JPH01126076A - Color image processing method - Google Patents

Abstract

PURPOSE:To correct the position of a picture element without deteriorating the sharpness of an image by obtaining image data when the other color is shifted prescribed shift quantity for a reference color with the aid of referring the data of the plural picture elements and interpolating it. CONSTITUTION:The image data color-separated to R, G and B and quantized by an input system 1 is sent to an output system 9 through a shading correction circuit 2, a position dislocation correction circuit 3, an MTF correction circuit 4, a (gamma) correction circuit 6, a color correction.UCR circuit 7 and a gradation processing circuit 8. The position dislocation correction circuit 3 outputs the image data when the other color is shifted only the prescribed shift quantity for the reference color by referring the data of the plural picture elements and interpolating it.

Description

TECHNICAL FIELD The present invention relates to a color image processing method, and more particularly to a color image processing method suitable for a digital color image reading device and the like.

BACKGROUND OF THE INVENTION In manuscripts containing both pictures and text, the text is often black, even if it is a full-color manuscript.

To reproduce black on a full-color copier, use Yellow.

M agenta, Cyan (hereinafter referred to as rY, M,
Layer three color materials (referred to as CJ) on top of each other. However, Y
, M, and C, if Y, M, and C are not perfectly balanced, some color components will remain. In addition, if the alignment of the Y, M, and C plates is incomplete and there is misalignment, images that require high resolution, such as characters,
Image quality deteriorates significantly. As a countermeasure for this problem, in digital color copying machines, it is possible to apply UCR (undercolor removal) in which the overlapping portions of the three colors Y, M, and C are replaced with black (BK).

On the other hand, as an example of a color image input method, a method is known in which a dichroic prism disclosed in Japanese Patent Laid-Open No. 187180/1980 is used to form an image on three CCDs to obtain a color signal. . In this method, it is a national policy to completely eliminate chromatic aberration in the imaging optical system, but one point on the document is not accurately imaged at a predetermined position on each CCD, and therefore the color balance of the read pixel signals is distorted. It turns out. In addition, it is difficult to adjust the position of the CCD, there are many parts,
There are also disadvantages such as high cost.

In another example, in Japanese Patent Application Laid-Open No. 61-61561, elements of a photoelectric conversion array include Red, Green, and Blue.
(Hereinafter referred to as rR.

There is a system in which filters (referred to as G and BJ) are arranged regularly to solve the problem of position adjustment and number of parts. Another problem with this method is that because the R, G, and H photoreceptors are shifted from each other, data at the same point on the original image cannot be read, and color correction processing and the UCR processing cannot be performed accurately. It had a

Regarding this problem, one applicant previously filed a patent application filed in 1986-1.
There is a method proposed in No. 94712 "Color image processing method". This method uses the R
, G, and B by performing linear interpolation using data of two adjacent pixels to obtain image data at a predetermined position. This method can correct one pixel position, but linear interpolation means weighting is taking an average, and it has a low-pass characteristic as a digital filter, so high frequency components of the image are suppressed. , there was a problem that the sharpness of characters, line drawings, etc. deteriorated.

This will be explained in detail below. Figure 20 shows G
, B, and R color separation filters are regularly arranged. In the figure, each pixel indicated by n-4 to n+3 is subdivided into three minute pixels having G, B, and R color separation filters. These minute pixels are arranged continuously in the main scanning direction.

Therefore, the sampling point of the image is shifted by 1/3 pixel between G-B and B-B, and by 2/3 pixel between G-B. Let us consider the influence of this positional shift on the UCR processing. Specifically, the sampling density is 16d
ot/a+m, and as for the image, the thickness of the line is about 100 μm, especially for black characters where UCR processing is a problem, so the sampling situation in this case is shown in FIG. 21.

Here, to simplify the explanation, consider a case where the output value of the image is linear in reflectance, and the coloring material, paper, etc. are ideal. 21st
In the figure, the black line spans pixels n and n+1. In an ideal sensor with no positional deviation between each color, pixels n, n+1
The output value (reflectance %) is 5 for each of G, B, and R.
0%, 17%. When reproducing this using M, Y, and C coloring materials, which are complementary colors of G, B, and R, it is sufficient to use coloring materials having an area ratio of 50% and 83%, respectively.

