JP3287717B2 - Image processing device - Google Patents

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, more particularly, to quantize input data into binary or multi-valued data while storing a difference between an input image density and an output image density by an error diffusion method or the like. The present invention relates to an image processing device.

[0002]

2. Description of the Related Art Conventionally, an error diffusion method has been known as a pseudo halftone process for representing input multi-valued data by binary or multi-valued levels smaller than the level of input multi-valued data. This error diffusion method is described in "An Adaptive Al.
goritm for Spatial Gray
Scale "in society for Info
rmation Display 1975 Symp
osium Digest of Technical
Papers, 1975, 36. In this method, the pixel of interest is P, the density of the pixel is v, and the densities of the non-binarized pixels P0, P1, P2, and P3 around the point P are v0, v1, v2, v3, and binarization, respectively. Is a threshold value of T, a binarization error E at the point of interest P is weighted by a weighting coefficient W empirically obtained for peripheral pixels P0, P1, P2, and P3.
This is a method in which weighting processing is performed with 0, W1, W2, and W3, and the weighting processing is performed so that the average density of the output image is macroscopically equal to the density of the input image. At this time, assuming that the output binary data is o, errors E0, E1, E2, and E3 with respect to the peripheral pixels P0, P1, P2, and P3 can be obtained by the following equations.

[0003]

[Outside 1] (However, Vmax: maximum density, Vmin: minimum density) E0 = E × W0; E1 = E × W1; E2 = E × W2; E3 = E × W3; (Example of weight coefficient: W0 = 7/16, W1) = 1/16, W
2 = 5/16, W3 = 3/16)

[0004]

A recording apparatus for recording an image using data processed by the error diffusion method is known. In this type of recording apparatus, the resolution in the main scanning direction is switched to change the sub scanning direction. There is also known a recording method in which the resolution is set higher than the resolution in the scanning direction.

Here, even when the resolution is switched in the main scanning direction, the binarization process by the error diffusion method is performed by using the weighting factor when the resolution in the main scanning direction and the resolution in the sub-scanning direction are the same. I was

In this case, there is a problem that a texture appears due to a difference in resolution in the main / sub-scanning direction, and image quality is deteriorated.

FIG. 5 illustrates this, and in FIG. 5A, the resolution in both the main scanning (left and right) direction and the sub-scanning (up and down) direction is 360 dpi (dot per in).
ch), whereas in (b), the same error diffusion method is used in the main scanning direction 720 dpi and the sub-scanning direction 360
This shows a case where a dpi image is processed. FIG. 5 (b)
Performs a binarization process using the weighting coefficients used in FIG. As can be seen from the figure, when the resolution in the main / sub-scanning direction is the same, the dots that were uniformly scattered globally are changed to the horizontal direction when the resolution in the main scanning direction is doubled by the same processing. In this example, an undesired texture (in this example, dots appear to be connected in the horizontal direction) appears. This is because, when the resolution is the same in the main scanning direction and the sub-scanning direction, the error is distributed to the peripheral pixels by the weight coefficient determined so that the dots are evenly distributed. This is due to the result of allocating errors with the same error distribution coefficient to an image whose resolution is twice as large as the direction.

The present invention has been made in view of the above-mentioned conventional problems, and provides an image processing apparatus capable of obtaining a high-quality image even when resolutions in the main / sub-scanning directions are different. Aim.

[0009]

According to the present invention, there is provided, in accordance with the present invention, input means for inputting multi-valued image data, processing means for quantizing the multi-valued image data, A dispersing unit that weights error data generated at the time of quantization processing based on an error distribution coefficient, and disperses the weighted error data into image data of a plurality of pixels; and a main scan of multi-valued image data input by the input unit. And a switching unit for switching the error distribution coefficient when the resolution in the sub-scanning direction is the same or different.

Further, according to the present invention, input means for inputting multi-valued image data, processing means for quantizing the multi-valued image data, Performing weighting based on the weighted error data, and dispersing means for dispersing the weighted error data into image data of a plurality of pixels, wherein the resolution in the main scanning and sub-scanning directions of the multilevel image data input by the input means is different. The dispersing means is characterized by using an error distribution coefficient having a large weight ratio in a scanning direction having a high resolution.

