JP2006129413A - Method and apparatus for compressing image data - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To compress pseudo gradation image data at high speed with high compressibility using a dither pattern and further to develop the image data at high speed using small-scaled hardware. <P>SOLUTION: A method for compressing pseudo gradation image data using a dither pattern includes: partitioning the image data for each of predetermined regions; determining whether an array pattern of dots of the image data in each region is matched with the dither pattern used for pseudo gradation; finding a representative value for a density of the image data in that region if matched; and creating compressed data using the found representative value. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to a compression method, a decompression method, and a compression apparatus for image data that has been pseudo-gradated using a dither pattern.

  In general, a printing system including a computer and a printer is used. In such a printing system, image processing such as pseudo gradation processing is performed on the computer side on the image data to be printed, and special processing is performed on the image data transmitted from the computer on the printer side. However, there is a method in which the data is output as it is and printed on paper.

  Conventionally, a raster printer is known as a printer used in this method. Since the raster printer does not perform special image processing on the printer side, it can be realized at low cost using small-scale hardware. However, on the other hand, since image data that can be printed on paper as it is is transmitted to the printer, there is a drawback that the amount of data to be transmitted becomes large. In addition, when character data is included in image data, the resolution must be increased in order to print characters clearly, and as a result, the amount of data transmitted to the printer is further increased. Therefore, it takes a lot of time to transmit image data from the computer to the printer.

  In order to solve this problem, it is necessary to compress the image data on the computer side. However, if the processing for compression is complicated, it takes time for the compression processing itself, and it takes time for the expansion processing on the printer side as well, and the scale of hardware for that becomes large and expensive. It becomes.

  Therefore, in order to realize a printing system that enables the use of inexpensive printers and performs high-speed processing as a whole, the compression processing is light, the processing at the time of compression is light, can be developed with small hardware, and a high compression rate can be realized. Technology is desired.

  By the way, in order to print multi-gradation image data with a printer, in many cases, the image data must be converted into pseudo gradations. A dither method has been well known as a pseudo gradation method. In the dither method, a dither pattern is used, and each threshold value of the dither pattern is compared with the value of each pixel of the image data to be binarized.

  As a compression technique focusing on the dither pattern, there is a method disclosed in Patent Document 1. According to the method disclosed in Patent Document 1, the binarized image data is divided into blocks of a predetermined size. The reference pattern corresponding to the number of dots included in an arbitrary image block is compared with the image block, and if the image block and the reference pattern match, a code indicating the reference pattern is assigned. Otherwise, the comparison result Is encoded.

  Further, as a compression technique for binarized image data, the JBIG system that has been accepted for adoption by the ITU (International Telecommunication Union) -T recommendation is known.

Further, Patent Document 2 discloses a method of compressing image data that has been pseudo-gradated with a dither pattern. According to the method described in Patent Document 2, the pixel value for each pixel is compared with a threshold value, thereby obtaining a range for each pixel.
JP-A-6-152986 USP 6201614

  However, in the method of Patent Document 1 described above, when the designated image block matches the reference pattern, the reference pattern is encoded, so the amount of data to be transmitted increases by the amount of the reference pattern code. .

  On the other hand, in the JBIG method, the compression process is relatively light, and the compression process can be performed at high speed even on a computer. However, according to the JBIG method, the compression rate is not so high as compared with other methods such as the LZS method or the LZW method, and the compression rate decreases particularly when halftone data increases.

  Further, in the method of Patent Document 2, since the value is determined for each pixel, the amount of information is not reduced by itself. Therefore, in order to reduce the amount of information, a means for separately compressing is necessary.

  The present invention has been made in view of the above-described problems, and can compress image data that has been pseudo-graded using a dither pattern at a high speed and with a high compression rate, and can also be performed at high speed with small hardware. It is an object of the present invention to provide a compression method, a decompression method, and a compression apparatus that can be restored by the above-described method.

  A compression method according to the present invention is a method of compressing pseudo-gradated image data using a dither pattern, and divides the image data into predetermined regions, and dot of image data in each region. It is determined whether or not the array pattern matches the dither pattern used for pseudo-gradation, and if it matches, a representative value related to the density of the image data in that area is obtained, and the compressed data is obtained using the obtained representative value. create.

  In dividing the image data into predetermined areas, for example, the image data is divided into areas of several 10 to 100 pixels. In that case, if the number of pixels is a multiple of 8, such as 24 pixels, 48 pixels, 96 pixels, etc., the processing is performed efficiently.

  Whether or not the dot arrangement pattern (dot pattern) matches the dither pattern is determined as follows, for example. That is, uniform image data having a certain density value (or gradation value) for all pixels is assumed. When the entire or part of the dot pattern obtained when the virtual image data is binarized by the dither pattern is equal to the dot pattern of one partitioned area, the dot pattern of the area is the same as the dither pattern. It is determined that they match. In other words, when a dot pattern is generated using a dither pattern for a certain density value, such a density value exists so that the generated dot pattern and the dot pattern of the area are equal to each other. It will be in agreement. Such a density value may be a specific value, or may take a plurality of values in a certain range. This density value is a representative value.

  Therefore, the above-described solution can be paraphrased as follows. That is, the image data is divided into predetermined areas, and whether or not the dot arrangement pattern of the image data in each area corresponds to at least a part of the dither pattern used for pseudo gradation processing. If it is discriminated and corresponds, a representative value relating to the density of the image data in that region is obtained, and compressed data is created using the obtained representative value.

Preferably, as the representative value, the density value of each pixel of the image data is compared by comparing the density value of each pixel of the image data in the region with the density value of each pixel of the corresponding portion of the dither pattern. When a dot is hit in a pattern area prepared in advance when it is small, the minimum value J of the density value of the pixel of the dither pattern corresponding to the dot hit in the area and the dot corresponding to the dot not hit J ≧ a ≧ K with the maximum density value K of the dither pattern pixels
The value a obtained so as to satisfy the following condition is used.

  Here, the density value of the dither pattern is usually provided by a threshold value of the dither pattern. Therefore, “the density value of each pixel in the corresponding portion of the dither pattern” can be rephrased as “the threshold value of each pixel in the corresponding portion of the dither pattern”.

  In addition, when a dot is shot when the density value of each pixel of the image data is large, the dot is printed with the minimum value J of the density value of the pixel of the dither pattern corresponding to the dot that has not been shot in the area. The representative value a may be obtained so as to satisfy the condition with the maximum density value K of the pixels of the dither pattern corresponding to the dots. Thus, in the present invention, the gradation, density, and the relationship between them and the absence of hitting dots can be applied in various combinations.

  The representative value is prepared in advance when the density value of each pixel of the image data is small by comparing the density value of each pixel of the image data in the region with the density value of each pixel of the dither pattern. When dots are hit in the pattern area, the number of dots hit or not hit in the area is used.

  In addition, as the representative value, a value that minimizes the difference between the representative values of adjacent regions in the range of each region is used.

  Further, when creating the compressed data, the difference between the representative values of each area and the other area is obtained, and the obtained difference is encoded.

  When there are a plurality of dither patterns used for pseudo gradation processing, the plurality of dither patterns are switched to determine whether or not they match the dot arrangement pattern of the image data in each area.

  Further, when the dot arrangement pattern of the image data in the area does not match the dither pattern used for pseudo gradation processing, the area is further divided into a plurality of small areas, and the image data in each small area is divided. It is determined whether or not the dot arrangement pattern matches the dither pattern.

Further, as the representative value, J ≧ a ≧ K between the minimum value J and the maximum value K.
The value a satisfying the above condition is used, and the number of dots hit or not hit in the area is used as the representative value in the small area. In this case, as the representative value in the small region, the representative value a obtained by the same method as that in the region may be used.

  In addition, when the dot arrangement pattern of the image data in the area or the small area does not match the dither pattern used for pseudo gradation processing, the pattern is hit or hit in the area or the small area. The compressed data is created by encoding an array of missing dots.

According to another aspect of the present invention, a first step of partitioning image data into predetermined areas, a dither pattern in which an array pattern of dots of image data in each area is used for pseudo gradation processing, and When the second step for determining whether or not they match and the result of the determination in the second step match, the representative values relating to the density of the image data in the region are represented by the minimum value J and the maximum value K. J ≧ a ≧ K
If the result of determination in the third step that satisfies the condition a and the determination in the second step do not match, the area is further divided into a plurality of small areas, and image data dots in each small area When the fourth step for determining whether or not the array pattern matches the dither pattern and the result of determination in the fourth step match, the representative value in the small region is entered in the region. A fifth step of determining the number of dots that have been struck or not struck, and a sixth step of encoding the arrangement of dots in the small region when the result of determination in the fourth step does not match; A seventh step of performing encoding based on the obtained representative value when the determination results in the second step or the fourth step match. With the door.

  In the restoration method according to the present invention, the representative value of each area is acquired from the compressed image data, and the acquired representative value is compared with the dither pattern to reproduce the dot pattern.

  A compression device according to the present invention is a device for compressing pseudo-gradated image data using a dither pattern, and means for partitioning the image data into predetermined regions, and image data in each region. Means for determining whether or not the dot arrangement pattern matches the dither pattern used for pseudo-gradation, means for determining a representative value for the density of the image data in that area, and a representative value obtained And means for creating compressed data using.

  In the present invention, the pseudo gradation image data may be binary image data, or multi-value image data such as 4-value, 8-value, and 16-value.