Furthermore, if you perform UCR100% processing, you can replace the minimum values of M, Y, and C with BK, so in the end, only BK is 5.
It is sufficient to use 0% and 83%. However, in reality, since there is a positional shift between R, G, and B, the output values of each color become as shown in FIG. 22, and do not match among R, G, and B. Therefore, the required M, Y, and C are as shown in Figure 23, and even if UCR 100% processing is performed, the required amounts of M, Y, C, and BK color materials are as shown in Figure 24. You can see that it cannot be reproduced in BKI color.

In the above-mentioned Japanese Patent Application No. 194712/1988 entitled "Color Image Processing Method", the method is used to correct positional deviation between each color.

Linear interpolation is performed using data between two adjacent pixels. Considering the sensor position of B color as the center, G and R colors have a positional shift of -1/3 pixel and 1/3 pixel, respectively. If this is corrected by linear interpolation, the following formula % Formula % Here, GylyRn-z etc. represent the output value of the n-th pixel of G color and the n-1th pixel of R color, and On' p B
n'rRn' represents a correction value.

The Gn and Rn correction processes described above are [0, 2/3
, l/3], [1/3.2/3. The spatial frequency characteristics (MTF) of these filters, which are equivalent to one-dimensional digital filtering with coefficients [O], can be found by performing a discrete Fourier transform (DFT).

When the filter characteristic is expressed by f(x), its DFT is as follows: U: Spatial frequency N: 1/ΔX ΔX: Sampling pitch m: Filter size MTF(u)=IF(u)l'' (3).

Figure 25 shows the MTF characteristics of the digital filter when F(x) = [1/3.2/3,0 cm = 3 Δ x = 62.5 μm (16 dots/am) (f(x) = [
0,2/3.1/3 have the same characteristics).

As is clear from the figure, this filter has poor transmission of high-frequency components and has low-pass characteristics.

Therefore, by correcting the positional deviation using this filter, the high frequency components of the G and R color images are degraded. That is, the G and H images become blurred, and the sharpness of characters, line drawings, etc. decreases.

Purpose The present invention has been made in view of the above circumstances.Its purpose is to correct the pixel position without deteriorating the sharpness of one image by solving the above-mentioned problems in the conventional technology. An object of the present invention is to provide a color image processing method that obtains a color image.

Configuration The above object of the present invention is to provide a color image processing device having an image reading means using a one-dimensional color image sensor in which color separation filters are regularly arranged, in which another color is shifted by a predetermined shift amount with respect to a reference color. This is achieved by a color image processing method characterized in that the color image processing method is configured to obtain image data by interpolating with reference to data of a plurality of pixels.

Hereinafter, after a detailed explanation of the present invention, based on examples,
The configuration will be explained in more detail.

From the sampling theorem, if the one-dimensional signal g(t) whose band is limited below the frequency W is sampled at an interval of T=1/(2W), that is, at a sampling frequency of f,=2W, then the following equation is obtained. This allows the original signal to be completely restored.

g(t)=Σg(iT)S(t-iT)...(4)
i=-ω T=1/(2W) 2πWt According to the color image processing method according to the present invention, the principle of equation (4) above is applied to the sampled image to obtain interpolated data, and positional deviation correction is performed.

Here, a method for calculating interpolated data will be explained. Third
The figure shows the relationship between the position of the sampling pixel, the position at which interpolated data is obtained, and other parameters. Using the parameters shown in FIG. 3, interpolated data ○(X) can be obtained by the following equation.

...(5) Here, h(x) is an interpolation function, h(x) = stnc(x) 1nrIx Ix to ψ, but from the graph of h(x) shown in Figure 4, As shown, when IXI increases, h(x) →
0. Therefore, in practice, 1 may be in the range of about -2 to 2.

