JPH0937081A - Device and method for processing picture - Google Patents

Abstract

PROBLEM TO BE SOLVED: To efficiently convert picture information with n-gradation per one picture element into picture information where the number of the picture element is increased to be A×B times as large as m-gradation per one picture element. SOLUTION: A picture processor is the one for converting picture information with n-gradation per one picture element into picture information where the number of the picture element is increased to be A×B times as large as m- fradation per one picture element and also is provided with a scalar quantization part 102 permitting picture information with n-gradation (n and m are natural numbers satisfying n>m >=2) to be picture information with p-gradation (n>p>m) by scalar quantization, an addition encoding part 106 and a vector encoding part 107 for compressing picture information with p-gradation from the scalar quantization part 102 into a code being equal to below the C-power of p by a C picture element unit (C>=2) so as to execute encoding, a decoding part 111 for decoding the code from the encoding parts by the C picture element unit and a density pattern converting part 112 executing a density pattern method for outputting the m-gradation patterns of the respective picture elements.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image processing apparatus and method, and is for transmitting image information to an image output apparatus such as a printer which outputs at a gradation number smaller than the gradation number of an input signal. The present invention relates to an image processing device and method.

[0002]

2. Description of the Related Art Conventionally, various methods have been proposed as pseudo gradation conversion for converting input multi gradation information into binary information.

Among them, a typical one is a dither method in which a dither signal is superimposed on an input signal for quantization, and an error diffusion method in which a quantization error is fed back to quantize pixels after the pixel of interest (R. Floyd & L. Stein
Berg, “An Adaptive Alogori
thm for Special Gray Scal
e ", SID75 Digest, pp36-37) and the like.

Now, it is assumed that these pseudo gradation processes are used in an image output device such as a printer. Due to the recent rapid growth of CPU power, more and more printer systems operate pseudo gradation processing by software of a printer driver on a host computer rather than by hardware in the printer body. FIG. 2 is the most common system form. Regions surrounded by two broken lines represent blocks of the printer driver and the printer main body, respectively. In the figure, reference numeral 201 denotes an input terminal to which multi-tone image information representing an image created by application software or the like on a host computer is input. Image creation such as this application software may be included in the printer driver. Reference numeral 202 denotes a binarization processing unit, which converts a multi-gradation image of each pixel into 2 by pseudo-gradation processing.
Value. The binarized image information is transmitted to the printer via I / O (not shown).

On the printer side, the transmitted information is stored in the memory 203 for a plurality of lines or for one page, and in a serial printer such as an ink jet printer or a thermal transfer printer, the data arrangement is adapted to the head configuration and the printer engine is used. It is sent to 204 and output.

The same applies to the case of a color printer, which is YMCK in which brightness information such as RGB is adapted to an engine by application software, a printer driver, or the like.
The color conversion means for converting into the density information is added before the binarization processing 202.

In recent years, the resolution of printer engines has increased, and the amount of information handled has also increased. Therefore, instead of the configuration of FIG. 2, in order to reduce the load of processing such as image creation of application software or color conversion, the resolution of an image handled in multiple gradations is set lower than the output resolution of the printer engine, A configuration in which the number of pixels is increased by the interpolation processing unit 301 and then binarization processing is performed is also conceivable (configuration shown in FIG. 3).

However, in the configuration shown in FIGS. 2 and 3, the higher the resolution engine, the larger the amount of transfer information from the printer driver to the printer, and the increase in transfer time.
In addition, the increase in the capacity of the memory causes an adverse effect such as an increase in the cost of the printer.

Therefore, in addition to the configurations shown in FIGS. 2 and 3, it is conceivable that information amount compression processing is added. The configuration of FIG.
A compression unit 401 is added to perform lossless compression processing based on run length or the like on the image information after the binarization processing.
The compressed image information is sent to the printer side and stored in the memory 2
After being stored in 03, it is decompressed by the decompression unit 402 and sent to the printer engine 204 for output. Further, for the purpose of shortening only the transfer time, it is possible to adopt a configuration in which the data is expanded and then stored in the memory.

