JP3809274B2 - Image processing apparatus and method - Google Patents

Description

[0001]
BACKGROUND OF THE INVENTION
The present invention relates to an image processing apparatus and method for gradation-converting input multi-valued image data and outputting it.
[0002]
[Prior art]
Conventionally, an error diffusion method (hereinafter referred to as “ED”), an average density storage method (hereinafter referred to as “MD”), and the like are generally known as image processing methods for performing halftone expression. These are intended to express a halftone in a macro manner by performing area gradation expression using a small number of gradations.
[0003]
However, since these processes are performed on the input image (8 bits), the processing load is large. For this reason, US Pat. Nos. 5,394,250 and USP 5,436,736 propose a method for reducing the processing load by converting 8 bits of an input image into 4 bits by preprocessing.
[0004]
[Problems to be solved by the invention]
However, even though the above-mentioned proposal can reduce the processing load, it has not been possible to improve the unique texture that causes a problem in a specific density region when processed by ED or MD.
[0005]
Therefore, as shown in FIG. 1, there has been proposed a technique for improving the texture by adding a predetermined random number to the input image before the t-value conversion process. Details are described below.
[0006]
In the figure, reference numeral 101 denotes a random number generation unit, which is a processing unit that generates a random number R. FIG. 2 is a block diagram illustrating a configuration of the random number generation unit 101. FIG. 3 shows random number generation in the program language C. Here, it demonstrates using FIG. 3 on the relationship of description.
[0007]
First, in initialization, “0” is written in the register of p [ii]: (0 ≦ ii ≦ 25), and “1” is set only in the register of p [12]. Then, before outputting the random number value, the following calculation is performed after calculating p [0] = (p [25] ^ p [24] ^ p [23] ^ p [22] & 1) for each pixel. To generate random values of -17 to 17.
[0008]
Random number = (1-2 * p [22]) * (((p [15] * 64 + p [16] * 32 + p [17] * 16 + p [18] * 8 + p [19] * 4 + p [20] * 2 + p [21] ) * 17) / 128)
Here, the reason why random numbers of ± 17 or more are generated and finally divided by 128 is to eliminate the bias in the random number generation rate.
[0009]
In the above formula, random numbers of -17 to 17 are generated, but the same effect can be obtained by changing the random number generator to generate random values of -15 to 15 as follows. Needless to say.
[0010]
Random number = (1-2 * p [2]) * (p [18] * 8 + p [19] * 4 + p [20] * 2 + p [21]
This random value tends to increase the texture improvement effect when the absolute value of the random value is increased and decrease the texture improvement effect when the absolute value is decreased.
[0011]
However, it goes without saying that if the random number is too large, the image becomes rougher than the texture improvement effect, leading to a reduction in image quality. An absolute value of about 7 to 17 is practical.
[0012]
Returning to FIG. 1, the random number value output from the random number generation unit 101 is input to the sign inversion and data holding unit 102 and the selector 103.
[0013]
In the sign inversion and data holding unit 102, the sign of the input random number value is inverted once, and “p × X + p / 2” (p ≧ 2 is an arbitrary even value, X is an address value in the main scanning direction) between pixels. The random number value is held and then output.
[0014]
On the other hand, the selector 103 is configured to switch the output of the input random number value and the value of the sign inversion and data holding unit 102 according to the image position signal.
[0015]
Here, the pixel position signal mentioned above means that the value of the random number generator 101 is output for each pixel of “p × X” (p ≧ 2 is an even even value, X: address value in the main scanning direction), and “ This is a control signal for outputting the value of the sign inversion and data holding unit 102 for each pixel of p × X + p / 2 ″, and is generated from the Hsync signal. At other pixel positions, a value of “0” is output.
[0016]
When the input multilevel signal D is other than “0” or “255”, the adding unit 104 adds the random number generated by the above processing to the input multilevel signal D. At this time, although not shown, the limiter is applied with a minimum of 0 and a maximum of 255.
[0017]
Next, the division unit 105 divides the input image signal by “17” and separates the quotient from the remainder. Here, the quotient (0 to 15) is input to the adder 107, and the remainder (0 to 16) is input to the comparator 106.
[0018]
In addition, the random number generation unit 109 is configured to output a positive random number value of 0 to 16 generated by a method basically similar to the random number generation unit 101 described above. The details thereof are the same as those of the random number generation unit 101, and thus the description thereof is omitted. FIG. 4 shows the random number generation of the random number generation unit 109 in the programming language C.