By the way, the interpolation data can be any one of R, G, and B.
It is sufficient to calculate the remaining two colors using the color as a reference. Here, a case will be described in which positional deviation correction is performed for G and R using B as a reference. However, the positional relationship of R, G, and B is as shown in FIG. 20. That is, R
As for the data, interpolated data at a position shifted to the left by 1/3 pixel from the pixel of interest Ixo is used.

Here, if xo is the origin (x0=O), the position from which interpolated data is obtained is as follows. By using the above equation (5), the interpolated data becomes as follows.

(6) FIG. 14 shows the values of each coefficient when data of five pixels of i=-2, -1, 0, 1, and 2 are used. A one-dimensional filter using the coefficients shown in FIG. 14 [: 10.1676°0.4191, 0.8383. -0.2095,0.1
By using 197 pixels, an image shifted by 173 pixels can be obtained. In other words, it is possible to convert the image into an image having the same phase as the B color.

When the MTF characteristic of this correction filter is determined using the above-mentioned equations (2) and (3), it becomes as shown in FIG. 5(a). It can be seen that flat characteristics without deterioration can be obtained up to the high frequency range. When implementing this filter in hardware, it is desirable that the coefficients be rational numbers that are as simple as possible. Figure 5 (b
).

One thing to keep in mind when approximating coefficients to rational numbers is the ratio between coefficients. If the coefficient for pixel i is C, then, although some intermediate calculations are omitted, it becomes, and in a small range of lil, l], that is, in a large range of Ct and Cj, the ratio of the coefficients becomes a simple integer ratio. Become.

This makes it possible to ensure the accuracy of the position (coordinates) for which interpolated data is obtained.

In the above explanation, interpolation of R color data has been described, but for G color, the filter coefficient can be calculated using equation (6) with x=+−p. Also, G, B
, H, based on R color, can be calculated in the same way using equation (6) by setting x=+-p. You can get filters.

Embodiments of the present invention will be described in detail below with reference to the drawings.

FIG. 1(a) is a block diagram of a digital color copying system which is an embodiment of the present invention. In this system, image data that has been color-separated into R, G, and B by an input system 1 and quantized is corrected by a shading correction circuit 2 for unevenness in sensitivity of a light source and an image sensor.

Below, positional deviation correction circuit 3. MTF correction circuit 4° γ correction circuit 62 Color correction/UCR circuit 7 The converted image data is sent to the output system 9 to obtain a copy image.

Here, the MTF correction circuit 4 corrects image blur caused by the input system, and in a digital copying system, a digital filter having coefficients as shown in FIGS. 2(a) to 2(d) is used. The value of the coefficient should be determined based on the MTF characteristics of the actual input system, but it is not limited to 3×3, and filters with sizes such as 5×3 and 5×5 may also be used.

As shown in FIGS. 3(e) and (f), the correction can be performed separately in the main scanning direction and the sub-scanning direction.

By the way, the positional deviation correction circuit according to the present invention is a one-dimensional filter, and can be combined with a first-stage MTF correction filter to form one filter. FIG. 2(h) shows a combination of the MTF correction filter (a) and the positional deviation correction filter (g). In addition, (i) is a filter for MTF correction in the main scanning direction (
e) and a positional deviation correction filter (g).

In Fig. 2 (h), the size of 7 x 3 is obtained by combining filters of size 3 x 3 and 5 x 1, and in Fig. 2 (i),
By combining the 3×1 and 5×1 filters, a 7×1 filter is obtained.

Here, the coefficients on the outside of the filter may be omitted considering that they are smaller than the coefficients near the center. FIG. 2(j) is a 5×1 filter obtained by ignoring the two outer elements of FIG. 2(i). Regarding (h), a similar simplification is possible. By combining filters into one in this way, hardware can be simplified and calculation accuracy can be improved.

FIG. 1(b) shows a system configuration in which the positional deviation correction circuit and the MTF correction circuit are integrated into one.

1(Q) and (d) are the systems shown in FIG. 1(,) above with a variable magnification circuit 5 added thereto. In digital copying systems, it is relatively easy to obtain a wide range of magnification ratios, not only when using an equal-magnification optical system for the input system but also when using a reduction optical system. A method of varying the magnification is used.