The configuration shown in FIG. 5 is also conceivable as the configuration. With this configuration, the compression unit 501 in the printer driver executes compression processing such as orthogonal transformation on multi-gradation image information, and after transmission to the printer main body, the memory 203
In the interpolation processing unit 301 after passing through the decompression unit 502.
And the binarization processing unit 202 performs binarization processing and sends the binarized processing to the printer engine 204 for output.

The compression process in this case may also be executed within the application software. For example, JPEG (Joint Photograph), which is an international standard for still image coding, may be used.
It may be configured such that the JPEG file is decompressed (decompressed) in the printer body by compressing in the hic Experts Group) format.

[0012]

However, the above configuration example has the following problems. First, with the configuration of FIG. 4, there is a problem that the compression efficiency is poor in the binary image after the pseudo halftone processing. For example, since a character, line image, or the like has a large amount of white space, etc., compression efficiency may increase when a compression method such as run length is used. However, for a natural image, proximity after binarization may be increased. Less correlation with pixels,
There is also a risk that the amount of information will increase compared to the case where compression is not executed. Although some error diffusion methods and compression methods for binary image information after dithering have been proposed, none have significantly improved compression efficiency.

Another problem other than the compression efficiency is variable-length coding. In the conventional technology, the property of a binary image is significantly different from that of a multi-valued image, and discussion has been made on the assumption that the image is lossless compression because of the redundancy of information. That is, it is difficult to perform fixed-length encoding on a binary image. However, the variable length of the information transmitted from the printer driver causes various problems such as a memory configuration problem inside the printer and a transfer time bias problem.

In the configuration of FIG. 5, since the multi-valued image information is compressed and transmitted, there is a degree of freedom in the coding method regardless of whether the variable length or the fixed length. However, in the configuration of FIG. 5, since the multi-valued image information having a large amount of original information is compressed, the compression rate is not better than that of the binary image unless the compression rate is significantly improved. In addition, the interpolation processing unit, the binarization processing unit, and the like must be mounted in the printer body, and it is expected that the cost of the printer will increase significantly. Further, when a compression method such as orthogonal exchange is used, the hardware of the decoding unit also greatly affects the cost increase.

[0015]

SUMMARY OF THE INVENTION The present invention has been made to solve the above problems, in which image information of n gradations per pixel is multiplied by A × B times m gradations per pixel. An image processing device for converting image information into an increased number (n, m
Is a natural number satisfying n> m ≧ 2, and a quantizing means for scalar-quantizing the image information of n gradations into image information of p gradations (where n>p> m) for each pixel. , The image information of p gradation from the quantizing means in units of C pixels (C ≧ 2),
coding means for compressing and coding to a code less than the C-th power of p, and transmitting means for transmitting the code from the coding means,
A decoding means for decoding the code transmitted by the transmitting means in C pixel units, and a density pattern method for outputting a pattern of m gradations for each pixel based on the decoded signal decoded by the decoding means are executed. And an image processing device having a density patterning means for controlling the density pattern, and inputting image information of n gradations per pixel, the number of pixels is (A × B) times m gradations per pixel. Is an image processing method for converting image information into increased image information (n and m are natural numbers satisfying n> m ≧ 2), and n gradation information is converted into p gradation (where n> m) for each pixel. (p> m), a quantization step of performing scalar quantization on the image information, and p gradation image information in units of C pixels (C ≧
In 2), an encoding step of compressing and encoding to a code less than the C-th power of p, a decoding step of decoding the encoded image information in C pixel units, and each pixel based on the decoded signal m
An image processing method having an output step of executing a density pattern method of outputting a gradation pattern.

[0016]

BEST MODE FOR CARRYING OUT THE INVENTION Embodiments of the present invention will be described below with reference to the drawings.