  According to the present invention, image data that has been pseudo-gradated using a dither pattern can be compressed at a high speed and with a high compression rate, and can be restored at high speed with a small amount of hardware. As a result, the entire process can be performed in a short time while using an inexpensive printer.

In the description of the embodiment, first, the case of compressing pseudo-graded binary image data will be described, and second, the case of compressing pseudo-gradated 4-level image data. explain. In the second description, only the main points of the differences from the first will be described.
[First]
Embodiment for compressing binary image data [Configuration of entire system]
FIG. 1 is a diagram showing an overall configuration of a print system 1 to which an image data compression method according to the present invention is applied.

  In FIG. 1, the print system 1 includes a computer main body 11, a display 12, a printer 13, a keyboard 14, a mouse 15, and the like.

  The computer main body 11 pseudo-gradates image data input from the outside or image data generated inside (original image data) using a dither pattern by a dither method. Pseudo gradation is sometimes called halftoning. In the present embodiment, binarization is performed as pseudo gradation processing, and binary image data D1 is generated. Then, the generated binary image data D1 is compressed to generate compressed data D2, and the generated compressed data D2 is transmitted to the printer 13. The printer 13 restores binary image data (halftone image) with respect to the received compressed data D2 by referring to the dither pattern used for binarization and prints it out on paper or the like.

  In the present embodiment, during the compression process, the binary image data D1 is separated into a dither pattern information component and an image information component. Then, only the image information component is extracted and encoded by the Huffman method to obtain compressed data D2. The dither pattern information component is not included in the compressed data D2. Incidentally, conventionally, both the dither pattern information component and the image information component have been compressed together.

  More specifically, in the course of the compression processing of the present embodiment, the binary image data D1 is divided into predetermined regions (low-resolution regions TL described later), and the dot pattern of the image data in each region is binary. It is determined whether or not it matches the dither pattern used for conversion, and if it matches, a representative value a regarding the density of the image data in that area is obtained. Then, difference information of the representative value a between adjacent areas is obtained, and the obtained difference information is encoded by the Huffman method to obtain compressed data D2. The dither pattern used for binarization is a dither pattern information component, and the representative value a is an image information component.

  In the binarization process, a plurality of dither patterns are switched and used depending on the type of area such as a character area or an image area. Therefore, even during the compression process, the plurality of dither patterns are switched and used in each area. It is determined whether or not it matches the dot arrangement pattern of the image data.

  If it does not match any dither pattern, the area is further divided into a plurality of small areas (medium resolution area TM to be described later), and the dot pattern of the image data in each small area matches the dither pattern. It is determined whether or not. If they match, the representative value is the number of dots hit in the small area. If they do not match again, the compressed data D2 is obtained by encoding the dot arrangement of these areas or small areas.

  The computer main body 11 transmits the obtained compressed data D2 to the printer 13. The computer main body 11 also transmits in advance to the printer 13 information on the dither pattern and a decoding table DC that is a table for restoration (decoding) by the Huffman method. As the decoding table DC, there are decoding tables DC1 to DC3 for the low resolution area, the medium resolution area, and the high resolution area, respectively. Details will be described later.

  The printer 13 acquires the representative value a of each area from the compressed data D2 transmitted from the computer main body 11, compares the acquired representative value a with the corresponding dither pattern, and is the same as the original binary image data D1. Reproduce the dot pattern (dot arrangement pattern). In such restoration processing (decoding processing), the decoding table DC is used for restoration by the Huffman method.

As the computer main body 11, a personal computer, a workstation, and other various computers are used. As the printer 13, a raster printer, a GDI printer, and other various printers are used.
[Compression processing]
Next, the compression process in the computer main body 11 will be described in more detail.

  2 is a block diagram showing a functional configuration of the computer main body 11, FIG. 3 is a block diagram functionally showing the compressed data creating unit 100 of the computer main body 11, and FIG. 4 is a block diagram showing a functional configuration of the printer 13. 5 is a diagram for explaining the partitioned low resolution region TL, FIG. 6 is a diagram illustrating an example of the low resolution region TL and the dither pattern DP, and FIG. 7 is a diagram illustrating the low resolution region TL and the dither pattern DP having different sizes. It is a figure which shows the example of.

  As shown in FIG. 2, the computer main body 11 includes an image database 150, a dither pattern storage unit 160, a pseudo gradation unit 170, a compressed data creation unit 100, and the like.

  The image database 150 holds a large number of image data (original image data) FD1, FD2,. All or part of the image data FD1 to FD may be described as “image data FD”. Note that most of the image data FD is a color image. In this case, one image data FD is composed of image data of each color of C (cyan), M (magenta), Y (yellow), and K (black). Is done. The image data FD is obtained, for example, by inputting from a scanner, a digital camera, or other external source, or by editing or generating inside.

  The dither pattern storage unit 160 holds a plurality of types of dither patterns DP11 to DP13, DP21 to 23, DP31 to 33, and DP41 to 43. All or part of these may be described as “dither pattern DP”.

  The dither pattern DP is a character area dither pattern DP11, 21, 31, 41, an image area dither pattern DP12, 22, 32, 42, and a chart area dither pattern DP13 for each color of C, M, Y, and K. 23, 33, 43, etc. are provided.

  The pseudo gradation unit 170 performs binarization processing on the image data FD stored in the image database 150 using the dither pattern DP selected from the dither pattern storage unit 160, and the obtained binary image data D1. Is sent to the compressed data creation unit 100. The binary image data D1 is also composed of binary image data of C, M, Y, and K colors.

  The compressed data creation unit 100 compresses the binary image data D1 to generate compressed data D2, and outputs the generated compressed data D2, the dither pattern DP, and the decode table DC to be transmitted to the printer 13.

In FIG. 3, the compressed data creation unit 100 includes a low resolution region partition unit 101, a low resolution comparison unit 102, a low resolution representative value calculation unit 103, a medium resolution region partition unit 104, a medium resolution comparison unit 105, and a medium resolution representative value calculation. Unit 106, dot pattern extraction unit 107, encoding unit 108, and data transmission unit 109.
[Low-resolution area processing]
The low resolution area dividing unit 101 divides the binary image data D1 sent from the pseudo gradation unit 170 into a low resolution area TL, which is a large number of small areas. The low resolution region TL is a rectangular region including 96 (6 × 16) pixels TP as shown in FIG. 5, for example. In the example of FIG. 5, the entire area of the binary image data D1 is partitioned up to TLn in order from the upper left, such as low resolution areas TL1, TL2, TL3,.

  The low resolution comparison unit 102 compares the dot pattern of each low resolution region TL with the dither pattern DP and determines whether or not they match each other. Whether or not they match is determined as follows.

  That is, uniform image data having a certain density value (or gradation value) for all pixels is assumed. When the dot pattern obtained when the virtual image data is binarized by the dither pattern DP is equal to the dot pattern of the low resolution area TL, the dot pattern of the low resolution area TL matches the dither pattern DP. Determine. Any value may be used as the density value used for discrimination. In other words, it can be said that when there is a density value such that the dot patterns are equal to each other when the dot pattern is generated using the dither pattern DP, it is determined that they match. Therefore, such a density value may be a specific value or may have a plurality of values in a certain range. This density value is the representative value a described above. These relationships will be described later.

  In the low resolution comparison unit 102, the dot pattern in the low resolution region TL and the dither pattern DP are compared with each other in order from the left and from the top to the bottom for the binary image data D1. For example, for a plurality of unit lines (lines) above, the process is performed for each region from the left end toward the right, and when one unit line ends, the unit line returns to the left end of the unit line below and returns to the right. Are performed in turn for each region, and end in the lower right region.

  As the dither pattern DP used for comparison, a dither pattern DP corresponding to each color of the binary image data D1 is used. The character area dither pattern DP is first used corresponding to each color. When the character area dither pattern DP does not match, the image area dither pattern DP is used next. When the character area dither pattern DP also does not match, the chart area dither pattern DP is used. Thus, when they do not match, the dither pattern DP is sequentially switched. Information indicating that the dither pattern DP has been switched is used in encoding as information for specifying the used dither pattern DP. If none of the dither patterns DP match, a discrimination result “not matched” is output.

The low resolution representative value calculation unit 103 obtains the representative value a when the discrimination results in the low resolution comparison unit 102 match. The method for obtaining the representative value a is as follows.
[How to find representative value a]
In the low resolution region TL shown in FIG. 6A, the black pixels are pixels on which dots are formed. Here, image data FD in a region corresponding to the low resolution region TL among the image data FD having gradation before binarization is considered. Such image data FD is referred to herein as “image data FDL”. Then, when the density value of each pixel of the image data FDL is less than the threshold value of the corresponding pixel of the dither pattern DP shown in FIG. That is, here, it is assumed that the smaller the density value, the higher the density.

  In that case, when a dot is formed in a certain pixel, it can be said that the density value of the pixel is less than the threshold value of the corresponding pixel of the dither pattern DP. In other words, the upper limit value of the density of the pixel is “1” smaller than the threshold value of the corresponding pixel of the dither pattern DP. On the other hand, when the dot is not printed, it means that the density value of the pixel is equal to or higher than the threshold value of the corresponding pixel of the dither pattern DP. In other words, the lower limit value of the density of the pixel is the threshold value of the corresponding pixel of the dither pattern DP.