The electrical scaling method converts a pixel data string sampled at the same magnification into a data string with a pixel density according to the scaling factor.6 For example, when 100 pixel data are sampled at the same magnification, If you want to enlarge by 120%, set it to 100.
Based on the pixel data, calculate 120 pixel data and calculate 7
In the case of 0% reduction, an operation is performed to obtain data for 70 pixels.

As an example of the above-mentioned electric magnification device, the present applicant has previously described
Patent Application No. 61-100503, No. 61-100505, No. 61-100506, No. 61-101721,
There are devices proposed in No. 61-104014 and No. 62-3262.

Among electrical scaling methods, those that use a Sinc function as an interpolation function can obtain scaling data with high accuracy.

Figure 6 shows the sampling position (Xi) of the same size data and 1
Sampling position at 33% enlargement (y i), 80
Sampling position when reducing by %! (zt). In this scaling method, image data at a position indicated by y□+ZL is obtained according to the above-mentioned equation (5) using data at a position indicated by X engineering.

By changing the density of the sampling points of the variable-magnification image indicated by 3'1yZi, it is possible to change the magnification at an arbitrary magnification ratio.

In this embodiment, by shifting the new sampling position after the above-mentioned scaling by a predetermined amount for each color, R, G, B
This method corrects the positional deviation between pixels at the same time as the scaling process. In other words, if we consider the relationship between the sampling positions of the three colors in the case of Figure 20 mentioned above, the pixel data at the position shifted 1x3 pixels to the left for R color and 173 pixels to the right for G color with respect to B color. It is obtained by interpolating.

FIG. 1(d) shows a digital copying system having a variable magnification processing section, but in this embodiment, in order to take positional deviation correction into consideration during the variable magnification processing, as shown in FIG. 1(e), It is also possible to combine the surface processing sections into one.

As described above, the positional deviation correction process can be combined with the MTF correction process or the variable magnification process.

The combination with the MTF correction process is to superimpose the function for MTF correction on the interpolation function shown in equation (5), and the combination with the scaling process is to superimpose the interpolation data in equation (5). This is to shift the sampling position to be determined.

Therefore, by performing these two combinations at the same time, it is possible to integrate the three processing units of positional deviation correction, MTF correction, and variable magnification into one. Figure 1(f) shows 1 position deviation correction.
An example of the configuration of a copying system having a processing unit that combines three processing units, MTF correction and magnification processing, is shown. In this case, the MTF correction circuit in the subsequent stage performs MTF correction in the sub-scanning direction. Although it is possible to combine the MTF correction in the sub-scanning direction into one, there is an advantage that the correction calculation unit is simpler if it is separated by one.

A specific configuration example will be described below.

FIG. 7(a) shows an example of the circuit configuration of the positional deviation correction filter shown in FIG. 2(g). By receiving the image data output from the input system with the five stages of latches, it is possible to simultaneously refer to the data of five pixels in the main scanning direction. In this example, the image data is multiplied by the coefficient of the positional deviation correction filter shown in FIG. 2(g) using a ROM instead of a multiplier and using a table reference method.

Furthermore, So and S-1 and Sl and S-2 are made into pairs, and the first stage addition is also performed simultaneously. That is, S
At the memory address addressed by the image data o and S-2 or Sl and 81, the sum of the products of the respective image data and the corresponding coefficients is stored.

The intermediate results of the operation output from the ROM are added by the next adder, and the operation ends.

A filter that combines positional deviation correction and MTF correction in the main scanning direction (see Fig. 2 (i) and (j)) is shown in Fig. 7 (a).
) can be realized by expanding the circuit. In other words, all you need to do is add the required number of latches, multipliers, and adders in the subsequent stages.The difference in coefficients is as shown in Figure 7(a). All you need to do is change the data to be stored.

FIG. 7(b) shows a configuration example of the MTF correction circuit in the sub-scanning direction. By sequentially updating and storing image data in the line memory for two lines, it is possible to refer to the data of three corresponding pixels of three consecutive lines at the same time.