(First Embodiment) FIG. 1 is a block diagram showing a main part of a first embodiment of the present invention. As described in the above configuration example, the areas surrounded by the two broken lines are classified into a printer driver block in the host computer and a block in the printer body. 10 in the figure
Reference numeral 1 denotes an input terminal for inputting multi-tone image information representing an image created by application software on the host computer. This is not only a natural image,
It is also possible to input image information in which character and line image information described in PDL (Page Description Language) is expanded and rasterized.

The input multi-gradation image information reduces the number of gradations of each pixel in the scalar quantizer 102.
Here, the scalar quantization of this embodiment will be described.

FIG. 6 is an explanatory diagram of scalar quantization. In the figure, 601, 602, 603, 604, 605, 606
Represents each pixel and is set as the input multi-tone information. In the scalar quantization of this embodiment, the threshold for quantization is regularly dithered according to the pixel position. According to the example of FIG. 6, pixels with diagonal lines (601, 603, 605)
Is set to perform scalar quantization by the quantization threshold shown on the left side, and the other pixels (602, 604, 606) are set to perform scalar quantization by the quantization threshold shown on the right side. In the figure, a, b, c, d, and e represent quantized representative values, and the thresholds for determining the quantized representative values are j,
It is written as k, l, m. However, the quantization condition shown on the right side and the quantization condition shown on the left side differ in the relative positional relationship of the threshold values between the quantized representative values.

In this example, an odd number in only the one-dimensional direction,
Although the dither expression using an even number is shown, naturally it is better to extend it to two dimensions.

Further, it is not necessary to pay attention to regularity in units of two pixels. Scalar quantization using such dither prevents the quantized value from becoming constant even in flat areas. Further, this quantization is not limited to linear one, and may be non-linear one.

Now, it is assumed that the input image information has n gradations per pixel and the gradation is reduced to p gradations (n> p). Further, each quantized quantized value is assigned a number from 0 to p in ascending order. This is called a quantization coefficient. For example, in the example in which the quantized representative value of FIG. 6 has five gradations of a, b, c, d, and e, a, b, and
The quantized coefficients of c, d, and e are 0, 1, 2, 3, 4,
It becomes 5.

Now, in FIG. 1, the scalar-quantized quantized coefficients of each pixel are packed by the packing unit 103 for each plurality of pixels. The packing unit may be the same as or different from the dither cycle described above, and is not limited to the one-dimensional direction or the two-dimensional direction.
Rather, this unit is roughly determined by how much the compression ratio is set when the present invention is applied to the image processing system. This packing is the same as blocking when the processing unit of a plurality of pixels is a rectangle.

Now, it is assumed that each C pixel is packed. The amount of information is the number of states of p to the Cth power, because the pixels of p gradation are arranged for C pixels. The encoding in this embodiment is to reduce the number of states.

Now, for ease of explanation, p = 17,
The case of C = 2 will be described. There are 289 states in this state. That is, if 289 different codes are set, transmission is possible.

In FIG. 1, reference numeral 104 denotes an evaluation unit, which evaluates vector information of quantized coefficients of packed pixels. In this embodiment, the difference value of the quantized coefficient in the packing is used for evaluation. In the above example of p = 17 and C = 2,
The difference value between the quantized coefficients of two pixels is calculated. When the number of pixels is 3 pixels or more, the maximum value and the minimum value in the packing may be obtained and evaluated by the value of the maximum value-the minimum value. When it is determined that the difference value of the quantization coefficient is small, the switch 105 selects the addition encoding unit 106, and when it is determined that the difference value is large, the vector encoding unit 107 is selected.
The determination of this magnitude may be performed by setting a threshold value in advance and comparing it with the difference value.

The addition coding unit 106 codes the value obtained by adding the respective quantized coefficients. Also, the vector encoding unit 10
In No. 7, since the value of each quantized coefficient may be slightly distorted, it is set so that the resolution is mainly preserved. That is, the coding method is switched from the edge portion of the image to the flat portion. At this time, it is natural to distinguish the code assigned to the addition coding from the code assigned to the vector coding.

