JP3150994B2 - 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 an image processing apparatus for requantizing color image data in accordance with a plurality of sets of color data that can be expressed by a recording apparatus.

[0002]

2. Description of the Related Art Conventionally, this type of device uses sensors for RGB.
The image data read after color separation is subjected to data conversion called masking / UCR processing into four color data of CMYK, which is a recording color, in consideration of recording characteristics. Further, it is configured such that the pseudo intermediate processing is independently performed in each color space separated into four colors.

[0003]

However, the above-mentioned prior art has the following drawbacks. When performing pseudo halftone processing by the conditional decision dither method represented by the error diffusion method, it is hard to say that one point on the recording paper necessarily represents the color of the input image.
Black dots generated by so-called black generation, which are slightly generated in the uncolored color, cause an unnatural texture and lower the image quality.

When the recording characteristics fluctuate, when a binary recording apparatus is used, so-called masking
If correction of the CR coefficient is to be performed, enormous data processing is required, and it cannot be realized at low cost on an actual machine.
When the requantized data after the pseudo halftone processing is compressed, it can only be performed independently for each of the correlated colors for four colors.

The present invention eliminates the above-mentioned disadvantages of the prior art.
And a plurality of sets of color data
From among the color space data to be processed,
Is requantized by selecting color data that is close to
Re-quantization process that is faithful to the color image
Furthermore, the input color image data can be expressed in a color that can be
By restricting according to the characteristics,
An object of the present invention is to provide an image processing apparatus capable of preventing divergence of requantization processing .

[0006]

To achieve the above object, according to the Invention The image processing apparatus of the present invention comprises input means for inputting color image data, the re-quantization processing by the re-quantization errors originating
And limiting means for limiting in accordance with the color image data input by said input means in order to prevent the dispersion in the color characteristics of the recording device, or a plurality of sets of color data possible representation of the recording device
The color image data limited by the limiting means.
It is characterized by having requantization means for performing requantization by selecting color data having the closest color space distance, and correction means for adding and correcting a requantization error generated during the requantization processing. And

Preferably, the requantization means calculates a plurality of weighted average values of the pixel of interest in accordance with the printing characteristics of the printing apparatus; Selection requantization means for selecting and requantizing a weighted average value closest to the color image data from the means.

[0008]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS A preferred embodiment according to the present invention will be described below in detail with reference to the drawings. FIG. 1 is a schematic block diagram illustrating the configuration of the image processing apparatus according to the present embodiment. First,
An analog image signal which is separated into three colors of R, G, and B by the CCD 1 and read is quantized by the A / D converter 2 into a digital signal having an 8-bit width. Then, the shading correction unit 3 corrects the unevenness and filter characteristics of the sensor 1 and an imaging system (not shown), and converts them into so-called NTSC / rgb luminance data. , Y '. When reading recording characteristics, the memory 8 stores an actual recording device 7 described later.
Can record one point in, for example, red (R), green (G), blue (B), cyan (C), magenta (M), yellow (Y), black (K), and white (W). R, g, logarithmically converted each of the eight recording colors
Stored as b data. When the recording device 7 has the above-described data in advance, the recording device 7 may input the data to the memory 8.

The density data converted in accordance with the above-mentioned recording characteristic data is limited by the gamut limiting section 5 to a color reproduction area. Gamut-limited c, m, y data is input to the requantization unit 6, and the above-described recording characteristic data, that is, any one of the eight recordable colors for one input image data is recorded. It is determined whether the recorded case is closest to the color of the input image and determined. Here, 1-bit data of each of CMYK, which is a recording color, is decoded from the determined eight-color data and recorded by the recording device 7.

[Explanation of Requantization Unit] Next, the detailed configuration of the requantization unit 6 will be described with reference to FIG. In the figure, the 3-bit data quantized by the selective requantization unit 62 is decoded into 1-bit data for each of CMYK by the recording signal conversion unit 64, and a weighted average in the vicinity of the pixel of interest based on the 1-bit data for each of cmy. Average value calculation unit 6
Required by 1. The signals are associated according to Table 1.

[0011]

[Table 1]

Eight kinds of weighted average values are obtained in order to predict the requantization of the target pixel into eight colors. Therefore, the selective requantization unit 62 ends the requantization by selecting the predicted value closest to the input data. At this time, the difference between the selected predicted average value and the input data is calculated in each cmy space. The difference, that is, the requantization error is corrected by the error correction unit 63.
The above-mentioned weighted average value is calculated by replacing a plurality of data already requantized in eight ways with cmy multivalued data obtained by the actual recording device 7 obtained from the memory 8.

Next, a more detailed description will be given with reference to FIG. In the figure, a memory 610 is a Fifo that delays image data requantized to 3 bits by one line, and data at its input / output terminals are provided independently of c, m, y.
The weighted average calculators 614a to 614c for three colors are connected. In other words, the requantized data is represented as c, m,
After being converted to y-valued data, for example, for cyan, F
/ F 611a-c, the weighted average values based on the requantized data of four pixels adjacent to the pixel of interest, which are further delayed and held by several pixels, are obtained by the weighted average calculation units 614a-c. Here, Table 2 shows the recording characteristics used in this example.