Here, the MTF correction filter shown in FIG. 2(f) will be explained. The data of the two peripheral pixels corresponding to the coefficient of -1 are added by the adder.
The calculation of subtracting the output value from the adder from the value three times (the value of the center pixel) is performed using a table reference method.

In this way, when MTF correction is performed separately in the main scanning direction and the sub-scanning direction, either direction may be performed first. In other words, either of the circuits in FIGS. 7(a) and 7(b) may be placed first.

Next, the scaling process will be explained.

The scaling process is performed, for example, by a circuit configured as shown in FIG. The circuit shown in Figure 8 consists of a function to determine the position of a new sampling point after scaling, and a function to calculate new data from the distance between the new sampling point and the old sampling point and the old data. .

First, in order to extract peripheral data at once when determining a new sampling point and performing calculations in the future, the data synthesis unit uses a correction method to group data into 6-pixel units using the interpolation method using 6 peripheral pixels. 1 For example, in Figure 3,
If the new sampling point X is between xo and
This means that sz is taken out at once.

A specific method is to input data (DATAI) sequentially input in synchronization with a data clock into a data clock (DC
This can be done by latching at LK). If there are 6 pixels, this can be realized using 5 stages of latches.

Next is the line memory section. This is a memory that stores groups of 4 to 8 pixels for the number of pixels in one line. It has a two-stage configuration for input and output, and when one is input, the other is The configuration is such that the input and output are reversed when one output line ends.

When input, the address of this line memory is
The address obtained by counting up the counter in synchronization with K is used as is, but this address is changed when outputting. The address at the time of output corresponds to the position determination function of the new sampling point.

When a new sampling point is between xl and Xi+□, and the next new sampling point is between xi and Xi+□, the counter is stopped and X i+
When it moves between +a and Xi+z, the counter is incremented by two, and when it moves between X1+□ and Xi+z, the counter is incremented by one as usual.

The counter may be stopped at the time of enlargement, and the counter may be incremented by two at the time of reduction. That is, when enlarging, the position of the new sampling point is determined by the operation of incrementing the counter by one and the operation of stopping the counter. When shrinking, the position is determined by a combination of operations that advance the counter by one and two. As long as reduction is considered within the range up to 50%, it is sufficient to advance the counter by one or two, but if the reduction rate is 50% or more, the counter may be advanced by three.

Information regarding where and how many increments the counter should be incremented is calculated in advance by the CPU based on the magnification. New sampling point position i! For the x-worker, set the starting position to 0. If the old sampling pitch is 1 and the magnification is α (%), then X = -X i (i = 0, 1, ...).
...(9) α becomes.

Assuming that the new sampling point is between X□ and X i+x, the integer part of xi in this case is i. In other words, when i increases and the integer part of xi increases by 1, the counter tL advances by 1, and when i increases and the integer part of Xi increases by 2, the counter also advances by 2 and the integer part of xi increases by 1. If the counter does not advance at all, you can prevent the counter from advancing either.

Further, the decimal part of Xi is the distance ΔX between Xi and X.

This distance data will be used later in the interpolation calculation section.

The CPU calculates i=o to cz-1 using equation (9). This is because in all cases, the new sampling points are every α period. This calculation is performed after the magnification α (%) is specified before the start of the reading operation, and is written in a form that matches the hardware in a RAM or the like, and is sequentially read out during the scaling process.

Alternatively, as another method, a dedicated CPU or arithmetic means is provided, the above formula (9) is calculated in parallel with the scaling process, and the integer part of the calculation result Xi is used as an address,
It is also possible to use the decimal part as distance data.

An example of the configuration of the data synthesis section and line memory section is shown in FIG. This example is a configuration example when two-pixel correction is performed.

Here, when the RAM is in the input state, the address generation section advances the address counter in synchronization with DCLK in normal operation, but when the RAM is in the output state, it modifies the address by the method described below.

The first method is to change the frequency of the counter clock. If the frequency of DCLK is fo,
α (%) Frequency when changing magnification fL:X is fα=□f0
...(10) α becomes. This method is accurate and reliable because the deviation of fα with respect to f is the deviation of the sampling point itself.