The code of each packing unit coded by either of the coding units is transmitted to the printer side via the I / O and stored in the memory 110. In this embodiment, since the number of codes to be assigned is fixed, the code to be transmitted has a fixed length. Therefore, the memory configuration is easy,
The transfer times are even. The code information stored in the memory 110 is decoded by the decoding unit 111.

In the case of the addition code, since the code itself is the addition value of the quantized coefficient in the packed unit, the density of the image is expressed in C pixel units. This executes the density pattern method, which is a known pseudo gradation method, in the density pattern conversion unit 112. In the case of the vector code, since the quantized coefficient for each pixel can be decoded, the density pattern method is executed for each pixel.

The density pattern method is a method of arranging a predetermined number of dots in a preset arrangement according to an input value. Similar to the dither method, this arrangement method includes a concentrated type in which dots are arranged from the center value, and a distributed type in which dots are arranged by being dispersed so that the spatial frequency becomes higher.

The difference from the dither method is that the threshold signal for the input signal is not 1: 1 and a plurality of binarized pixels are output for one input. Therefore, resolution conversion and binarization can be realized at once. Now, it is assumed that the enlargement ratio is A times horizontal and B times vertical. The binary information created by the density pattern method is transmitted to the printer engine 113,
Is output.

Encoding and binarization of this embodiment will be described with reference to FIG.

In FIG. 7, enlargement factors A and B are A = B =
4, the packing pixel number C is C = 4. If the final output information is binary, the number of gradations of scalar quantization p
Is preferably set to A × B + 1, so p = 17.

In the figure, reference numeral 701 indicates a part of multi-tone image information. Reference numeral 702 denotes block information, which indicates a quantization coefficient obtained by scalar-quantizing the image information 701 and packing it with 4 pixels. The quantization coefficient of each pixel is 0
It can be up to 16.

Now, the evaluation unit 104 determines that the packed block is a flat portion based on its quantized coefficient. Therefore, the addition encoding unit 106 or the switch 1
05 is selected. 703 is the result of adding the quantized coefficients of these four pixels in the addition encoding unit 106 and assigning a code (11 + 10 + 10 + 10 = 41).

Since the quantized coefficients are 0 to 16, the addition code results are 0 to 64. Therefore, assuming that the code amount to be transmitted is 1 byte for 4 input pixels,
As shown in FIG. 11, 0 to 64 can be assigned to codes by addition coding, and 65 to 255 can be assigned to codes by vector coding.

Now, in the reference numeral 703 of FIG. 7, "41"
The packing information assigned with the sign is transmitted from the printer driver to the printer side and binarized by the density pattern conversion unit 112. As described above, the binarization of the addition coding packing is performed by the density pattern method in the packed C pixel unit (in this case, 4 pixel unit). Since the density pattern method requires an arrangement matrix corresponding to the enlargement ratio, the arrangement matrix of the density pattern of A × B × C pixels as shown in 704 is used. Although the arrangement matrix 704 shows a centralized type, the arrangement matrix 704 is not limited to this.

Information of this arrangement matrix 704 and "4
From the code “1”, the density pattern conversion unit 112
Binary information of the dot pattern shown in 05 is created. If the enlargement ratio is small, the density pattern is
A pattern can be created using a UT (look-up table), but when the enlargement ratio is large, if each pixel of the arrangement matrix is used as a threshold value and compared with the signal of “41”, the dot is turned on as in the dither method. Whether it is OFF or OFF can be determined, and binary information can be easily created.

Next, an example of the vector code will be shown. Figure 7
Medium 711 indicates a part of the multi-tone information input as in the image information 701. Reference numeral 712 denotes block information packed in 2 pixels × 2 pixels after each scalar quantization. When the evaluation unit 104 determines that the evaluation result of the block information is the edge portion, the vector coding unit 107 is selected and vector coding is performed. Now, FIG.
As shown in, the outputable code is 1 by 4 pixels.
Assuming te, and assigning a code for 65 gradations without degeneracy in the addition code, the remaining 191 code amounts are used for the vector code. Ie typical 191
The streets are set in the table, and the nearest vector information is approximated and output.