With the above-described configuration, even when the resolution of the input image data in the main / sub-scanning directions is different, the generation of texture is suppressed by using an error distribution coefficient according to the difference, and a high quality halftone processed image is obtained. be able to.

[0012]

【Example】

[First Embodiment] An embodiment of the present invention will be described below in detail with reference to the drawings.

FIG. 1 is a block diagram illustrating the configuration of an image processing apparatus according to a first embodiment of the present invention.

In FIG. 1, reference numeral 1 denotes a multiplier. The multiplier 1 multiplies the value of the denominator of the distribution coefficient (256 in the case of the distribution coefficient of FIG. 3) when allocating the error to the 8-bit input data. Reference numeral 2 denotes an adder, which adds error data from a pixel that has already been binarized to the 16-bit data from the multiplier 1. Reference numeral 3 denotes a comparator, which is a value obtained by multiplying “127” corresponding to an intermediate level between the 17-bit data from the adder 2 and the 8-bit input data by the denominator of the distribution coefficient (“127”).
× 256 ”). 1 bit 2 from comparator 3
The value data is sent to an unillustrated inkjet printer or laser beam printer, and an image is formed by turning on and off the dots.

A subtractor 4 calculates a difference between the 17-bit data from the adder 2 before binarization and the value after binarization, that is, error data. The value after binarization used in the subtractor 4 is 2
When the binarization result is 1, it is “255 × 256”, and when the binarization result is 0, it is “0”.

Reference numeral 5 denotes a divider, which divides the 16-bit data from the subtracter 4 by the value of the denominator of the distribution coefficient, and outputs a quotient of 8 bits (with a sign) and a remainder of 8 bits.

Reference numerals 6 and 7 denote latches for delaying the remainder data from the divider 5 by one pixel. That is,
The remaining 8-bit data from the latch 7 is added by the adder 2 to the input data input two pixels later. Reference numeral 8 denotes an error distribution table in which error data to be distributed to pixel positions shown in FIGS. 2A and 2B for each value of the quotient data from the divider 5 is stored in advance. For example, the quotient is 1 and the remainder is 5
When 0, 128 to e0, 71 to e1, 37 to e2, e
20 error data is distributed to 3 and 50 error data is distributed to the pixel on the right of e0.

Reference numerals 9, 11, and 13 denote latches for delaying data by one pixel. Reference numerals 10 and 12 denote adders, which are used for adding error data. or,
Reference numeral 14 denotes an error buffer capable of storing data for one line, and is for delaying the error data for one line.

The circuit of FIG. 1 switches between processing from left to right in the direction of → and processing from right to left in the direction of ← for each line of input data. As shown in FIG. 1, the storage position of the error data from the adder 12 in the error buffer 14 changes between processing in the rightward direction and processing in the rightward direction. This control is executed by a control circuit (not shown).

By executing the zigzag processing for changing the processing direction between the → direction and the ← direction for each line, it is possible to prevent the generation of a unique stripe pattern which has been a problem when the error diffusion method is executed.

In FIG. 1, reference numeral 20 denotes a resolution setting means. The resolution of input image data is input by an operator, and the input resolution is set. The resolution can be selectively set when the main / sub-scanning direction is the same and when the resolution in the main scanning direction is higher than the sub-scanning direction.

Reference numeral 21 denotes a weight coefficient selection reading means for selecting one of the weight coefficients shown in FIGS. 3A and 3B in accordance with the resolution set by the resolution setting means 20. 2
Reference numeral 3 denotes an error distribution table calculating unit that determines a value of the error distribution table 8 according to the selected weight coefficient, and 24 denotes a table download unit that loads the determined value into the error distribution table 8.

Next, the flow of processing will be described.