When reading from the RAM, the desired composite data can be obtained by moving the address counter with the above fα and sampling (latching) the output of the RAM again with DCLK.

With this method, the calculation result of equation (9) mentioned earlier is
Information about the integer part is no longer needed; only information about the bottom part, that is, information about the distance is needed.

Another method is to focus on the integer part in the calculation result of equation (9), and calculate (1) When reducing: When the integer part increases by one → a = 1 When the integer part increases by 2 → al=Q (2) When expanding: When the integer part increases by 1 → al=
1. When the integer part is not increasing, → al = Q. Define the sequence (ai) from i = O to α-1, and use RA
There is a method in which a clock having a frequency 2f0, which is twice the frequency of DCLK, is prepared as a clock.

During the scaling process, ai is read from the RAM. Read is i
It is assumed that =O to α-1 are read out repeatedly. During reduction, the address counter clock for the output of the line memory (RAMI or RAM2) is: When al=1: fo (DCI, K) When a=0: 2f.

Switch so that

When expanding, the address counter clock is ai and DCL.
By performing an AND of K, it is possible to count up when a = 1 and not count when al = o.

A block diagram of a circuit for implementing this method is shown in FIG. The RAM 3 is a memory that stores ai and decimal part information of the result of equation (9) calculated by the CPU.

If this method is used, the data synthesis section shown in FIG. 8 can be omitted. In other words, the peripheral data can be obtained by inputting 6-bit data as is to the line memory in synchronization with DCLK, and after output, latching it in several stages using the aforementioned clock in the interpolation calculation section. It's for a reason.

Still another method is shown in FIG. 11, in which the address counter itself continues to count up based on DCLK. and,
One more thing besides the address counter.

This has an UP/DOWN counter, and when expanding, DO
WN, set it to UP when reducing. This UP/DO
The clock of the WN counter is an AND of DCLK and a-work so that it counts only when al=Q.

By this, for example, when reducing, first a1=o
Set the UP/DOWN counter to 1 and add 1 to the value of the address counter to obtain the address of RAM1 or RAM2. Furthermore, at the next Bi=Q, the UP/DOWN counter is set to 2, the address counter is added, and so on, and the position of the new sampling point is determined. In the case of expansion, conversely, subtract one by one with a = 0, so UP/
The DOWN counter is decremented.

Next, a method of interpolation calculation will be explained.

The interpolation calculation involves calculating the above-mentioned equation (5), but the problem here is the positional accuracy of the new sampling point. In other words, the question is to what degree of accuracy ΔX/p should be considered.

In the present invention, since a 1/3 dot deviation between R, G, and 8 is corrected, an accuracy of about 0.1 dot is required. Therefore, it is sufficient to consider Δx 1/p with an accuracy of 1/8 or 1/16 doso. Furthermore, if emphasis is placed on correcting the positional deviation of 173 dots, it is effective to treat Δxi/p with an accuracy of 173 dots or 1/6 dot. In other words, by shifting the new sampling points of the two colors on both sides of the new sampling point of the pixel of the central color among R, G, and B by ±173 dots, interpolated data is obtained without any calculation error. be able to.

Here, as a representative example, a case will be explained in which processing is performed with 1/8 dot accuracy.

When handling with 178 dot precision, the decimal part of ΔX/p will be treated as 3-bit data. Third
In the figure, Δx, , /p are quantized in eight ways as shown in FIG. Eight sets of coefficients of equation (5) are prepared for eight types of bi. Here, interpolation using 6-pixel reference with symmetry in mind will be explained.

In FIG. 16, for each bL, pixel X□(i = -3
, -2, -1, 0, 1, 2).

FIG. 12 shows an example of the configuration of an interpolation calculation circuit. In this circuit, 6 pixel data referred to during interpolation, which is output from the line memory shown in FIG. 9 above, is received by a latch and 1
The calculation of equation (5) is performed using a multiplier and an adder. On this occasion,
The coefficients must be changed as shown in FIG. 16 depending on the value of bi.