It is assumed that the block information 712 is approximated to the vector 713 by the vector coding unit 107. After the code representing the vector 713 is transmitted from the printer driver to the printer side, the density pattern conversion unit 112 on the printer side performs binarization based on this vector information. As described above, the binarization in the case of the vector code is to perform the density pattern for each pixel. In the example of the enlargement ratio A = B = 4, the density pattern of 4 × 4 pixels as shown by 714 is used. Prepare a placement matrix. Each pixel of the arrangement matrix 714 is set to "1".
Binary information as shown by 715 is created by comparing with 4 ”,“ 14 ”,“ 14 ”, and“ 2 ”.

The example of the addition code and the example of the vector code have been described above. By separating the coding method from the packing information of a plurality of pixels, the gradation is preserved in the flat part and the resolution is improved in the edge part. Can be saved. Also, by adapting and optimizing the arrangement matrix of the density pattern of the addition code with the scalar quantization at the time of encoding, there is no distortion at the time of addition code, and the distortion at the time of scalar quantization is exactly the same as the distortion in the density pattern method. A compression method that enables

FIG. 8 shows an example in which the density pattern conversion of the vector code is different from that in FIG. In the method of converting the density pattern shown in FIG. 7, if the arrangement pattern of the addition code and the arrangement pattern of the vector code are different, the dot gain due to the overlapping of the adjacent dots in the printer is different, and even if the density is the same on the signal, the dot gain is different. The density on the paper may change depending on the arrangement procedure of. That is, there is a risk that the switching of the encoding method will be detected on the output paper. In addition, the matrix size of the arrangement pattern used in the addition code and the matrix size of the pattern used in the vector code may be different, which may be a problem.

Here, an example in which the matrix size and the dot arrangement procedure of both are the same will be described.

In FIG. 8, reference numeral 801 is a vector code packing example, which is the same as the vector 713 in FIG. The method of converting the density pattern of the addition code is the same as that described with reference to FIG.

Reference numeral 802 denotes an arrangement matrix of density patterns for vector codes. Unlike the addition sign,
Since the value of the quantization coefficient to be compared with the threshold of the arrangement matrix is not the addition of 4 pixels, the arrangement matrix 802 arranges the thresholds of the same level for every 4 pixels. 803
Indicates binary information created by the density pattern. That is, in the present embodiment, the value used for comparison with each threshold value of the arrangement matrix of the density pattern is one kind in the packed unit in the addition code and C pixels in the packed unit in the vector code. This is a feature and does not care about the size of the density pattern layout matrix or the dot layout procedure.

(Second Embodiment) FIG. 9 is a principal block diagram showing a second embodiment of the present invention. FIG. 9 shows the configuration of the vector coding unit 107 in FIG. That is,
If the number of packed pixels C and the number of gradations p are large, the vector code is converted into an LUT (look-up table).
It becomes difficult to assign the code only. That is,
This is because there are as many input states as p to the Cth power (for example, when p = 17, p can be rounded to 16 and used as 4 bits at the expense of one gradation).

Therefore, in this embodiment, a method of reducing the capacity of the LUT and assigning codes by a simple method will be described.

In FIG. 9, reference numeral 901 denotes an input terminal to which the packed quantization coefficient information for C pixels is input. 9
Reference numeral 02 denotes a maximum value / minimum value detection unit, which detects the maximum value / minimum value in the C pixel. This maximum value / minimum value detection unit 9
02 can be shared with the detection mechanism of the evaluation unit 104 in FIG. However, here, the difference between the two is not calculated, but the threshold value calculation unit 903 calculates the threshold value for binarizing the C pixel in the packing based on the maximum value and the minimum value. In the present embodiment, the calculation is made by threshold = (maximum value + minimum value) / 2. Simple 2 shown in 904 based on the calculated threshold
The binarizing unit binarizes the C pixels in the packing. The maximum and minimum quantized coefficient information is transmitted to the LUT 905, and the binarized packing information is transmitted to the LUT 906. Although the two LUTs are separated on the block, the same memory may be used as a matter of course. The values output from both LUTs are encoded by the encoding unit 907 and output to the output terminal 908.