The input image pixel data input to the multiplier 1 is 8-bit multi-valued image data. The multiplier 1 multiplies the value of the denominator of the error distribution coefficient as shown in FIG. In this embodiment, the value of the denominator of the error distribution coefficient is 256.
And output to the adder 2. The adder 2 outputs the input image data multiplied by the value of the denominator of the error distribution coefficient in the multiplier 1, the rounding error output from the latch 7, the error from the previous line read from the error buffer 14, and the output from the latch 13. The error from the left horizontal (→ direction processing) or right horizontal (← direction processing) pixel is added and output. The data output from the adder 2 is input to the comparator 3. The comparator 3 compares the value output from the adder 2 with a predetermined threshold value (127 × 256 in this embodiment). At this time, if the output of the adder 2 is larger than the threshold value, 1 is output, and if not, 0 is output and this becomes binary data. The data output from the adder 2 and the data output from the comparator 3 are input to a subtractor 4, and the former is subtracted from the latter. Since the data output from the adder 2 is 17 bits and the value output from the comparator 3 is 1 bit, the latter is bit-extended inside the subtractor 4 and further multiplied by the denominator multiple of the error distribution coefficient. When the binary data is 1, the binarization error represented by (Equation 1) is calculated as 255 × 256, and when the binary data is 0, it is similarly set to 0. The binarization error calculated by the subtractor 4 is input to the divider 5 and is divided by the value of the denominator of the distribution coefficient. As a result, the quotient becomes an integer value and becomes a reference value for referring to the error distribution table 8, while the remainder becomes a rounding error of less than one and becomes the latch 6
Is input to

Here, the remaining 8-bit data is 0 to 255
However, since the input data is multiplied by 256 by the multiplier 1, the input data has 8 bits (0
To 255), the remaining 8-bit data 0 to 255 is 0 to 255/256, which is less than 1 for 8 bits of input data. As a result, the value of the rounding error can be reduced, and particularly, the image quality in the highlight portion of the image can be improved.

When the value obtained by dividing the data from the subtracter 4 by the value of the denominator of the distribution coefficient is 1.5, the divider 5 outputs a value of −2 as a quotient and outputs +128 as a remainder.
That is, the remaining data does not become a negative value.

The remaining 8 bits of data are delayed by latches 6 and 7 for two pixels and then input to adder 2 again. The quotient output from the divider 5 is input to the error distribution table 8 as a reference value. The error distribution table 8 is a RAM (random access memory) or R
This is a look-up table constituted by an OM (read only memory), and stores a value obtained by multiplying the denominator times of the weight coefficient previously loaded by the error distribution table download unit 24 for each binarization error value.

The error distribution table 6 is shown in FIGS.
The values corresponding to the error distribution window as shown in (1) are stored. Each value is multiplied by the denominator of the error distribution coefficient according to the value of the binarization error. ing. In this embodiment, two symmetrical error distribution windows as shown in FIGS. 2A and 2B are used by switching every line according to the processing direction. Therefore, one error distribution table is sufficient.

Here, the values stored in the error distribution table are created by the following procedure. First, the resolution in the main scanning direction and the sub-scanning direction of the image to be processed is set by the resolution setting unit 20, and the main / sub resolution is read out by the resolution reading unit 21. In accordance with the read main / sub resolution, the weight coefficient selection / read means 22 selects and reads an error weight coefficient used for error diffusion. In the present embodiment, the weighting factors are determined corresponding to the two symmetrical error distribution windows as shown in FIG. 2, and are switched and used for each raster in accordance with the error diffusion processing method. . The value of the weighting factor is determined in advance so that an undesired texture does not appear in accordance with the set resolution. When the resolution in the main / sub-scanning direction is the same as shown in FIG. If the resolution in the main scanning direction is set to twice the resolution in the sub-scanning direction, the weight coefficient selection and reading means 22 uses the coefficient value shown in FIG. Selected and read. The weighting factor selected and read by the weighting factor selection and reading means 22 is multiplied by the error distribution table calculating means 23 according to the value of the binarization error, and further multiplied by the denominator of the error distribution coefficient to obtain the error distribution table download means. 24, the data is downloaded to the error distribution table 8 in advance.