In the example shown in FIG. 12, a ROM is used instead of a single multiplier to perform multiplication using a table reference formula and add two pixels. Furthermore, by inputting the above b into the ROM address in synchronization with DCLK, the coefficients can be easily changed. The outputs from the ROM are added by two adders, and the interpolation operation is completed. Here, any two pixels may be selected for the first stage addition using ROM, but it is better to combine pixels with similar coefficient values as shown in Figure 16 for more accurate calculations with a smaller number of bits. Can be done. Here, 5o-S-8,s, -s-,,52-s-
.

It is good to combine.

The above is the calculation for the basic color component image. For the other two colors, it must be shifted by 173 dots. For example, this has an address generator for each color as shown in FIG. 10, and a RAM corresponding to each color.
3, the aiyt) process when shifted by the specified amount is
All you have to do is calculate and write it. However, since the amount of shift is always constant, it is possible to use only one address generator.

Next, an interpolation calculation method that is a further improvement on the above method will be described.

If the set of coefficients shown in FIG. 16 is selected, interpolated data can be obtained in units of 178 dots. Therefore, it is also possible to obtain interpolated data at a position shifted by 173 dots≠3/8 dots. When the decimal part b□ of the coordinates of the standard color is 4 (more precisely, 478), if you select b□ = 4 ± 3 for other colors, you can obtain interpolated data at a position shifted by 13/8 dots. It will be done.

3/8 = 0.375. 1/3 = 0.333,
In practice, a sufficient positional deviation correction effect can be obtained even when 3/8=1/3. When the positional accuracy is set to 174 dots, a shift of +1/4 dots provides some effect, but if the emphasis is placed on correcting positional deviations, 173 dots correction is more effective.

Returning again to the case of 178 dot accuracy. When bi is 2 or less or 5 or more, the shift of +3/8 dots may cause the bi of other colors to become negative or exceed 7. In the standard color, the interpolation position X exists between X-1 and xo, but due to the shift operation, in other colors,
This means that it may come between o and xl. As a countermeasure for this, for a color that shifts by -173 dots, use S-4ts-3tS-ZIS-L9S@ts as a reference pixel.
For 7 pixels of 1ts1, +173 dots shift color, s +3, s +3, s +lt S
Prepare 7 pixels of OI S 1 t S 2 + S 1, and if B1 is other than O to 7, S
In the latter case, the 16th pixel is
Interpolation calculations may be performed using the appropriate set of coefficients shown in the figure. In this case, the coefficient for B2 in the former case and S-3 in the latter case is 0.
It is.゛In Figure 17, 89~S when shifted by -173 dots
The coefficient for 2 is shown. In the case of +1/3 dot, S-
3 to S, coefficients can be similarly determined. FIG. 13 shows an example of the configuration of the arithmetic circuit in this case. here,
For b, the same signal as the reference color is used, and the contents of the ROM table may be the result of calculation using the coefficients shown in FIG.

In addition, in FIG. 17, Cn1. indicates the coefficient when b=n and pixel number=m.

Here are some other examples.

It has already been explained that by using the filter shown in FIG. 2(g) above, data shifted by -1/3 dots can be obtained. Here, by using coefficients obtained by superimposing the filter coefficients shown in FIG. 2(g) on the coefficients shown in FIG. 16, the shift operation and interpolation calculation are performed simultaneously. This combination results in one-dimensional filter calculations of 6×1 and 5×1 sizes, resulting in a 10×1 filter calculation. Although 10 pixels may be referred to, in order to simplify the hardware, sufficient effects can be obtained by using approximately 6 to 8 pixels with large coefficients.

FIG. 18 shows coefficients when performing interpolation calculations with reference to seven pixels S-1 to S. In the case of +173 dot shift, the coefficient can be found in the same way.

Here, new coefficients were calculated using two sets of filter coefficients, which are shown in Fig. 15 as Δx, /p = Δx, /p + 1/3 for b = O ~ 7. This is the same as finding the coefficient from equation (5).

Both of the above two methods can use the ayop tri data in common for each color.
l) In the method of calculating i by the CPU, the load on the CPU can be reduced.