Therefore, in the low resolution region TL and the dither pattern DP, the upper limit value and the lower limit value of each pixel are totaled to obtain the minimum value J of the upper limit value and the maximum value K of the lower limit value. About the minimum value J of these upper limits and the maximum value K of the lower limits,
J ≧ K (1)
If the relationship of
J ≧ a ≧ K (2)
There exists “a” that satisfies the above. This “a” is the representative value a. In other words, when the above equation (1) holds, the dot pattern in the low resolution region TL and the dither pattern DP match and there is a representative value a. If the representative value a is known, the dot pattern of the low resolution area TL can be restored from the dither pattern DP. That is, by obtaining only one representative value a in each region as an image information component, it is possible to reproduce the binary image data D1 in that region using the dither pattern DP that matches the low resolution region TL. It is.

  Therefore, by transmitting this representative value a to the printer 13, the printer 13 can reproduce the dot pattern of the binary image data D1 using the same appropriate dither pattern DP as when the binary image data D1 was obtained. is there.

  In the example of FIG. 6, it is assumed that dots are formed when the density value of each pixel of the image data FDL is less than the threshold value of the dither pattern DP. As shown, a dot may be formed when the density value of each pixel of the image data FDL is equal to or greater than the threshold value of the dither pattern DP5. That is, the higher the density value, the higher the density. In this case, when a dot is shot at a certain pixel, the density value of the pixel is equal to or greater than the threshold value of the corresponding pixel of the dither pattern DP5, that is, the lower limit value of the density of the pixel. Is the threshold value of the corresponding pixel of the dither pattern DP5. When the dot is not printed, the density value of the pixel is less than the threshold value of the corresponding pixel of the dither pattern DP5, that is, the threshold value of the corresponding pixel of the dither pattern DP5 is “ It means that the value was smaller by 1 ”. In this case, similarly to the above, “a” satisfying the expression (2) is set as the representative value.

  If the image data FD has 256 gradations for each color, the representative value a has an 8-bit information amount. In the present embodiment, the low resolution area TL has an information amount of 6 × 16 = 96 bits, and this can be expressed by 8 bits. Therefore, the information amount can be compressed to about 1/10. For most image data FD, the representative values a are close to each other in the adjacent low resolution region TL. That is, there is a property that a difference in density is small in a neighboring region, and therefore a difference in representative value a is small. Therefore, if the difference between the representative value a of a certain low resolution area TL and the representative value a of the low resolution area TL obtained immediately before is taken, the difference is often “0”, and the statistical frequency of the difference The bias becomes larger. That is, by using the difference of the representative value a instead of the representative value a itself, it is possible to compress at a higher compression rate by the Huffman method encoding. As a result, it is possible to further compress the signal into, for example, a fraction in encoding.

  In the example of FIG. 6, an example in which the size of the low resolution region TL is divided so as to be the same as the size of the dither pattern DP is shown, but these sizes may be different from each other.

For example, as shown in FIG. 7, the size of the low resolution region TLb may be smaller than the size of the dither pattern DPb. In this case, the plurality of low resolution regions TLb _n and TLb _{n + 1} are compared with different portions in the dither pattern DPb. In this case, the coordinate position of the dither pattern DPb to be applied to the first low-resolution area TLb of the binary image data D1 is determined, and then the dither pattern DPb is sequentially shifted so that all the low-resolution areas TLb On the other hand, the coordinate position of the dither pattern DPb to be applied is uniquely determined.

  Contrary to the example of FIG. 7, the size of the low resolution area TL may be larger than the size of the dither pattern DP.

  The representative value a described above can be obtained by various methods as is apparent from the above description. Next, as one example, a method for obtaining the representative value a with reference to a table created in advance will be described.

  As described above, what is necessary for obtaining the representative value a is the minimum value J of the upper limit value and the maximum value K of the lower limit value of each pixel value corresponding to the dot pattern of a certain region. When the dither pattern DP is given, these are determined by the position in the dither pattern DP and the dot pattern of the area. The position in the dither pattern DP can be represented by two variables as the coordinates of the first pixel of the area. The dot pattern can be represented by an integer value of 0 to 255 per block when it is considered as one block every 8 pixels (see FIG. 14). In this case, since an integer value can be obtained simply by interpreting the dot pattern of 8 pixels as a numerical value, no conversion is necessary. Therefore, for each pixel of the dither pattern DP, there may be a table in which the minimum value J of the upper limit value and the maximum value K of the lower limit value are described corresponding to 256 dot patterns of 0 to 255, respectively. That is, if there is a table for converting data of the number of pixels of the dither pattern DP × 256, all can be described. With such a table, the values (minimum value J and maximum value K) described at the position can be easily extracted at high speed from the position coordinates in the dither pattern DP and the integer value of the dot pattern. In this embodiment, such a table is created as an upper / lower limit table TJK.

  FIG. 8 shows an example of the upper / lower limit table TJK.

  The upper and lower limit table TJK shown in FIG. 8 shows the correspondence between the coordinates and dot pattern in a dither pattern DP and the minimum value J of the upper limit value and the maximum value K of the lower limit value for a dither pattern DP. Yes.

  Therefore, the above-described low resolution region TL is divided into 12 blocks of 8 pixels, and the minimum value J and the maximum value K are obtained for each block. For example, when the coordinate in the dither pattern DP of a certain block is (0, 2) and the integer value of the dot pattern is “0”, the minimum value J is “255” and the maximum value from the upper / lower limit table TJK. It can be seen that the value K is “141”.

  Based on the minimum value J and maximum value K of the 12 blocks obtained in this way, the entire minimum value J and maximum value K of the low resolution region TL are obtained. That is, the minimum value J of the low resolution area TL is the smallest of the 12 minimum values J, and the maximum value K of the low resolution area TL is the largest of the 12 maximum values K. is there.

  Thus, by using the upper / lower limit table TJK, the processing for calculating the representative value a can be realized by the operation of reading data from the upper / lower limit table TJK of about 2 Mbytes at most. Since reading from the table can be performed at a high speed, the representative value a can be obtained at a high speed. Moreover, since this processing is a heavy load in the entire compression processing, the entire processing time can be greatly shortened.

  Note that the upper / lower limit table TJK can also be used to determine whether an 8-pixel block matches the dither pattern DP.

  As described above, the representative value a is obtained from the obtained minimum value J and maximum value K. The representative value a may be a specific value, or may take a plurality of values spread over a certain range. However, for the printer 13 to reproduce the dot pattern of the binary image data D1, only one representative value a is sufficient. Therefore, a method for narrowing the obtained representative value a to a specific value when the representative value a spreads over a certain range will be described.

  FIG. 9 is a diagram showing an example of transition of representative values for a plurality of low resolution regions TL.

  In FIG. 9, the horizontal axis indicates the number of the low resolution region TL, and the vertical axis indicates the representative value. As shown in FIG. 9, the representative value has a certain range ET. Therefore, the representative value a is determined so that the change of the representative value a is as small as possible, that is, the difference between the representative values a of the adjacent low resolution regions TL is “0” as much as possible.

  That is, the representative value a of the first low-resolution area TL that is the leftmost side in FIG. 9 is determined as the center value in the range, and the representative value a of the second low-resolution area TL that is adjacent to the right is the first representative value a. The same value as the representative value a. If the representative value a of the third low-resolution area TL is the same value as the second representative value a, the representative value a is determined so as to fall within the range. For the fourth, as in the third, the representative value a is determined so as to fall within the range. The fifth representative value a is the same value as the fourth representative value a. The difference of the representative value a determined in this way is shown in the lower part of the figure. By increasing “0” as the difference of the representative value a, the frequency deviation becomes large, and a high compression rate is obtained in the Huffman method encoding.

  By the way, since the range of values that the representative value a can take is 0 to 255, when a simple subtraction is performed, the range of the difference is −255 to +255, and the amount of information necessary to express this is 9 A bit. However, in the present embodiment, the difference is not obtained by simple subtraction, but the difference is obtained assuming that the representative value a is a cyclic integer of 0 to 255. As a result, all the differences are represented by integers from 0 to 255, and the amount of information necessary to represent this is 8 bits, which is reduced to half.

  Next, a method for obtaining the difference assuming that it is a cyclic integer will be described. In order to simplify the description, a cyclic integer of 0 to 8 will be described.

  FIG. 10 is a diagram showing a cyclic integer of 0 to 8.

  In FIG. 10, in order to obtain a difference C between a certain number A and a certain number B, the position number corresponding to the number B is rotated leftward from the position indicated by the number A in the cyclic integer. The numerical value of the stopped position is defined as a difference C. For example, the difference between “5” and “3” is “2” obtained by rotating three rotations from the position of the cyclic integer “5” to the left. In another example, the difference between “0” and “8” is “1”, which is obtained by rotating eight leftward from the position of the cyclic integer “0”. In yet another example, the difference between “3” and “5” is “7”, which is obtained by rotating left by five from the position of the cyclic integer “3”. In this way, the difference is obtained as an integer value in the range of 0-8.

  Further, a certain number A is obtained by adding the difference C to the certain number B. In this case, the number of positions corresponding to the difference C is rotated to the right from the position indicated by the number B having the cyclic integer, and the numerical value of the stopped position is set to the number A. In this way, it can be completely restored.

  FIG. 11 is a diagram showing the distribution of the appearance frequency of the difference of the representative value a in the image.

  As shown in FIG. 11, the appearance frequency is high in the ranges where the difference is about “0” to “20” and about “230” to “255”. Such a distribution is almost the same regardless of the type of image, and the deviation is very large, so that most images can be greatly compressed by the Huffman method by using the difference.

