Facsimile and static presentation processing – Static presentation processing – Attribute control
Reexamination Certificate
2000-02-29
2004-09-28
Lee, Thomas D. (Department: 2624)
Facsimile and static presentation processing
Static presentation processing
Attribute control
C358S003120
Reexamination Certificate
active
06798542
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
The present invention relates to an image encoding apparatus suitable for adapting to an image forming apparatus using an areal tone method.
2. Description of the Prior Arts
There are following two types in image data performed by a printer.
(1) Raster image information inputted as bit map information. The raster image is generally gray-scale image.
(2) Vector information inputted as an graphic drawing command or text data and converted to raster information by being subjected to graphic drawing and rasterizing at printing. The vector information can generally be represented as an area where uniform pixel value is continuous.
The resolution of the raster information and that of the vector information (a size for one pixel at marking) are not always the same. The raster information showing a natural image is generally sufficient to have a relatively low resolution, with the result that it is expressed with low resolution. Further, the vector information showing a character or graphic image has an importance on positional information, so that it is expressed with high resolution.
For example, character-graphic image information that is vector information is frequently expressed by a binary with high resolution and half-tone image that is a raster image is frequently expressed with low resolution like a method (Conventional Example 1) disclosed in Japanese Unexamined Patent Application No. Hei 8-223423.
In Conventional Example 1, the raster image is gray-scale data of 300 dpi (dot per inch: 1 inch is approximately 25.4 mm) resolution and the vector image is binary data with 600 dpi resolution. At this time, an area for one pixel of the raster image corresponds to an area for four pixels that are the total of two pixels in the longitudinal direction and two pixels in the widthwise direction of the vector image. An example in which the raster image and vector image are present is shown in FIG.
28
. In
FIG. 28
, a single rectangular corresponds to one pixel, a shaded area is a raster image area and the other area is a vector image area.
There are sixteen kinds of a pattern of data for four pixels of the vector image corresponding to one pixel of the raster image as shown in FIG.
29
. In Conventional Example 1, the image is a raster image until the level of the pixel value of 0 to 239 in order to express the raster image and vector image on the same plane. Additionally, the image is a vector image until the level of 240 to 255. The data pattern of sixteen kinds shown in
FIG. 29
is allotted with respect to the pixel value level of 240 to 255. Since the raster image becomes 240 level, a tone compressing processing shown in
FIG. 30A
is performed in case where an image of 256 tones is inputted. A tone expanding processing shown in
FIG. 30B
is performed when an image of 256 tones is outputted.
A higher tone number or resolution is required for printing a digital image with high quality. A capacity of an image is represented by (pixel number×tone bit number), thereby being enormous. It is desired to make as small as possible the amount of an image transmitted to a printer or the amount of an image processed in the printer in order to reduce an accumulating cost of an image or transmitting cost.
Various image encoding methods have been proposed as a method for reducing the amount of image data. A typical image encoding method among these methods is JPEG Baseline method (Conventional Example 2). JPEG Baseline method is disclosed in “International Standard of Multi-media Encoding”, edited by Dr. Yasuda, Maruzen, p. 18 to p. 23 (JPEG: Joint Photographic coding Experts Group). This method is explained hereinafter with regard to FIG.
22
.
In
FIG. 22
, designated at
1001
is an input image,
1002
a block circuit,
1003
a DCT circuit,
1004
a quantizer,
1005
a quantizing table,
1006
a scan converting circuit,
1007
a significant coefficient detecting circuit,
1008
a grouping circuit,
1009
a ran length counter,
1010
a two-dimensional Huffman encoding circuit,
1011
a DC difference calculating circuit,
1012
a grouping circuit,
1013
an one-dimensional Huffman encoding circuit,
1014
a duplexing circuit and
1015
is an output code.
In
FIG. 22
, the inputted image
1001
is divided into blocks of 8×8 pixels (hereinafter referred to as pixel block) at the block circuit
1002
. The pixel block is DCT-transformed at the DCT circuit
1003
, whereby a transformed coefficient outputted as a result of the DCT is quantized at the quantizer
1004
in accordance with the quantizing step information memorized at the quantizing table
1005
. The quantized converting coefficient can be represented by a matrix of 8×8. The converting coefficient is generally positioned such that the coefficient in the longitudinal direction of the matrix corresponds downwardly to a higher DCT coefficient and the coefficient in the widthwise direction corresponds rightwardly to a higher DCT coefficient. The most leftward and uppermost coefficient among sixty-four converting coefficients is the one corresponding to a direct current frequency area of a DCT transforming area, so that it is called as a direct current component or DC coefficient. The other sixty-three coefficients correspond to an alternating current frequency area, so that it is called as an alternating current component or AC coefficient.
The difference from the DC component of the previous image block is taken out from the DC coefficient at the DC difference calculating circuit
1011
, and then the resultant DC coefficient is sent to the grouping circuit
1012
.
At the grouping circuit
1012
, group numbers and additional bits shown in
FIG. 25
are calculated from the DC difference. The additional bit is a value for specifying the DC difference in the same group. The bit numbers of the additional bit are shown in FIG.
25
.
The group numbers calculated at the grouping circuit
1012
is Huffman-encoded at the one-dimensional Huffman encoding circuit
1013
. Further, the additional bit is sent to the duplexing circuit
1014
.
The AC coefficient quantized at the quantizer
1004
is scan-converted to a zigzag scan order shown in
FIG. 23
at the scan converting circuit
1006
, and then, sent to the significant coefficient detecting circuit
1007
. The significant coefficient detecting circuit
1007
determines whether the quantized AC coefficient is “0” or except for “0”. If “0”, a count up signal is supplied to the run length counter
1009
for increasing the counter value by one. If the value of the AC coefficient is a significant coefficient except for “0”, a reset signal is supplied to the run length counter
1009
for resetting the counter value as well as the AC coefficient is sent to the grouping circuit
1008
.
The run length counter
1009
is a circuit for counting the run length of “0”. NNNN that is a number of “0” between the significant coefficients is sent to the two-dimensional Huffman encoding circuit
1010
. At the grouping circuit
1008
, the AC coefficient is divided into group numbers SSSS and additional bits shown in FIG.
24
. Then, the group numbers are sent to the two-dimensional Huffman encoding circuit
1010
and the additional bits are sent to the duplexing circuit
1014
. The additional bit is a value for specifying the DC difference in the same group. The bit numbers of the additional bit are shown in FIG.
24
.
The two-dimensional encoding circuit
1010
performs Huffman encoding to the combination of the run length NNNN and the group number SSSS, and send it to the duplexing circuit
1014
.
The duplexing circuit
1014
duplexes the DC coefficient Huffman code, AC coefficient Huffman code, DC coefficient additional bit and AC coefficient additional bit for one pixel block, and then, outputs code data
1015
.
As described above, JPEG Baseline encoding method is a lossy encoding method intended for the gray-scale image. Further, the JPEG Baseline encoding method decreases electricity in a high frequency range, in other words, reduces a redun
Kimura Shun-ichi
Koshi Yutaka
Shinohara Koichiro
Brinich Stephen
Fuji 'Xerox Co., Ltd.
Lee Thomas D.
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