Here, the characteristics of the error distribution coefficients shown in FIGS. 3A and 3B will be described. The error distribution coefficient in FIG. 3A is a coefficient used when the resolution in the main / sub-scanning direction is the same, and the weight ratio in the main scanning direction (right direction) is 1
28/256, the weight ratio in the sub-scanning direction (downward) is (20 + 37 + 71) / 256 = 128/256, and the weight ratio in the main scanning direction and the sub-scanning direction is the same. The generation of texture can be suppressed for input image data having the same resolution in the scanning direction. The error distribution coefficient in FIG. 3B is a coefficient used when the resolution in the main scanning direction is twice the resolution in the sub-scanning direction, and the weight ratio to the main scanning direction is 177/25.
6. The ratio of the weight to the sub-scanning direction is (12 + 23 + 4)
4) / 256 = 79/256, and the weight is increased about twice in the main scanning direction. This is because the resolution in the main scanning direction is twice that in the sub-scanning direction, and the distance between the pixels to which the error is distributed is halved. Is twice the weight in the sub-scanning direction. This allows
Even when the binarization processing is performed by the error diffusion method on the input image data whose resolution in the main scanning direction is twice the resolution in the sub-scanning direction, the generation of the texture as shown in FIG. Can be suppressed. Therefore, when the resolution in the sub-scanning direction is higher than the resolution in the main scanning direction, the ratio of the weight of the weighting factor in the sub-scanning direction may be made larger than the ratio of the weight in the main scanning direction.

The error distribution table 8 outputs four values ek0, ek1, ek2, and ek3 in accordance with the value of the binarization error k.
It corresponds to the values 0, e1, e2, and e3. Therefore, the output ek0 is input to the latch 13 and is input to the adder 2 again after a delay of one pixel is added. The output ek1 is input to the latch 9, and after a delay of one pixel is added, the output ek1 is input to the adder 10 and added to the output ek2. The output of the adder 10 is a latch 11
, And a delay of one pixel is added, and then input to the adder 12 and added to the output ek3. Then, the output of the adder 12 is written to the error buffer 14. In this embodiment, the location where the error is written is two places to the left or right of the pixel of interest depending on the direction of the binarization process.
It is a place separated by pixels, and the direction of the binarization processing is switched every line.

By the above processing, 2 for one input data
Since the binarization processing is completed, the above processing is repeated while being shifted by one pixel in the processing direction, thereby enabling binarization processing for the entire image.

As described above, according to the first embodiment of the present invention, the value of the binarization error multiplied by the denominator of the weight coefficient is calculated in advance and stored in the table. The device can be omitted, the circuit scale can be reduced, and high-speed processing can be performed. Further, the sum of the density of the input pixel and the error distributed from the surrounding pixels is obtained, and the sum of the error and 2
Dividing the difference from the valuation result by the denominator of the weighting factor to determine the quotient and the remainder, the quotient is distributed to the peripheral pixels based on the values stored in the table, and the remainder is distributed to the peripheral pixels to obtain the weight. The coefficient can be given flexibility, and the value of the rounding error can be reduced from 0 to less than 1, so that the image quality including the highlighted portion can be improved.

According to this embodiment, even when the resolution in the main scanning direction and the resolution in the sub-scanning direction are different, the generation of texture is suppressed by devising the ratio of the weights of the weighting factors when allocating errors. High quality images can be obtained.

[Second Embodiment] FIG. 4 is a block diagram illustrating the configuration of an image processing apparatus according to a second embodiment of the present invention.