  Depending on the image, one low resolution area TL can be compressed to about 1 to 2 bits. The probability that the dot pattern of the 6 × 16 pixel low-resolution area TL matches the dither pattern DP is about 95% in most images. That is, in an area of approximately 95% of the entire image, data originally 96 bits can be expressed by 1 to 2 bits, and compression can be performed at a compression rate as high as several tens of times at this point.

  In FIG. 11, the appearance frequencies of three values “256”, “257”, and “258” are shown after 0 to 255, which are the differences of the representative value a. This is to indicate the state with a specific three numerical values when a predetermined state occurs, thereby further reducing the amount of information and further increasing the compression rate.

  For example, since pixels with the same density frequently continue in the image for a long time, as described later, when the same density continues over 50 regions, that is, when the difference “0” continues 50 times, it is set to “257”. It is expressed by one attribute code. “256” is an attribute code indicating that a certain low resolution area TL does not match any dither pattern DP, and “258” indicates that the dither pattern DP is switched, that is, a certain low resolution area TL is switched. This is an attribute code indicating that it matches the other dither pattern DP. When switched twice, “258” is output twice.

  As described above, in the low resolution representative value calculation unit 103, the representative value a is obtained in order for the low resolution region TL, and a difference between adjacent regions is obtained. Data to be sent to the encoding unit 108 is created based on the difference and the attribute value.

For example, when “0” continues as the difference 50 times, the attribute value “257” is output to the encoding unit 108. The value of the difference “0” is not output. If the difference “0” has not been repeated 50 times, “0” is output for the number that has been continued until then, and then a difference that is not “0” is output. When the dither pattern DP is switched, the attribute code “258” is output for the number of times of switching. If the low resolution area TL does not match any dither pattern DP, the attribute code “256” is output. In this case, the low resolution area TL is processed by the medium resolution area dividing unit 104 described below.
[Processing of medium resolution area and high resolution area]
12 is a diagram showing the low resolution region TL and the medium resolution region TM, FIG. 13 is a diagram showing the distribution of the appearance frequency of the difference in the number of dots in the image, and FIG. 14 is a diagram for explaining the digitization of the dot pattern. 15 is a diagram showing the distribution of the appearance frequency of each dot pattern.

  In the medium resolution area dividing unit 104, the low resolution area TL is further divided into four medium resolution areas TM of 3 × 8 pixels as shown in FIG.

  The medium resolution comparison unit 105 determines whether or not each dot pattern matches a part of the dither pattern DP in each medium resolution region TM by the same method as in the low resolution region TL. That is, since the medium resolution area TM is composed of three high resolution areas TS of 8 pixels, the minimum value J and the maximum value K are read out from the upper / lower limit table TJK described above three times and totalized. It can be determined whether or not it matches the dither pattern DP. The reason for determining whether or not the pattern matches the dither pattern DP is that the medium resolution area TM is used because the frequency of matching increases as the area becomes smaller.

  In the middle resolution representative value calculation unit 106, when the middle resolution area TM matches the dither pattern DP, the number of dots applied to the middle resolution area TM, for example, the number of black dots, is obtained as a representative value. Since the total number of dots in the medium resolution area TM is 24, the amount of information is not so large even if the number of dots is a representative value, and the process of counting the number of dots is fast. It is possible to restore the original dot pattern from the number of dots. Then, based on the obtained representative value, the difference in the representative value between the adjacent medium resolution areas TM is calculated in the same manner as in the case of the low resolution area TL described above. The difference here is in the range of 0 to 24 because the cyclic integer described above is used.

  As shown in FIG. 13, the appearance frequency is high in the range where the difference is about “0” to “3” and “21” to “24”. Such a distribution is almost the same regardless of the type of image, and the deviation is very large. Therefore, a high compression ratio can be obtained by using the difference. For example, a compression ratio of about ten times can be obtained.

  In FIG. 13, the appearance frequency for the value “25” is shown after 0 to 24 as the difference. The meaning of this is the same as the attribute code in the case of the low resolution area TL, and “25” is an attribute code indicating that a certain medium resolution area TM does not match any dither pattern DP.

  When the processing of the four medium resolution areas TM for one low resolution area TL is completed, the process returns to the processing for the low resolution area TL again.

  The dot pattern extraction unit 107 further divides the medium resolution area TM into three high resolution areas TS of 8 pixels and quantifies the dot pattern of the high resolution area TS when the medium resolution area TM does not match. To do. In the digitization of the dot pattern, for example, as shown in FIG. 14, the doted pixel is represented by a binary number “1”, and the non-printed pixel is represented by “0”, which is converted into a decimal number. This is output as an attribute code.

  As shown in FIG. 15, it can be seen that the distribution is considerably biased and concentrated on a specific value. Accordingly, even in this case, a high compression rate can be obtained by encoding using the Huffman method. For example, a compression ratio of about twice can be obtained.

  When the processing of the three high resolution areas TS for one medium resolution area TM is completed, the process returns to the process for the medium resolution area TM again.

The encoding unit 108 encodes input data, that is, a difference in the representative value a, a difference in the number of dots, an attribute code, and the like by the Huffman method. The compression by the Huffman method is very effective for an object whose signal frequency distribution does not change greatly. Since the Huffman method itself is publicly known, detailed description thereof is omitted here.
[Explanation of Huffman code table]
In this embodiment, the difference and attribute code of the representative value a for the low resolution area TL, the difference and attribute code of the number of dots for the medium resolution area TM, and the attribute code for the high resolution area TS are respectively independent codes. 1 to 3 are encoded. Therefore, three dedicated Huffman code tables FH1 to FH3 are provided for each.

  FIG. 16 is a diagram showing an example of the Huffman code tables FH1 to FH3. FIG. 16A shows the Huffman code table FH1 for code 1 for the low resolution area, FIG. 16B shows the Huffman code table FH2 for code 2 for the medium resolution area, and FIG. 16C for the high resolution area. A Huffman code table FH3 for code 3 is shown. These will be briefly described.

  In FIG. 16A, the Huffman code table FH1 includes items such as an input, an output code, and the number of output digits. The relationship between the input and the output code is determined in advance by encoding by the Huffman method based on the appearance frequency of each data. The output code is actually stored in the memory as, for example, 4 bytes of data, and a code that is substantially less than 4 bytes is padded with “0” in the upper digit.

  For the input data, the data of the term of the output code corresponding to the input term corresponding to the input data is read from the least significant digit by the number of digits indicated by the term of the number of output digits. For example, when the input is “3”, “1000100” which is 7 digits of the output code “. The read “1000100” becomes the compressed data D2.

  Similarly, the Huffman code tables FH2 and 3 shown in FIGS. 16B and 16C are also provided with items such as input, output code, and number of output digits. The relationship between these input and output codes is determined in advance by encoding by the Huffman method for the three Huffman code tables FH1 to FH3.

  For example, in the Huffman code table FH2, when the input is “1”, “1010” that is four digits of the output code “. In the Huffman code table FH3, when the input is “1”, “1010”, which is the four digits of the output code “.

  Although these Huffman code tables FH1 to 3 may be converted into the same code, compression is performed on which code area corresponds to which code 1 to 3 is converted. Since it can be recognized, the decoding table DC corresponding to it is selected, and complete restoration is possible.

  For example, in encoding, code 1 is encoded using the Huffman code table FH1 for the low resolution area until “256” appears in the data. When “256” appears, after “256” is encoded with code 1, it is switched to the Huffman code table FH2 for the medium resolution area, and the code of code 2 is encoded until encoding of the four medium resolution areas TM is completed. Will continue. If “25” appears during encoding of code 2, “25” is encoded with code 2 and then switched to the Huffman code table FH3 for the high-resolution area, and the three high-resolution areas TS The encoding of code 3 is continued until the encoding of is completed. When the encoding of the three high resolution areas TS is completed, the process returns to the encoding of the code 2, and when the encoding of the four medium resolution areas TM is completed, the process returns to the encoding of the code 1 again. Thereafter, the input data is sequentially encoded according to this rule, and the compressed data D2 is created.

  Further, the compressed data creation unit 100 creates decode tables DC1 to DC3 for restoring the compressed data D2 encoded by the Huffman code tables FH1 to FH3.

  The data transmission unit 109 transmits the compressed data D2 created by the encoding unit 108 to the printer 13. In addition, the data transmission unit 109 transmits all the dither patterns DP and the decode table DC to the printer 13 in advance.

The decoding table DC is created based on the appearance frequency of data. The appearance frequency of each data can also be obtained by actually executing the algorithm in this embodiment. For example, as such a frequency table, a table created by summing all the frequencies obtained for the dither patterns DP for the character area, the image area, and the chart area for each color of CMYK can be used. . Ideally, the frequency table should be obtained for each image to be compressed, but even if it is not done, sufficient compression performance can be obtained on the basis of the frequency table created as a sum as described above. For the same reason, the same frequency table created as described above can be used for each region such as a character region, an image region, and a chart region for each color of CMYK.
[Restore processing]
Next, restoration processing in the printer 13 will be described.

  4, the printer 13 includes a dither pattern storage unit 360, a data restoration unit 300, a decode table storage unit 370, a line buffer 380, and the like.

  The dither pattern storage unit 360 holds the same dither pattern DP stored in the dither pattern storage unit 160 of the computer main body 11. The dither pattern DP is transmitted from the computer main body 11 in advance, but the same dither pattern DP stored in an appropriate memory may be built in the printer 13 in advance.

  The decode table storage unit 360 stores the decode table DC transmitted from the computer 11.