The combination of magnification processing and positional deviation correction processing has been described above in detail, but as described above, it is possible to further incorporate MTF correction into one. These processes can be combined into one by multiplying the coefficients for calculation, as shown in FIGS. 16 to 18. FIG. 19 shows the coefficients of the filter obtained by superimposing the MTF correction filter in the main scanning direction shown in FIG. 2(e) on the variable magnification and ten-position shift correction filter shown in FIG. be. Here, the reference pixels are 7 pixels.

Note that it is also possible to use the above-mentioned improved method for one position shift by combining the magnification change and MTF without superimposing the three filters.

Effects As described in detail above, according to the present invention, in a color image processing device having an image reading means using a one-dimensional color image sensor in which color separation filters are regularly arranged, different colors are used for the reference color. Since the image data obtained when shifted by a predetermined shift amount is determined by interpolation with reference to data of a plurality of pixels, the color image can be corrected for pixel positions without deteriorating the sharpness of the image. This has the remarkable effect of making it possible to implement a processing method.

[Brief explanation of the drawing]

1(a) to 1(f) are block diagrams of a digital color copying system showing an embodiment of the present invention, FIG. 2 is a diagram showing the structure of a digital filter, FIG. 3 is an explanatory diagram of sampling positions, and FIG. The figure is a graph showing the Sinc function, Figure 5 is a graph showing the MTF characteristics of the filter used in the example, and Figure 6 is a graph showing the MTF characteristics of the filter used in the example.
7(a) is a block diagram showing an example of the circuit configuration of a positional deviation correction filter.
Figure (b) is a block diagram showing an example of the configuration of the MTF correction circuit in the sub-scanning direction, Figure 8 is a block diagram showing an example of the configuration of the scaling processing circuit, and Figures 9 to 11 are the data synthesis section and line memory. FIGS. 12 and 13 are block diagrams showing examples of the configuration of the correction calculation circuit, FIG. 14 is a diagram illustrating the digital filter along with its calculation process,
Fig. 15 is a diagram showing the process of positional deviation correction, Figs. 16 to 19 are diagrams showing the coefficients of the synthesized digital filter, Fig. 20 is a diagram showing the line sensor, and Fig. 21 is a diagram showing sampling by the line sensor. A diagram showing the situation, Figure 22~
FIG. 25 is a diagram for explaining the problems of the prior art. 1: Input system, 2: Shading correction circuit, 3: Positional deviation correction circuit, 4: MTF correction circuit, 5: Magnification changing circuit, 6:
γ correction circuit, 7: Color correction/UCR circuit, 8: Gradation processing circuit, 9: Output system, 10: Positional deviation correction/MTF correction circuit, 11: Positional deviation correction/magnification circuit, 12: Positional deviation correction/ MTF correction/variable magnification circuit. Patent applicant Ricoh Co., Ltd. Figure 2 (a) (b)
(c) Fig. 2 (h) Fig. 3 Winter Fig.'5 7 Fastening side Storage Fig. 7 (a) Latch x 5 Fig. 7 (b) Line memory x 2 Fig. 10 Reduced Fig. 11 or Reduced Figure 15 Figure 20 n-4z-3n-2n-1n n+1 n+2
nF3 Figure 21 GERGB Figure 22 Figure 23 (Area ratio equivalent %) Figure 24 (Area ratio equivalent %)

Claims (5)

[Claims] (1) In a color image processing device having an image reading means using a one-dimensional color image sensor in which color separation filters are regularly arranged, image data obtained when another color is shifted by a predetermined shift amount with respect to the reference color is , a color image processing method characterized in that the color image processing method is configured to perform interpolation with reference to data of a plurality of pixels. (2) The color image processing method according to claim 1, wherein the predetermined shift amount is ±(1/3) dots. (3) The color image processing method according to claim 1 or 2, wherein the interpolation is performed using a Sinc function. (4) The interpolation is performed by combining two pixels each starting from the one with the largest weight.
The color image processing method according to item 2 or 3. (5) The color image processing method according to claim 1, 2, 3, or 4, characterized in that the number of reference pixels when performing the interpolation is 4 or more pixels. .