The processing of this embodiment will be described with reference to FIG. Now, assume that p = 17 and C = 8. Naturally, if this is left as it is, the number of input states is large, and it is difficult to assign codes in the LUT.

In FIG. 10, reference numeral 1001 indicates the input packing information. Here, the maximum value and the minimum value detected by the maximum value / minimum value detection unit 902 are 13, and the minimum value is 2. Therefore, the threshold value calculated by the threshold value calculation unit 903 is 7 or 8. Reference numeral 1002 denotes the result of simple binarization of the quantization coefficient information by the simple binarization unit 904 with the calculated threshold value. This 8-bit binary information is input to the LUT 906, and the approximated result is shown in 1003. On the other hand, (maximum value, minimum value)
The vector information of was (13, 2), but it is assumed that this vector information is input to the LUT 905 and the approximated result is (14, 2). The packing information encoded based on the approximated result of both is 1004. That is, in this embodiment, since resolution and gradation are separately processed, the capacity of the LUT can be reduced. In the example of FIG. 10, both the resolution and the gradation are approximated and compressed, but when there is a margin in the compression rate, it is better to preserve the resolution in the processing in the vector code.

The coding processing of the quantized information has been described above, but various modifications are conceivable. For example, even in the density pattern conversion of the addition code, a method of comparing the addition information of the C pixel with the threshold value of the arrangement matrix of the density pattern, allocating the addition information evenly to each pixel, and then allocating the assigned value of the arrangement matrix A method of comparing with a threshold value is possible. In the configuration of FIG. 1, the order of scalar quantization and packing of a plurality of pixels may be exchanged.

When the printer is capable of binary output or more, for example, m gradation output per pixel (n>p> m)
, P can be set as p = (A × B) × (m−1) +1. Further, in various processing, a portion that can be realized by the LUT may be processed by setting the LUT.

Further, the above configuration utilizes the property of the density pattern method. That is, in the density pattern method capable of simultaneously performing resolution conversion and binarization, there is a high possibility that the amount of information originally possessed will be lost due to the relationship between the number of input gradations and the enlargement ratio. For example, if the input signals are signals each having 256 gradations, 256 times (for example, 16 times x
Unless it is expanded 16 times), the information amount is lost (the vertical and horizontal magnifications may be different).

However, the loss of the information amount is used in the compression section, and the scalar quantization, the coding, and the density matrix arrangement matrix are optimized to reduce the deterioration caused by the compression and the coding.

[0055]

As described above, according to the present invention, when creating high resolution binary information, it is possible to reduce the amount of transfer information by a fixed length for transmission. Further, since the configuration is simple, it is possible to design a high-quality system in which the processing speed is high, the receiving side is low in cost, and there is almost no deterioration due to compression. In addition, it is possible to realize encoding that also satisfies gradation and resolution, and this adaptive processing is possible. Also, good binarization can be realized, and in a system with a high compression rate. Can reduce the table capacity at the time of encoding,
A printer system capable of effectively executing image recording can be realized.

[Brief description of drawings]

FIG. 1 is a block diagram of essential parts showing a first embodiment of the present invention.

FIG. 2 is a block diagram of a main part showing a conventional example.

FIG. 3 is a block diagram of a main part showing a conventional example.

FIG. 4 is a block diagram of a main part showing a conventional example.

FIG. 5 is a block diagram of a main part showing a conventional example.

FIG. 6 is a diagram showing a processing example of scalar quantization according to the first embodiment.

FIG. 7 is a diagram showing a processing example of the first embodiment.

FIG. 8 is a diagram showing a processing example of binarization of a vector code according to a modification of the first embodiment.

FIG. 9 is a principal block diagram showing a second embodiment of the present invention.

FIG. 10 is a diagram showing a processing example of the second embodiment.