  The data restoring unit 300 restores the compressed data D2 received from the computer 11 with reference to a predetermined dither pattern DP and the decoding table DC, and reproduces a dot pattern. At the time of decompression of the compressed data D2, first, the decompression process by the decode 1 is performed using the decode table DC1 for the low resolution area, and the decompression process by the decode 2 using the decode table DC2 for the medium resolution area according to the conditions. Alternatively, the restoration process by the decode 3 using the decode table DC3 for the high resolution area is performed. That is, the compressed data D2 encoded by the codes 1, 2, and 3 are restored by the decodes 1, 2, and 3, respectively.

  FIG. 17 is a diagram showing an example of the decode table DC2.

  In FIG. 17, the decode table DC2 has items such as the number of symbols, Root, child 0, child 1 and the like. Based on the input data, the original data can be obtained by sequentially tracing the table from the position of Root = 24. For example, if the input data is “011011”, the top of the data is “0”, so the process starts with the child 0 of Root = 24. Since the value of the child 0 of Root = 24 is “23” and the next value of the data is “1”, next, the child 1 of Root = 23 is seen. Since the value of the child 1 of Root = 23 is “22” and the next value of the data is “1”, the child 1 of Root = 22 is seen next. Thereafter, the same operation is repeated, and the process ends when the value of child 0 or child 1 becomes negative. The sum of the last obtained value (negative value) and the number of symbols (in this case “26”) is the original data. Thereafter, the same processing is performed from the next value of the data, and it is repeated until the data expansion is completed.

  In the reproduction of the dot pattern, the restoration process is first performed by the decode 1. When the value restored by the decoding table DC1 is “258”, it indicates that the dither pattern DP has been switched. When a plurality of “258” continues, the dither pattern DP is sequentially switched as many times as the number of times followed, and the dither pattern DP after the switching is set as a dither pattern (current dither pattern) DP to be used thereafter.

  When the restored value is “256”, the subsequent processing is switched to the restoration processing by decoding 2 using the decoding table DC2 for the medium resolution area. If the restored value is “257”, it means that “0” has continued 50 times for the difference between the representative values, and therefore, the low-resolution area TL previously calculated for 50 areas by the current dither pattern DP. The dot pattern is reproduced with the same value as the representative value of, and sent to the line buffer 380. When the end of the line is reached before the processing for 50 areas is completed, the rest is sent to the line buffer 380 as data of the next line. If the restored value is none of these, the value is a difference between representative values. In this case, the representative value a of the low resolution region TL calculated last time is set as an initial value, and the current representative value a is obtained by adding the difference to the initial value. In this manner, the representative values a of all the low resolution areas TL are obtained by accumulating the differences. If this is the first time, the initial value is set to “0” to obtain the representative value a. Then, a dot pattern is reproduced from the obtained representative value a and the current dither pattern DP and sent to the line buffer 380.

  In the restoration process by the decode 2, the restoration is performed by the decode table DC2 for the medium resolution area. When the value restored by the decode 2 is “25”, the subsequent processing is switched to the restoration processing of the decode 3 for the high resolution area. If the restored value is not “25”, the value is the difference between the representative values (number of dots) of the medium resolution area TM. In this case, the representative value is obtained by accumulation as in the case of the low resolution region. From the obtained representative value and the current dither pattern DP, the dot pattern of the medium resolution region TM is reproduced. When the processing for the four medium resolution areas TM is completed, the process returns to the decode 1.

  In the restoration process by the decode 3, the restoration is performed by the decode table DC3 for the high resolution area. The result restored by the decode 3 represents an array of dots for 8 pixels. The restoration for the three high resolution areas TS is repeated, thereby reproducing the dot pattern of one medium resolution area TM. Thereby, it is counted that one restoration process of the medium resolution area TM is completed, and the process returns to the decoding 2 of the calling process.

  As described above, the attribute codes “256” and “25” function as code switching signals between areas, and when these attribute codes appear, switching from code 1 to code 2 or from code 2 to code 3 is definitely performed. Can do.

In the line buffer 380, the binary image data sent from the data restoration unit 300 is temporarily stored. The binary image data stored in the line buffer 380 is output every six lines, for example, and printed out on paper.
[Explanation by flowchart]
Next, processing in the computer main body 11 and the printer 13 will be described with reference to flowcharts.

  18 is a flowchart showing a general flow of compression processing in the computer main body 11, and FIG. 19 is a flowchart showing a general flow of decompression processing in the printer 13.

  In FIG. 18, after the dither pattern DP is read as preparation (# 11), the binary image data D1 is read (# 12). The binary image data D1 is divided into low resolution areas TL (# 13), and it is determined whether or not one low resolution area TL matches the dither pattern DP (# 14). When there are a plurality of dither patterns DP, the dither patterns DP are switched until they match. If they match (Yes in # 14), the representative value a is obtained (# 15), the difference is taken (# 16), and encoding is performed (# 17).

  If the pattern does not match in step # 14, it is divided into medium resolution areas TM (# 19), and it is determined whether one medium resolution area TM matches the dither pattern DP (# 20). If they match, the number of dots is obtained (# 21), the difference is taken (# 22), and encoding is performed (# 23). If the patterns do not match in step # 20, the pattern is divided into high resolution areas TS (# 25), and a dot arrangement is obtained for one high resolution area TS (# 26) and encoded (# 27). .

  Such a process is performed until all of the read binary image data D1 is completed (# 18, 24, 28).

  In FIG. 19, the dither pattern DP and the decode table DC are read as preparation (# 31, 32). The compressed data D2 is read (# 33), the representative value a is obtained (# 34), and the dot pattern is obtained by referring to the dither pattern DP (# 35, 36). Note that the description of the restoration processing of the medium resolution area TM and the high resolution area TS is omitted.

  Next, it demonstrates using a more detailed flowchart.

  20 and 21 are flowcharts of compression processing in the compressed data creation unit 100, and FIGS. 22 and 23 are flowcharts of decompression processing in the data restoration unit 300. Note that these flowcharts show processing for one color component in CMYK.

  20 and 21, first, the dither pattern DP and the decode table DC are read (# 101, 102). Further, the dither pattern DP and the decode table DC are transmitted to the printer 13 in advance. An upper / lower limit table TJK is created (# 103). Six lines of the binary image data D1 are input (# 104), and it is determined from the left end whether or not one low resolution area TL matches the dither pattern DP (# 105). If they match, the representative value a is obtained by referring to the upper and lower limit table TJK (# 106), and the representative value difference is calculated (# 107).

  If the representative value difference is “0” (Yes in # 108), one variable n indicating the number of consecutive times is added (# 109). When the variable n becomes “50” (Yes in # 110), the attribute code “257” indicating that the representative value difference “0” has continued 50 times is encoded with the code 1 and output as the compressed data D2. (# 111), variable n is initialized to “0” (# 112).

  If NO in step # 105, that is, if the pattern does not match the dither pattern DP, the representative value difference “0” is encoded and output by the code 1 (# 120), and the variable n is set to “0”. (# 121). Then, it is checked whether or not it matches with another dither pattern DP (# 122). If there is a matching dither pattern DP (Yes in # 122), the dither pattern DP is switched to (# 123), and the attribute code “258” indicating that the dither pattern DP has been switched is encoded by the code 1 for the number of times of switching. Output (# 124), obtain representative value a (# 225), and proceed to step # 107.

  If NO in step # 108, that is, if the representative value difference is not "0" (NO in # 108), the representative value difference "0" is encoded with code 1 for the number of times so far and output (# 126). The variable n is initialized to “0” (# 127). The representative value difference is encoded with code 1 and output (# 128), and the process returns to step # 113.

  If the processing has not been completed up to the right end of the inputted 6 lines (No in # 113), step # 105 and the subsequent steps are repeated in order to sequentially process the low resolution region TL on the right for the same 6 lines. When the processing for 6 lines is completed (Yes in # 113), if there is an unprocessed line (No in # 114), the next 6 lines of the binary image data D1 are input (# 104). The process is repeated until the entire processing of the value image data D1 is completed (# 114).

  If NO in step # 122, that is, if there is no matching dither pattern DP, the attribute code “256” indicating that the low resolution area TL does not match any dither pattern DP is encoded with code 1 and output. (# 129), the process proceeds to step # 131 and subsequent steps which are processing of the medium resolution area TM.

  In the process of the medium resolution area TM, it is determined whether or not one medium resolution area TM obtained by dividing the low resolution area TL into four matches with any dither pattern DP (# 131). If they match (Yes in # 131), the number of dots in the medium resolution area TM is acquired and the difference is calculated (# 132), and the dot number difference is encoded with code 2 and output (# 133). This is repeated four times to return to the processing of the low resolution area TL in step # 113.

  If NO in step # 131, that is, if the medium resolution area TM does not match any dither pattern DP, the attribute code “25” indicating that they do not match is encoded by code 2 and output (# 135). ), The process proceeds to step # 141 and subsequent steps which are processing of the high-resolution area TS.

  In the processing of the high-resolution area TS, the dot pattern is digitized for one high-resolution area TS obtained by dividing the medium-resolution area TM into three (# 141), and the numerical value is encoded with code 3 and output (#). 142). This is repeated three times (# 143), and the process returns to the process of the medium resolution area TM in step # 134.

  22 and 23, first, the dither pattern DP and the decode table DC are read (# 201, 202). Then, the compressed data D2 transmitted from the computer main body 11 is received, and processing for restoration is performed in order from the head. Initially, it is restored by decode 1 (# 203).