[0014]

[Table 2]

The weight for obtaining the average value is shown in FIG.
As shown in (a) shown in FIG.
1 to D and the target pixel as shown in FIG.
値 6/16. In the case of cyan, the F /
F611c output is A, F / F611a input is B, F / F
The output 611a corresponds to the position of C, and the output of the F / F 611b corresponds to the position of D. Therefore, the weighted average value calculation unit 614a
Performs a so-called sum-of-products operation using the weighting coefficients shown in FIG. 4B, and calculates eight types of average values in which requantization of the target pixel is predicted in eight ways.

[0016]

[Table 3]

For example, if the ABCD requantization results are cyan, white, yellow, and white,
Table 3 shows the recording characteristics shown in FIG.
From 4a to 4c, the average values m _c and m for the four pixels shown in the following equation are obtained.
_m, m _y are obtained, respectively. _{m c = (4 × 206 +} 1 × 15 + 4 × 19 + 1 × 15) × 1/16 = 58 m m = (4 × 91 + 1 × 15 + 4 × 16 + 1 × 15) × 1/16 = 29 m y = (4 × 37 + 1 × 15 + 4 × 196 + 1 × 15) × 1/16 = 105 Next, the above-mentioned average value m _c ,
m _m, m _y and eight predicted mean value M _c shown in Table 4 based on the weighting coefficient 6/16 of the pixel of interest, M _m, M _y are obtained.

[0018]

[Table 4]

As an example, when the target pixel is predicted to be cyan, the following equation is obtained from the data in Table 2, and similarly, the prediction data in Table 4 is obtained. And _{M c = m c + 206 ×} 6/16 = 135 M m = m m + 91 × 6/16 = 63 M y = m y + 37 × 6/16 = 119, the selecting requantization unit 62, the input data (accurate Is compared with the eight kinds of data shown in Table 4. The comparison compares the input data to I _c ,
When I _m and I _y are set, the distance △ d between the eight types of predicted average values and the input data is obtained based on the following equation, and the requantized color exhibiting the minimum value is obtained.

Δd = (I _c −M _c ) ² + (I _m −M _m ) ² + (I _y −M _y ) ² where I _c = 81, I _m = 100, and I _y = 140. If so, obviously that of magenta will be minimal, thus requantizing the pixel of interest to magenta. by the way,
The predicted mean value and the input data of magenta has a difference of finite, the difference E _c, E _m, E _y is outputted to the distributor 634 as a requantization error. In the above case, the following equation is obtained.

E _c = 81−79 = 2 E _m = 100−112 = −2 E _y = 140−134 = 6 This requantization error is divided into two by the divider 634, and one is input to the line delay memory 630. Is delayed by one line, and the other is read out from the same memory 630. That is, after the error generated one line before is added to the adder 631, the next input data is input by the F / F 632. After synchronization with the timing, the next pixel data is corrected.
It goes without saying that the above-described error correction unit 63 performs processing for each of the colors cyan, magenta, and yellow.

By sequentially executing the above series of processing for each input pixel data, requantization of all image data is completed. [Modification of Requantization Unit] Next, a case where the requantization unit 6 is implemented by an error diffusion method will be described in detail with reference to FIG.

As shown in FIG. 5, the selective requantization unit 162
Input the input cmy data after requantization error correction described later and compare the input cmy data with the recording characteristic data shown in Table 2 inputted from the recording characteristic data memory 8 shown in FIG. Select from 8 types. For example, as described above, the input data I _c = 81, I _m =
If the 100, I _y = 140, if the pixel of interest predicted cyan and requantization, the distance between the cyan △ d is ^{△ d = (206-81) 2 +} (91-100) 2 + (37- 140) ² = 26315 Similarly, a comparison is made with the prediction of the other seven types, and it is determined that the distance of Red is the minimum. The requantization result is decoded by the recording signal conversion unit 64 and output to the recording device as CMYK binary data in the same manner as described above.

On the other hand, the requantization errors are input as follows to the error distribution units 163 to 165, and are distributed to the four adjacent pixels at the distribution ratio shown in FIG. Error memories 166 to 168
Is stored in E _c = 81−60 = 21 E _m = 100−219 = −119 E _y = 140−190 = −50 Here, for the next pixel, the distribution error and the previously distributed error are read out from the memory and integrated. Later, adder 1
In steps 70 to 173, the input image data is corrected.

By performing the above processing for each pixel,
As in the above-described example, requantization having a color reproduction characteristic that is faithful to the color of the input image can be performed. [Gamut Restriction] In the above-described processing, when the input image data exceeds the color reproduction area due to the recording characteristics, for example, I _c
= I _m = I _y = 255 When the data is continuously input, the predicted average value always shows a value smaller than that, so that the generated requantization error is always added to the input data as a positive value. . As a result, the requantization error becomes a larger positive value, and the processing diverges. Therefore, the gamut restriction unit 5 in the present embodiment is configured for the purpose of preventing processing from diverging.