In the first embodiment, since the error distribution coefficient as shown in FIG. 3 is used, the number of denominators of the error distribution coefficient is a power of two. Therefore, the multiplier 1 and the divider 5 of the first embodiment can be omitted because they can be replaced by a bit shift operation. FIG. 4 is obtained by removing the multiplier 1 and the divider 5 from FIG. That is, the input data of 8 bits is input to bits 8 to 15 of the adder 2, and the operation result of the adder 2 is such that the upper 9 bits including the sign bit become a quotient, the sign bit and the lower 8
Bits correspond too much. The error distribution table refers to the upper 9 bits output from the adder 2. As can be understood from the equation (1), the binarization error can be obtained from the value of the upper 9 bits from the adder 2 without referring to this error data. If it does, there is no problem even if the table is referred to by the value of the upper 9 bits from the adder 2. Further, the binary data o is also registered in the error distribution table 8, and by referring to this value, the comparator 3 in the first embodiment can be omitted.

As described above, according to the second embodiment, it is possible to execute the error diffusion processing at a high speed by reducing the circuit scale without using a multiplier, a divider and a comparator, and to reduce the weight coefficient. It became possible to have flexibility.
Further, the rounding error in distributing the error can be suppressed from 0 to less than 1, and the image quality in the highlighted portion can be improved. Further, in the second embodiment as well, similar to the first embodiment, a weight coefficient corresponding to the resolution is used, so that generation of texture can be prevented.

In the embodiment described above, the input image pixel data is 8-bit multi-valued image data. However, the input image pixel data may be represented by a large number of bits such as 4 bits, 12 bits, and 16 bits. . The present invention can also be applied to quantizing 8-bit input data into 2-bit or 3-bit data. Further, in this embodiment, the error distribution window is constituted by four pixels. However, it goes without saying that the error distribution window can be constituted in the same manner even if the window is larger or smaller.

Furthermore, in the embodiment described here, there are only two types of weighting factors that can be selected: the case where the resolution in the main / sub-scanning direction is the same, and the case where the resolution in the main scanning direction is twice that in the sub-scanning direction. However, it goes without saying that a configuration in which more types of weighting coefficients are selected according to the set resolution can be adopted.

Further, by providing the circuits of this embodiment as many as the number of input colors, the present invention can be used for a color image.

[0041]

As described above, according to the present invention, even when the resolutions of the input image data in the main / sub-scanning directions are different, the generation of texture is suppressed by using an error distribution coefficient corresponding to the resolution, thereby achieving high image quality. A halftone processed image can be obtained.

[Brief description of the drawings]

FIG. 1 is a block diagram illustrating a configuration of an image processing apparatus according to a first embodiment.

FIG. 2 is a schematic diagram showing an error distribution window.

FIG. 3 is a schematic diagram showing an error distribution coefficient.

FIG. 4 is a block diagram illustrating a configuration of an image processing apparatus according to a second embodiment.

FIG. 5 is a schematic diagram for explaining a texture that appears due to a difference in resolution between a main scanning direction and a sub-scanning direction.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 1 Multiplier 2 Adder 3 Comparator 4 Subtractor 5 Divider 6, 7, 9, 11, 13 Latch 8 Error distribution table 10, 12 Adder 14 Error buffer 20 Resolution setting means 21 Resolution reading means 22 Weight coefficient selection reading Means 23 Error distribution table calculation means 24 Table download means

──────────────────────────────────────────────────続 き Continued on the front page (58) Field surveyed (Int. Cl. ⁷ , DB name) H04N 1/40-1/409 H04N 1/46 H04N 1/60

Claims (2)

(57) [Claims] An input unit for inputting multi-valued image data; a processing unit for quantizing the multi-valued image data; and performing weighting on error data generated in the quantization process based on an error distribution coefficient. A dispersing unit that disperses the weighted error data into image data of a plurality of pixels, and the error distribution coefficient when the resolution in the main scanning and sub-scanning directions of the multi-valued image data input by the input unit is different from the same. An image processing apparatus, comprising: switching means for switching. 2. Input means for inputting multi-valued image data; processing means for quantizing the multi-valued image data; weighting error data generated at the time of the quantization processing based on an error distribution coefficient; Dispersing means for distributing the weighted error data into image data of a plurality of pixels, wherein when the resolution in the main scanning and sub-scanning directions of the multivalued image data input by the input means is different, the dispersing means An image processing apparatus using an error distribution coefficient having a large weight ratio for a high scanning direction.