  When the value dc1 obtained by the restoration is not the attribute codes “258”, “256”, and “257” (No in # 204 to 206), the value dc1 is the difference of the representative value a, and thus the cumulative value k1 so far The value dc1 is added to the value, and the obtained value is set as a new cumulative value k1 (# 206). If the cumulative value k1 exceeds “255” (Yes in # 208), since it exceeds the maximum value of the representative value a, “256” is subtracted from the cumulative value k1 (# 209). Then, using the accumulated value k1 as the representative value a, the dot pattern is restored using the dither pattern DP specified by the pattern number pn (# 210). The dot pattern is transferred to the line buffer (# 211), and 1 is added to the area number nb (# 212). The area number nb is a number indicating the position in the 6 lines of the low resolution area TL to be processed.

  Step # 203 and subsequent steps are repeated until the development for the same six lines is completed (No in # 213). When the development for 6 lines is completed (Yes in # 213), the area number nb is initialized to "0" (# 214), and the developed data for 6 lines (binary image data) is printed out (# 215). The process is repeated until all the compressed data D2 is processed (# 216).

  If yes in step # 204, that is, if the value dc1 obtained by restoration is “258”, “1” is added to the pattern number pn (# 221). If the pattern number pn is “3” (Yes in # 222), “3” is subtracted from the pattern number pn. That is, the pattern number pn is any one of “0”, “1”, and “2”, and this specifies one of the three types of dither patterns DP.

  If YES in step # 206, that is, if the value dc1 is "257", the dot pattern is restored using the dither pattern DP specified by the pattern number pn with the cumulative value k1 as the representative value a (# 231). . The dot pattern is transferred to the line buffer (# 232), and 1 is added to the area number nb (# 233). This is repeated 50 times (# 234). Accordingly, the binary image data of 50 low resolution areas TL are reproduced based on the representative value a when the difference “0” continues 50 times. When the right end of the line is reached during this process, the process is temporarily interrupted, the process from step # 214 is performed, and a new dot pattern is written from the beginning of the next line.

  If YES in step # 205, that is, if the value dc1 is "256", the process proceeds to step # 251 which is the process for the medium resolution area TM. In step # 251, the data is restored by the decode 2. If the value dc2 obtained by decoding 2 is not “25” (No in # 252), the value dc2 is the difference in the number of dots, so the value dc2 is added to the cumulative value k2 so far, and the obtained value Is set as a new accumulated value k2 (# 253). If the cumulative value k2 exceeds “24” (Yes in # 254), the maximum value of the number of dots is exceeded, so “25” is subtracted from the cumulative value k2 (# 255). Then, using the accumulated value k2 as the number of dots, the dot pattern is reproduced using the dither pattern DP specified by the pattern number pn (# 256). This is repeated four times (# 257). The dot pattern for four times is transferred to the line buffer (# 258), and 1 is added to the area number nb (# 259).

  If YES in step # 252, that is, if the value dc2 is "25", the process proceeds to step # 261, which is processing of the high resolution area TS. In step # 261, the data is restored by decoding 3 (# 261). From the restored value, an 8-dot pattern of the high-resolution area TS is reproduced (# 262). This is repeated three times (# 263).

  As described above, during the compression process, the binary image data D1 is separated into a dither pattern information component and an image information component. Then, only the image information component is extracted and subjected to encoding processing by the Huffman method to obtain compressed data D2. Since the dither pattern information component is not included in the compressed data D2, a high compression rate and high speed processing can be realized.

  Further, the processing for calculating the representative value a can be performed at high speed by reading data from the upper / lower limit table TJK, which greatly contributes to shortening the entire processing time. Further, in the processing of the high resolution region TS, since the image data of 8 pixels is read with one numerical value, the address instruction is fast. This also shortens the overall processing time.

  In the printer 13, the cost of the ASIC used for restoring the compressed data D2 is greatly influenced by the size of the work area of the on-chip memory. As a work area for performing the data expansion process, a storage area for the read dither pattern DP and decode table DC and a data storage area for the processing target area are required. For example, the dither pattern DP is about several hundred bytes to several kilobytes, the decoding table DC is about 2 kilobytes, and the total amount of data is about 3 to 4 kilobytes including other buffers. is there. Therefore, by providing the printer 13 with a small ASIC of about 3 to 4 Kbytes, the decompression process of the compressed data D2 can be performed at high speed. Further, the capacity can be further reduced by storing the decode table DC in the ROM. In this manner, the printer 13 can expand the compressed data D2 at high speed with small hardware. Thus, the entire process can be performed in a short time while using an inexpensive printer 13.

  In the embodiment described above, the low-resolution area dividing unit 101 shown in FIG. 3 divides the binary image data D1 into the low-resolution area TL. Various methods are used for the dividing method. Is possible. That is, since the partition may be virtual, it is not necessary to actually divide the binary image data D1 for each region. For example, the low resolution comparison unit 102 may specify an address for indicating a position to be compared. The configuration of the compressed data creation unit 100 shown in FIG. 3 is an example, and the functions described above can be realized by various configurations.

  In the embodiment described above, the computer main body 11 is provided with the pseudo gradation unit 170, and the binarization processing of the image data FD is performed here, but the binarization processing is performed inside the computer main body 11. Alternatively, the binary image data D1 may be input from the outside. In this case, information such as the dither pattern DP used for the binarization process may be acquired.

In the above-described embodiment, the binary image data D1 can express whether or not a dot is applied to each pixel constituting the image without a flag. Dots may be applied to pixels with high density, or dots may be applied to pixels with low density. The minimum value J and the maximum value K of the pixel density values for obtaining the representative value a may also be calculated assuming that dots are shot on a pixel with low density, or for pixels with high density. It may be obtained assuming that a dot is hit. As described above, various combinations can be made with respect to the gradation, the density value, the luminance value, and not hitting the dots.
[Second]
Embodiment for Compressing 4-level Image Data Next, a case of compressing 4-level image data will be described. In this case, the case is basically the same as the case of compressing binary image data. is there. Therefore, the description and drawings in the first can be applied to the second in substantially the same manner, and for many parts, the “two values” in the first description are changed to “four values” in the second. It can be applied by replacing. Only the main differences will be described here.

FIG. 25 is a diagram for explaining the partitioned low-resolution area TL, FIG. 26 is a diagram showing an example of the low-resolution area TL and the dither pattern DP, and FIG. 27 shows four-value image data (four-value image data) D5. FIG. 28 is a diagram for explaining binary image data (binary image data) D1.
[Explanation of quaternary image data]
In FIG. 25, the low resolution region TL is a rectangular region composed of 48 (6 × 8) pixels TP. In the example of FIG. 25, the entire area of the quaternary image data D5 is partitioned from the upper left to TLm, such as low resolution areas TL1, TL2, TL3,.

  In the low resolution region TL shown in FIG. 26A, the black pixel is a pixel on which a dot is formed. The size of the dot changes in three steps according to the pixel value. In other words, if the state where dots are not applied is “0”, the state where dots are applied to about one third of the area of one pixel is “1”, and dots are applied to about two thirds of the area. The state in which the dots are applied to the entire area of one pixel can be represented as “3”.

  As shown in FIG. 27, in correspondence with each state “0”, “1”, “2”, “3”, for example, by controlling the laser light emission time (pulse width control) of the printer, the pixel density is set in four levels. Can be changed. Thus, these states “0”, “1”, “2”, and “3” correspond to the gradation values.

  That is, in the state “0”, the laser does not emit light, and the pixel is “white”. In the state “1”, the laser light is emitted for about one third of the pixel width, and the region of about one third of the pixel is “black”. Similarly, in state “2” or “3”, the laser light is emitted for a period of about two-thirds or about three-thirds of the pixel width, respectively, and about two-thirds of the pixel area or the entire region is exposed. “Black”. That is, a density of 4 gradations is obtained corresponding to the state value. Four states representing four gradations can be represented by 2 bits. Therefore, four pixels of four gradations can be represented by 8 bits.

  The relationship between the laser emission time, the size of the dots hit by the laser, and the density at which it is viewed macroscopically is complex, and the above example is an example for explanation. Only.

  The threshold value of the dither pattern DP is a value in the range of 0 to 255, and three threshold values are set for each pixel. In each pixel, indexes (numbers) “1”, “2”, and “3” are given to the three threshold values in ascending order. The image data FD having a density smaller than the lowest threshold value with the index “1” is in the state “0”. The image data FD having a density between the threshold value of the index “1” and the threshold value of the index “2” is in the state “1”. Image data FD having a density between the threshold value of the index “2” and the threshold value of the index “3” is in the state “2”. The image data FD having a density larger than the highest threshold value whose index is “3” is in the state “3”. Usually, different pixels have different thresholds for the same index.

  Here, binary image data is also described for comparison.

  As shown in FIG. 28, in the binary image data, the pixel density can be changed in two stages of black and white by controlling on / off the laser of the printer, for example, corresponding to each state “0” “1”. .

That is, in the state “0”, the laser does not emit light, and the pixel is “white”. In the state “1”, laser light is emitted, and the pixel is “black”. That is, a density of two gradations is obtained corresponding to the state value.
[How to find representative value a]
Now, when the density value of each pixel of the image data FD is equal to or higher than any threshold value of the corresponding pixel of the dither pattern DP, a dot is shot corresponding to the threshold value of that pixel. And That is, in this case, not hitting a dot means not corresponding to the pixel but corresponding to each of the three threshold values corresponding to the pixel. Here, the larger the density value, the higher the density.

