditions. 
One of such additional compression algorithms is an adaptive 1D/2D DCT 
compression technique. 
Normally, in most compression processes, two dimensional correlation, i.e., 
both horizontal and vertical correlation, is employed. However, in certain 
image signals, such as the motion compensated prediction error signals and 
horizontal or vertical line pattern signals, it is also possible to have a 
meaningful correlation in one directional dimension only. In this case, 
one dimensional DCT may be sufficient and more economical than two 
dimensional DCT. Accordingly, it is sometimes desirable to compress image 
signals making use of an adaptive 1D/2D DCT compression technique. 
SUMMARY OF THE INVENTION 
It Is, therefore, an object of the invention to provide an improved image 
signal encoding apparatus which is capable of compressing image signals by 
employing an adaptive 1D/2D DCT compression technique. 
It is another object of the invention to provide an improved image signal 
encoding apparatus which is capable of selecting a more efficient DCT 
compression technique in an economical fashion. 
In accordance with the invention, there is provided an improved image 
signal encoding apparatus for processing a digitized image signal for 
transmission thereof in a compressed form, comprising: first means for 
compressing the digitized image signal utilizing a horizontal correlation 
therein to provide a first compressed image signal; second means for 
compressing the digitized image signal utilizing a vertical correlation 
therein to provide a second compressed image signal; third means for 
compressing the digitized image signal utilizing the horizontal and the 
vertical correlations to provide a third compressed image signal; and a 
comparator for comparing a first compression error contained in the first 
compression signal, a second compression error contained in the second 
compression signal and a third compression error contained in the third 
compression signal so as to enable the selection of the compression signal 
having a least error.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS 
FIG. 1 illustrates an image signal encoding apparatus using an adaptive 
1D/2D DCT compression technique in accordance with a preferred embodiment 
of the present invention. 
In accordance with the present invention, image data such as a digitized 
image signal is provided through a terminal 100 to a current frame memory 
102. The process of digitizing such an image signal is well known in the 
art. 
Image data is decomposed at the current frame memory 102 into blocks of a 
size appropriate for data compression. The blocks of data are fed to a 
subtractor 104 and a motion compensation and prediction block 122. The 
decomposed image data is predicted by the motion compensation and 
prediction block 122 based on the image data of its preceding image frame. 
The predicted image data, i.e., the predictive signal from the motion 
compensation and prediction block 122 is subtracted from the image 
retrieved from the current frame memory 102 to produce a predictive error 
signal. 
The predictive error signal is then fed to a horizontal one-dimensional 
compression path, a vertical one-dimensional compression path and a 
two-dimensional compression path, respectively. 
The horizontal 1D compression path comprises a first format converter 106, 
a horizontal one-dimensional Discrete Cosine Transform(1H DCT) block 108 
and a first quantizer 110; the vertical 1D compression path comprises a 
second format converter 116, a vertical one-dimensional Discrete Cosine 
Transform(1V DCT) block 118 and a second quantizer 120; and the 2D 
compression path comprises a two-dimensional Discrete Cosine Transform(2D 
DCT) block 128 and a third quantizer 130. The output signal from each of 
said quantizers is fed, respectively, through line L4, L8 or L12 to a 
coding circuitry 112. 
In the horizontal one-dimensional compression path, each block of image 
data is rearranged through the first format converter 108 into a 
horizontal one-dimensional data. The horizontal 1D data is transformed by 
the 1H DCT block 108 into a set of horizontal one-dimensional transform 
coefficients which have a statistic distribution in the frequency region 
between a d.c. component zone up to a high frequency zone and which have 
different levels of electric power. The electric power of the transform 
coefficients is locally distributed, i.e., concentrated on a local 
frequency zone which includes the d.c. component and a low frequency zone 
near the d.c. component. This shows that non-zero or significant transform 
coefficients mainly appear in the low frequency zone; and that zero or 
insignificant transform coefficients mainly appear in the high frequency 
zone, which may be truncated or need not always be transmitted. 
Further, in the horizontal one-dimensional compression path, the set of 
transform coefficients is quantized by the first quantizer 110 into a 
first quantization signal. The quantization is a process of assigning to a 
selected transform coefficient a reconstruction or quantization level to 
thereby represent the set of transform coefficients with a finite number 
of bits. 