FIG. 5 is a diagram showing the configuration of the gamut limiting section 5 in the present embodiment. In FIG. 5, RAMs 50 to 52 provided for each color are provided with a so-called look-up table (L) prepared in advance based on recording characteristics (Table 2).
UT), and the data is converted according to the following equation. Taking cyan as an example, when C ′ ≧ Cmax, C = Cmax, when C ′ ≦ Cmin, C = Cmin, otherwise C = C ′, where Cmax and Cmin are the maximum values 210 of the cyan data in Table 2, respectively. And the minimum value is 15. The same applies to other magenta and yellow.

[Modification of Gamut Limitation] In the above embodiment, data exceeding the reproduction color space is clamped by Cmax and Cmin. May be mapped. C = Cmin + (Cmax−Cmin) / 255 × C ′ Further, as a non-linear conversion, an embodiment using various algorithms such as the following equation can be easily realized using FIG.

C = f (Cmin, Cmax, C ') Although the calculation is performed independently for each color, in order to perform the calculation more accurately, cmy3 obtained from the eight kinds of data shown in Table 2 is used.
With respect to a solid connecting eight points in the dimensional space, a point outside the solid may be detected and mapped to the closest surface of the solid. Specifically, a RAM for inputting c'm'y '24-bit data to an address terminal is used, and its RA
It can be realized by performing conversion based on the look-up table data in M.

[Storing of recording characteristic data] As described above, according to this embodiment, recording is performed by requantizing while correcting the error based on the tint data recorded by the actual recording device 7. It is possible to easily cope with a change in the characteristics of the device. In other words, in the case of requantization to binary, black and white are used for the six colors of the combination of cyan, magenta, and yellow, where white is the color data of the recording paper to be used and is recorded as a color pattern. This can be realized by reading the pattern with a sensor and storing it in the data memory 8.

[0030]

Other Embodiments In the above-described embodiment, recording characteristics data of a single color of a black recording material was used for black recording. However, in order to further improve the color reproduction of input image data, K _c and K _c by K and C were used. Three kinds of different color data of K _y by K and Y and K _m by K and M are added, and 1
It may be requantized to one color. Further, even if black data Kcmy by CMY is added and requantized to 12 colors, color reproduction is further improved. In this case, decoding into a recording signal is based on Table 5.

[0031]

[Table 5]

Although the above-described embodiment has been described in connection with the example of requantization into binary values, the present invention can be similarly applied to a case where recording in each color in three to sixteen values is possible. That is, FIG.
In order to extend the embodiment of the present invention to three values, the sum of the weighting factors at the time of the average value calculation is set to 1 to 1/2, and the requantization level is selected from each of the colors 0, 1, and 2, respectively. There are 27 types of combinations, and the prediction of the pixel of interest may be selected from among the 27 types. As in the present embodiment, by increasing the number of requantization levels with a larger number of multi-valued levels, more accurate requantization can be performed on the input image in order to further reduce the requantization error.

The present invention may be applied to a system constituted by a plurality of devices, or may be applied to an apparatus constituted by a single device. Needless to say, the present invention can also be applied to a case where the above is achieved by supplying a program to a system or an apparatus.

[0034]

According to the present invention as described above, according to the present invention, the serial
Out of multiple sets of color data that can be represented by
Color data whose color space distance is closest to the color image data of the elephant
Since requantization is performed by selecting, requantization processing that is faithful to the input color image can be performed . Furthermore, the present invention
According to, input color image data can be represented by a recording device
By restricting according to various color characteristics, requantization error
The divergence of the re-quantization process can be prevented by.

According to the reproducible color characteristics of the recording apparatus,
By controlling the input image data, the divergence of the requantization process can be prevented.

[Brief description of the drawings]

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

FIG. 2 is a block diagram illustrating a configuration of a requantization unit according to the embodiment.

FIG. 3 is a diagram illustrating a detailed configuration of a requantization unit according to the embodiment.

4A is a diagram illustrating a position of a pixel adjacent to a target pixel, and FIG. 4B is a diagram illustrating weights for obtaining an average value of the target pixel.

FIG. 5 is a diagram illustrating a configuration of a gamut limiting unit according to the present embodiment.

FIG. 6 is a diagram illustrating a configuration when a requantization unit is implemented by an error diffusion method.

──────────────────────────────────────────────────続 き Continued on the front page (58) Field surveyed (Int.Cl. ⁷ , DB name) H04N 1/40-1/409 H04N 1/46-1/62 B41J 2/525

Claims (2)

(57) [Claims] An input unit for inputting color image data and a divergence of requantization processing due to a requantization error are prevented.
The color image data input by said input means and limiting means for limiting, depending on the color characteristics of the recording apparatus, from among a plurality of sets of color data that can be represented of the recording apparatus,
The color image data limited by the limiting means
Requantization means for requantizing by selecting color data having a short color space distance, and correcting means for adding and correcting a requantization error generated at the time of the requantization processing. An image processing apparatus characterized by the above-mentioned. 2. The re-quantization unit includes: a calculating unit that calculates a plurality of weighted average values of a pixel of interest according to a recording characteristic of the recording device; 2. The image processing apparatus according to claim 1, further comprising a selection requantization unit that selects a weighted average value closest to the color image data and requantizes the selected weighted average value.