  In this case, when a dot is shot with a threshold value of a certain pixel, it can be said that the density value of that pixel is equal to or higher than the corresponding threshold value. In other words, the lower limit value of the density of the pixel is the same value as the corresponding threshold value. On the contrary, when a dot is not hit, it means that the density value of the pixel is less than the corresponding threshold value. In other words, the upper limit value of the density of the pixel is a value smaller by “1” than the corresponding threshold value.

  In this way, the upper limit value and the lower limit value are totaled for each threshold value assigned to each pixel of the dither pattern DP, and the minimum value J of the upper limit value and the maximum value K of the lower limit value are obtained. Similarly to the above, “a” satisfying the expression (2) is set as a representative value.

When there are a plurality of “a” s that satisfy the expression (2), that is, when there is a representative value a within a certain range (range), the representative value of the adjacent region among such representative values a The value that minimizes the difference is used as the representative value a.
[Low resolution area, medium resolution area, high resolution area]
FIG. 29 is a diagram showing a low resolution area TL, a medium resolution area TM, and a high resolution area TS.

As shown in FIG. 29, the low resolution area TL is an area of 6 × 8 pixels. The low resolution area TL is divided into four medium resolution areas TM of 3 × 4 pixels by the medium resolution area dividing section 104. The medium resolution area TM is further divided into three high resolution areas TS of 4 pixels as necessary.
[Low-resolution area processing]
As in the first case, the low resolution region TL partitioned as shown in FIG. 25 is compared with the dot pattern and the dither pattern DP to determine whether or not they match each other. If they match, the representative value a is obtained as described above. The rest is the same as in the first case.
[Medium resolution area processing]
FIG. 30 is a diagram illustrating a distribution of appearance frequencies of the difference in the number of dots in an image.

  In the medium resolution representative value calculation unit 106, when the medium resolution region TM matches the dither pattern DP, the representative value a satisfying the expression (2) is obtained by the same processing as in the case of the low resolution region.

  Then, based on the obtained representative value a, the difference between the representative values between the adjacent medium resolution areas TM is calculated in the same manner as in the low resolution area TL. The difference here is in the range of 0 to 255 using the cyclic integer described above.

  As shown in FIG. 30, the appearance frequency is high in the range where the difference is about “0” to “30” and “200” to “255”. After the difference of 0 to 255, the appearance frequency for the value “256” is shown. The meaning of this is the same as the attribute code in the case of the low resolution region TL, and “256” is an attribute code indicating that a certain medium resolution region TM does not match any dither pattern DP.

  That is, if no dither pattern DP matches in the medium resolution area TM, “256” is output as the code 2 to further divide the area into high resolution areas TS.

In the case of the binary value shown in the first example, the medium resolution area TM has 24 pixels, and the maximum number of dots is 24. Therefore, the number of dots in the area is counted as a representative value. However, in the case of the four values shown in the second example, priority is given to the sharing and the processing speed, and the density value is used as the representative value as described above.
[Explanation by flowchart]
Next, the first process will be described with reference to a flowchart.

  FIG. 31 is a flowchart showing a rough flow of compression processing in the computer main body 11. FIG. 31 corresponds to the first FIG. 18, and only step # 22B is different.

  That is, in FIG. 31, when one medium resolution area TM matches the dither pattern DP (Yes in # 21), the representative value a is obtained in the same manner as in Step # 15 (# 22B). Then, the difference is taken (# 22) and encoded (# 23).

  32 and 33 are flowcharts of compression processing in the compressed data creation unit 100, and FIGS. 34 and 35 are flowcharts of decompression processing in the data restoration unit 300. 32 to 35 correspond to the first FIGS.

  In FIG. 33, if it matches any of the dither patterns DP (Yes in # 131), the representative value a is acquired in the medium resolution area TM and the difference is calculated (# 132B), and the representative value difference is coded. 2 is encoded and output (# 133B). This is repeated four times, and the process returns to the processing of the low resolution region TL in step # 113 in FIG.

  If NO in step # 131, that is, if the medium resolution area TM does not match any dither pattern DP, the attribute code “256” indicating that it does not match is encoded by code 2 and output (# 135B ), The process proceeds to step # 141 and subsequent steps which are processing of the high-resolution area TS.

  In FIG. 35, if the value dc2 obtained by decoding 2 is not “256” in step # 252B, the value dc2 is the difference between the representative values, so the value dc2 is added to the cumulative value k2 obtained so far. The obtained value is set as a new cumulative value k2 (# 253). When the cumulative value k2 exceeds “255” (Yes in # 254B), the maximum value of the representative value is exceeded, so “256” is subtracted from the cumulative value k2 (# 255B). Then, using the accumulated value k2 as a representative value, the dot pattern is reproduced using the dither pattern DP specified by the pattern number pn (# 256).

  If YES in step # 252B, that is, if the value dc2 is "256", the process proceeds to step # 261, which is processing of the high resolution area TS.

  In the decompression process, the dither process is performed using the dither pattern DP attached to the header portion of the compressed data D2. In the case of binary image data, the representative value a is compared with a threshold value. When the representative value a is greater than or equal to the threshold value, “1” is indicated, and when the representative value a is less than the threshold value, “0” is indicated. Are output respectively.

  On the other hand, in the case of quaternary image data, the threshold value is compared with the threshold value by comparing the representative value a with the threshold value because three threshold values are arranged for each pixel in ascending order. A value obtained by adding “1” to the index value (0 to 3) of the largest threshold value is output. If there is no threshold value less than the representative value a, “0” is output.

  In the case of 10-value image data, 15 threshold values are arranged for each pixel in ascending order, so that the representative threshold value a is compared with the threshold value, and the largest threshold value that is equal to or lower than the representative value a. A value obtained by adding “1” to the value (0 to 14) of the value index is output. If there is no threshold value less than the representative value a, “0” is output.

  However, when the index is set to “1” to “4”, for example, in the case of four values, the index value may be output without adding “1”.

  In the above embodiment, binarization and quaternarization have been performed as pseudo-gradation, but various values such as ternarization, 8-level conversion, and 16-level conversion can also be performed. .

  In addition, the configuration, function, number, number of bits, processing contents or order of the entire computer main body 11, printer 13, and printing system 1 or each part can be appropriately changed in accordance with the spirit of the present invention.

  The present invention is used in a printing system including a raster printer, a GDI printer, and the like, and can be used as a method for compressing pseudo gradation image data.

1 is a diagram illustrating an overall configuration of a print system according to the present invention. It is a block diagram which shows the functional structure of a computer main body. It is a block diagram which shows the compressed data production part of a computer main body functionally. FIG. 2 is a block diagram illustrating a functional configuration of a printer. It is a figure for demonstrating the divided low resolution area | region. It is a figure which shows the example of a low-resolution area | region and a dither pattern. It is a figure which shows the example of the low resolution area | region and dither pattern from which size differs. It is a figure which shows the example of an upper / lower limit table. It is a figure which shows the example of transition of the representative value about a some low resolution area | region. It is a figure which shows the example of a cyclic integer. It is a figure showing distribution of the appearance frequency of the difference of the representative value in an image. It is a figure which shows a low-resolution area | region and a medium-resolution area | region. It is a figure showing distribution of the appearance frequency of the difference of the number of dots in an image. It is a figure for demonstrating the digitization of a dot pattern. It is a figure showing distribution of the appearance frequency of each dot pattern. It is a figure which shows the example of a Huffman code table. It is a figure which shows the example of a decoding table. It is a flowchart which shows the rough flow of a compression process. It is a flowchart which shows the rough flow of a decompression | restoration process. It is a flowchart of the compression process in a compression data creation part. It is a flowchart of the compression process in a compression data creation part. It is a flowchart of the restoration process in a data restoration part. It is a flowchart of the restoration process in a data restoration part. It is a figure for demonstrating the divided low resolution area | region. It is a figure for demonstrating the divided low resolution area | region. It is a figure which shows the example of a low-resolution area | region and a dither pattern. It is a figure for demonstrating 4 value image data. It is a figure for demonstrating binary image data. It is a figure which shows a low-resolution area | region and a medium-resolution area | region. It is a figure showing distribution of the appearance frequency of the difference of the number of dots in an image. It is a flowchart which shows the rough flow of a compression process. It is a flowchart of the compression process in a compression data creation part. It is a flowchart of the compression process in a compression data creation part. It is a flowchart of the restoration process in a data restoration part. It is a flowchart of the restoration process in a data restoration part.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Print system 11 Computer main body 13 Printer 100 Compressed data creation part 101 Low resolution area | region division part 102 Low resolution comparison part 103 Low resolution representative value calculation part 104 Medium resolution area | region division part 105 Medium resolution comparison part 106 Medium resolution representative value calculation part 107 Dot pattern extraction unit 108 Coding unit 109 Data transmission unit 300 Data restoration unit D1 Binary image data (pseudo-gradation image data)
D2 Compressed data D5 Four-value image data (Pseudo gradation image data)
DP dither pattern DP5 dither pattern TL Low resolution area (predetermined area)
TM Medium resolution area (predetermined area)
TS High resolution area (predetermined area)

Claims (25)