In the vertical one-dimensional compression path, each block of image data 
is rearranged through the second format converter 116 into a vertical 
one-dimensional data. The vertical one-dimensional data is transformed by 
the 1V DCT block 118 into a set of vertical one-dimensional transform 
coefficients, which is then quantized by the second quantizer 120 to 
produce a second quantization signal, also provided to the coding 
circuitry 112. 
In the two-dimensional compression path, the predictive error signal is 
transformed into a set of two-dimensional transform coefficients, which is 
quantized at the third quantizer 130 to produce a third quantization 
signal, which is then provided to the coding circuitry 112. 
The coding circuitry 112 is illustrated in a greater detail in FIG. 2. The 
coding circuitry 112 includes scanners 202, 212 and 222, a zero run-length 
coder 206, variable length coders 210, 220 and 230 and switches 204, 208 
and 214. 
Each of the quantization signals provided through lines L4, L8 and L12 is 
scanned with a predetermined scanning method adapted to the particular 
distribution pattern of the transform coefficients. For example, the first 
scanner 202 may use a vertical scanning method, the second scanner 212 may 
employ a horizontal scanning method and the third scanner 222 may perform 
a zigzag scanning. Each of the scanning methods may be preferably operated 
progressively from the low frequency components towards the high frequency 
components of the transform coefficients. 
Each of said scanned quantization signals is provided through the switch 
204 to the zero run-length coder 206. The coder 206 encodes the scanned 
quantization signal by utilizing the zero level of transform coefficients, 
which mainly appear in the high frequency zone as mentioned above, to 
produce zero run-length codes. The run-length coding method is well known 
in the art. 
Zero run-length codes are provided through the switch 208 to each of 
variable length coders 210, 220 and 230. In each of the variable length 
coders, a plurality of code sets adapted to each of the compression paths 
is memorized to define a respective relationship between each zero 
run-length code and its corresponding variable length code. Each of the 
coders encodes the zero run-length code to provide a variable length code 
to a multiplexer(not shown) which multiplexes the variable length code and 
other compression information such as motion vectors, which are generated 
in the motion compensation and prediction block 122. 
In the meanwhile, in accordance with the invention, selection among the 
horizontal one-dimensional, the vertical one-dimensional and the 
two-dimensional compression paths is made on a block-by-block basis by 
comparing the compression error contained in the compressed data from each 
path. In the preferred embodiment, the selection is made by comparing the 
quantization errors. 
The error evaluation and selection block 114 is illustrated in a greater 
detail in FIG. 3. The block 114 includes a horizontal compression, a 
vertical compression and a two-dimensional compression error evaluating 
components and a comparator 330. The error evaluating components have 
inverse quantizers(IQs) 302, 312 and 322, subtractors 304, 314 and 324, 
absoluters 306, 316 and 326 and accumulators 308,318 and 328. 
From the horizontal one-dimensional, the vertical one-dimensional and the 
two-dimensional compression paths, when the respective unquantized signals 
are provided through lines L2, L6 and L10, and the quantized signals are 
provided through lines L4, L8 and L12, respectively, each of the 
differences between them is calculated at each of subtractors 304, 314 and 
324. At this time, quantized signals provided through lines L4, L8 and L12 
are inversely quantized prior to their subtraction. Each of the difference 
signals is absoluted by absoluters 306,316 and 326 and accumulated at 
accumulators 308,318 and 328. 
The comparator 330 compares each of the accumulated quantization error 
signals on a block-by-block basis to provide through line 14 a switch 
control signal to the switches provided in the coding circuitry 112 and 
the motion compensation and prediction block 122. 
Referring back to FIG. 1 the motion compensation and prediction block 122 
produces the predictive signal utilizing the motion compensation 
technique. The block 122 has three decompression paths corresponding to 
the three compression paths and a switch which is responsive to the switch 
control signal to select a decompressed signal. Further, the block 122 has 
a previous frame memory where the selected decompressed signal is stored 
until it can be used for the next frame prediction. 
The selective use of the 1D/2D DCT compression technique in accordance with 
the invention can be effectively employed in improving the image quality 
of digitally transmitted signals. 
While the present invention has been shown and described with reference to 
the particular embodiment, it will be apparent to those skilled in the art 
and many changes and modifications may be made without departing from the 
spirit and scope of the invention as defined in the appended claims.