FIG. 11 is a diagram showing an example of code allocation.

[Explanation of symbols]

 102 Scalar Quantization Unit 103 Packing Unit 104 Evaluation Unit 105 Addition Encoding Unit 106 Vector Encoding Unit 112 Density Pattern Converter

Claims (14)

[Claims] 1. An image processing apparatus for converting image information of n gradations per pixel into image information in which the number of pixels is increased by A × B times m gradations per pixel (n and m are n > M ≧ 2
The image information of n gradations, p gradations (where n
>P> m) image information that is scalar-quantized, and p-gradation image information from the quantization unit is compressed in units of C pixels (C ≧ 2) to a code that is less than the C-th power of p. Encoding means for encoding, the transmitting means for transmitting the code from the encoding means, the decoding means for decoding the code transmitted by the transmitting means in C pixel units, and the decoding means. An image processing apparatus, comprising: a density pattern unit that executes a density pattern method that outputs a pattern of m gradations for each pixel based on a decoded decoded signal. 2. The encoding means adds the quantized coefficient of the quantized value in the block for C pixels to create a first code, and the encoding means for the C pixels in the block. 2. The image processing apparatus according to claim 1, further comprising: a vector coding unit that quantizes vector information of the coding coefficient and allocates the second code. 3. An evaluation means for evaluating the feature quantity of the quantized coefficient, and a selection means for selecting either the first coding or the second coding based on the evaluation result. The image processing apparatus according to claim 2, wherein the first code and the second code are mixed and transmitted. 4. The density pattern means comprises first comparing means for comparing the decoded value of the first code with each threshold value of the arrangement matrix of A × B × C pixels, and C pixel portions of the second code. 3. The image processing according to claim 2, further comprising: second comparing means for comparing each pixel for C pixels with each threshold value of the arrangement matrix of A × B pixels based on the decoded value of. apparatus. 5. The image processing apparatus according to claim 3, wherein the evaluation unit evaluates based on difference values of codes of a plurality of pixels. 6. The image processing apparatus according to claim 1, wherein the quantization means uses different quantization conditions for a plurality of pixels. 7. The image processing apparatus according to claim 6, wherein a dither signal is superimposed on a quantization threshold as different quantization conditions. 8. The image processing apparatus according to claim 1, wherein the gradation number p satisfies p = (A × B) × (m−1) +1. 9. The image processing apparatus according to claim 2, wherein the vector coding means performs code allocation using a LUT (look-up table). 10. The vector coding means sets specific image information to 2 from the image information of p gradation for C pixels.
A means for selecting a seed, a means for converting p-gradation image information for C pixels into a binary value, and a first vector encoding means for encoding vector information of the selected two kinds of specific image information. An image processing apparatus according to claim 2, further comprising: a second vector encoding unit that vector-encodes the binary information of C pixels. 11. The specific image information selected from the two types is
The image processing apparatus according to claim 10, wherein the image processing apparatus has a maximum value and a minimum value in C pixels. 12. The image processing apparatus according to claim 10, wherein the binarization in the C pixel is performed by using the average value of the maximum value and the minimum value as a fixed threshold value. 13. The quantizing means, the encoding means and the transmitting means are on the printer driver side executed on a host computer, and the decoding means and the density pattern means are
The image processing apparatus according to claim 1, wherein the image processing apparatus is on the printer side. 14. An image processing method, wherein image information of n gradations per pixel is input and converted into image information in which the number of pixels is increased by (A × B) times m gradations per pixel. n,
m is a natural number that satisfies n> m ≧ 2, and n gradation information is p gradations for each pixel (where n> p <
m) a quantization step of performing scalar quantization on the image information, and an encoding step of compressing and encoding the image information of p gradation in units of C pixels (C ≧ 2) into a code less than the C-th power of p. A decoding step of decoding the coded image information in units of C pixels, and an output step of executing a density pattern method for outputting a pattern of m gradations of each pixel based on the decoded signal. Characterized image processing method.