A method of compressing pseudo-gradated image data using a dither pattern,
The image data is divided into predetermined areas, and it is determined whether or not the dot arrangement pattern of the image data in each area matches the dither pattern used for pseudo-gradation. To obtain a representative value for the density of image data in and create compressed data using the obtained representative value,
A method for compressing image data. When the density value of each pixel of the image data is small by comparing the density value of each pixel of the image data in the region with the density value of each pixel of the corresponding portion of the dither pattern as the representative value When a dot is hit in a pattern area prepared in advance, the minimum value J of the pixel density value of the dither pattern corresponding to the dot hit in the area and the dither pattern corresponding to the dot not hit J ≧ a ≧ K between the maximum density value K of the pixels
Using a value a that is required to satisfy the following condition:
The method of compressing image data according to claim 1. When the density value of each pixel of the image data is large by comparing the density value of each pixel of the image data in the region with the density value of each pixel of the corresponding portion of the dither pattern as the representative value When dots are hit in a pattern area prepared in advance, the maximum density value K of the pixels of the dither pattern corresponding to the dots hit in the area and the dither pattern corresponding to the dots not hit J ≧ a ≧ K with the minimum value J of the density value of the pixel
Using a value a that is required to satisfy the following condition:
The method of compressing image data according to claim 1. As the representative value, a value that minimizes the difference between the representative values of adjacent regions is used.
The image data compression method according to claim 1. When the density value of each pixel of the image data is small by comparing the density value of each pixel of the image data in the region with the density value of each pixel of the corresponding portion of the dither pattern as the representative value When a dot is hit in a pattern area prepared in advance, the number of dots hit or not hit in the area is used.
The method of compressing image data according to claim 1. When creating the compressed data, in each area, obtain a difference between the representative values of the other areas, and encode the obtained difference.
6. A method for compressing image data according to claim 1. When there are a plurality of dither patterns used for pseudo-gradation, it is determined whether the plurality of dither patterns are switched to match the dot arrangement pattern of the image data in each region.
The method of compressing image data according to claim 1. When the dot pattern of the image data in the area does not match the dither pattern used for pseudo-gradation, the area is further divided into a plurality of small areas, and the dot of the image data in each small area Determining whether an array pattern matches the dither pattern;
The method of compressing image data according to claim 1. As the representative value in the area, the density value of each pixel of the image data in the area is compared with the density value of each pixel of the corresponding portion of the dither pattern, and the density value of each pixel of the image data is small. In this case, when a dot is applied to a pattern area prepared in advance, the dither pattern corresponding to the minimum value J of the pixel of the dither pattern corresponding to the dot applied in the area and the dither corresponding to the dot not applied J ≧ a ≧ K between the maximum density value K of the pattern pixels
Using a value a that satisfies the condition
As a representative value in the small area, the number of dots hit or not hit in the area is used,
The method of compressing image data according to claim 8. As a representative value in the area, the density value of each pixel of the image data in the area is compared with the density value of each pixel of the corresponding portion of the dither pattern, and the density value of each pixel of the image data is large. In this case, when a dot is applied to a pattern area prepared in advance, the dither pattern corresponding to the maximum value K of the pixel of the dither pattern corresponding to the dot applied in the area and the dither corresponding to the dot not applied J ≧ a ≧ K between the minimum value J of the density values of the pixels of the pattern
Using a value a that satisfies the condition
As a representative value in the small area, the number of dots hit or not hit in the area is used,
The method of compressing image data according to claim 8. As the representative value in the area and the small area, the density value of each pixel of the image data in the area or the small area is compared with the density value of each pixel in the corresponding portion of the dither pattern, respectively. When the density value of each pixel of the data is small, when a dot is shot in a pattern area prepared in advance, the density value of the pixel of the dither pattern corresponding to the dot hit in the area or the small area Between the minimum value J and the maximum density value K of the pixels of the dither pattern corresponding to the dot that has not been hit, J ≧ a ≧ K
A value a satisfying the condition
The method of compressing image data according to claim 8. As the representative value in the area and the small area, the density value of each pixel of the image data in the area or the small area is compared with the density value of each pixel in the corresponding portion of the dither pattern, respectively. When the density value of each pixel of the data is large, when the dot is hit in the pattern area prepared in advance, the density value of the pixel of the dither pattern corresponding to the dot hit in the area or the small area J ≧ a ≧ K between the maximum value K and the minimum value J of the density values of the pixels of the dither pattern corresponding to the dot that has not been hit
A value a satisfying the condition
The method of compressing image data according to claim 8. When creating the compressed data, in each area, obtain a difference between the representative values of the other areas, and encode the obtained difference.
The method for compressing image data according to claim 8. When the dot arrangement pattern of the image data in the area or in the small area does not match the dither pattern used for pseudo-gradation, it was hit or not hit in the area or in the small area Creating the compressed data by encoding an array of dots;
The method for compressing image data according to claim 8. A method of compressing pseudo-gradated image data using a dither pattern,
A first step of dividing the image data into predetermined areas;
A second step of determining whether or not the dot arrangement pattern of the image data in each region matches the dither pattern used for pseudo-gradation;
If the determination result in the second step matches, the representative value related to the density of the image data in the area is set as the density value of each pixel of the image data in the area and each pixel of the corresponding portion of the dither pattern. The dither pattern corresponding to the dot hit in the pattern area when the dot value is hit in the pattern area prepared in advance when the density value of each pixel of the image data is small J ≧ a ≧ K between the minimum value J of the pixel density value J and the maximum density value K of the pixel of the dither pattern corresponding to the dot that has not been hit
A third step for obtaining a value a that satisfies the following condition:
When the determination result in the second step does not match, the area is further divided into a plurality of small areas, and whether or not the dot arrangement pattern of the image data in each small area matches the dither pattern. A fourth step of determining;
A fifth step of obtaining the number of dots hit or not hit in the area as a representative value in the small area when the determination results in the fourth step match;
A sixth step of encoding an array of dots in the small region when the result of determination in the fourth step does not match;
A seventh step of performing encoding based on the obtained representative value when the determination results in the second step or the fourth step match;
A method for compressing image data, comprising: A method of compressing pseudo-gradated image data using a dither pattern,
A first step of dividing the image data into predetermined areas;
A second step of determining whether or not the dot arrangement pattern of the image data in each region matches the dither pattern used for pseudo-gradation;
If the determination result in the second step matches, the representative value related to the density of the image data in the area is set as the density value of each pixel of the image data in the area and each pixel of the corresponding portion of the dither pattern. The dither pattern corresponding to the dot hit in the pattern area when the dot value is hit in a pattern area prepared in advance when the density value of each pixel of the image data is large J ≧ a ≧ K between the maximum value K of the density values of the pixels of the pixel and the minimum value J of the density values of the pixels of the dither pattern corresponding to the dots that have not been hit.
A third step for obtaining a value a that satisfies the following condition:
When the determination result in the second step does not match, the area is further divided into a plurality of small areas, and whether or not the dot arrangement pattern of the image data in each small area matches the dither pattern. A fourth step of determining;
A fifth step of obtaining the number of dots hit or not hit in the area as a representative value in the small area when the determination results in the fourth step match;
A sixth step of encoding an array of dots in the small region when the result of determination in the fourth step does not match;
A seventh step of performing encoding based on the obtained representative value when the determination results in the second step or the fourth step match;
A method for compressing image data, comprising: A method of compressing pseudo-gradated image data using a dither pattern,
A first step of dividing the image data into predetermined areas;
A second step of determining whether or not the dot arrangement pattern of the image data in each region matches the dither pattern used for pseudo-gradation;
If the determination result in the second step matches, the representative value related to the density of the image data in the area is set as the density value of each pixel of the image data in the area and each pixel of the corresponding portion of the dither pattern. The dither pattern corresponding to the dot hit in the pattern area when the dot value is hit in a pattern area prepared in advance when the density value of each pixel of the image data is large J ≧ a ≧ K between the maximum value K of the density values of the pixels of the pixel and the minimum value J of the density values of the pixels of the dither pattern corresponding to the dots that have not been hit.
A third step for obtaining a value a that satisfies the following condition:
When the determination result in the second step does not match, the area is further divided into a plurality of small areas, and whether or not the dot arrangement pattern of the image data in each small area matches the dither pattern. A fourth step of determining;
A fifth step of obtaining a representative value by the same process as the third step as a representative value in the small region when the determination results in the fourth step match;
A sixth step of encoding an array of dots in the small region when the result of determination in the fourth step does not match;
A seventh step of performing encoding based on the obtained representative value when the determination results in the second step or the fourth step match;
A method for compressing image data, comprising: As the representative value, a value that minimizes the difference between the representative values of adjacent regions is used.
18. The method for compressing image data according to claim 15. In the seventh step, a difference between representative values in each area and other areas is obtained, and the obtained difference is encoded.
The method for compressing image data according to claim 15. The pseudo gradation image data is binary image data.
20. The method for compressing image data according to claim 1. The pseudo gradation image data is multi-value image data.
20. The method for compressing image data according to claim 1. A method for restoring image data compressed by the method according to any one of claims 1 to 21, comprising:
Obtain a representative value of each area from the compressed image data, and compare the acquired representative value with the dither pattern to reproduce the dot pattern,
A method for restoring image data. An apparatus for compressing pseudo-gradated image data using a dither pattern,
Means for dividing the image data into predetermined areas;
Means for determining whether or not the dot pattern of image data in each region matches the dither pattern used for pseudo-gradation;
Means for obtaining a representative value for the density of the image data in the area when they match,
Means for creating compressed data using the obtained representative value;
A compression apparatus for image data, comprising: The means for obtaining the representative value uses, as the representative value, a value that minimizes the difference between the representative values from adjacent regions.
24. The apparatus for compressing image data according to claim 23. The means for creating the compressed data obtains a difference between representative values of each region and the other region, and encodes the obtained difference.
The image data compression apparatus according to claim 23 or 24.