[0019]
Next, the comparator 106 compares the random number value (0 to 16) input from the random number generation unit 109 with the remainder value (0 to 16) input from the division unit 105, and the remainder is more than the random value. A value “1” is output only when the value is large, and “0” is output otherwise. The output value is added to the quotient value (0 to 15) from the division unit 105 by the addition unit 107, and a 4-bit signal is output to a t-value conversion processing unit described later.
[0020]
After the input signal is converted into a 4-bit signal by the above processing, t (t ≦ 4) value processing is performed by the t value processing unit 108 and output.
[0021]
However, in the case of the method shown in FIG. 1 described above, the addition unit 104 and the addition unit 107 add random numbers to the input image twice, which not only increases the hardware scale but also reduces the image quality. There was also a problem of being connected.
[0022]
The present invention was made to solve the above problems, and while simplifying the hardware, Multi-value image data of High-quality gradation conversion processing To do For the purpose.
[0023]
[Means for Solving the Problems]
In order to achieve the above object, according to the present invention, in an image processing apparatus that outputs gradation-converted input multi-valued image data, a random number generation unit that generates a random value and the random number generation unit Random value control means for controlling the fluctuation range of the random number value to be equal to or greater than a predetermined value, and controlling the fluctuation range of the random value according to the pixel value of the image data, and the random number for each pixel value of the image data An addition means for adding random numbers controlled by the control means, and an addition result obtained by the addition means is divided by a predetermined division constant. Of the results quotient only Gradation conversion means for performing gradation conversion using the predetermined value, and the predetermined value is obtained from the division constant. 1 It is characterized by a small value.
[0024]
In order to achieve the above object, the present invention provides an image processing method for performing gradation conversion on input multi-valued image data and outputting it, and a random number generation step for generating a random value and the random number generation step. A random number control step for controlling the fluctuation range of the random number value to be equal to or greater than a predetermined value, and controlling the fluctuation range of the random number value according to the pixel value of the image data, and the pixel value of the image data. An addition step for adding the random number values controlled in the random number control step, and the addition result in the addition step is divided by a predetermined division constant. Of the results quotient only A gradation conversion step of performing gradation conversion using the above-mentioned, and the predetermined value is obtained from the division constant 1 It is characterized by a small value.
[0025]
DETAILED DESCRIPTION OF THE INVENTION
Hereinafter, embodiments according to the present invention will be described in detail with reference to the drawings. In this embodiment, a case where the present invention is applied to a binarization process of a color copying machine will be described as an example.
[0026]
● Process outline
FIG. 5 is a block diagram illustrating a schematic configuration of the color copying machine according to the embodiment. In the figure, reference numeral 509 denotes an image reading unit, which includes a lens 501, a CCD sensor 502, and an analog signal processing unit 503. Here, the image information of the original 500 formed on the CCD sensor 502 through the lens 501 is photoelectrically converted into analog electric signals of R (Red), G (Green), and B (Blue) by the CCD sensor 502. . The converted image signal is input to the analog signal processing unit 503, and is subjected to analog / digital (A / D) conversion after being sampled and held, corrected for dark level, and the like for each color of R, G, B. The The digitally converted full-color image signal is input to the image processing unit 504.
[0027]
The image processing unit 504 performs correction processing necessary for the image reading system such as shading correction, color correction, and wrinkle correction, smoothing processing, edge enhancement, other processing, processing, and the like, and outputs the result to the printer unit 505. .
[0028]
The printer unit 505 includes an exposure control unit (not shown) composed of a laser and the like, an image forming unit (not shown), a transfer paper conveyance control unit (not shown), and the like, and is transferred by an input image signal. Record an image on paper.
[0029]
A CPU circuit unit 510 includes a CPU 506, a ROM 507, a RAM 508, and the like, and controls the image reading unit 509, the image processing unit 504, the printer unit 505, and the like, and comprehensively controls the sequence of the apparatus.
[0030]
● Image processing section
Next, the above-described image processing unit 504 will be described in detail. FIG. 6 is a block diagram illustrating a configuration of the image processing unit 504 in the embodiment. In the figure, 601 is a shading correction unit, 602 is a gradation correction unit, 603 is a color / monochrome conversion unit, and 604 is a gradation conversion processing unit.
[0031]
In the above configuration, first, a digital image signal output from the analog signal processing unit 503 is input to the shading correction unit 601. A shading correction unit 601 corrects variations in sensors for reading a document and light distribution characteristics of a document illumination lamp. Next, the corrected image signal is input to the gradation correction unit 602 in order to convert the luminance signal into density data, and density image data is created. The image signal converted into density data is input to the color / monochrome conversion unit 603 and output as monochrome data. The data output from the color / monochrome conversion unit 603 is input to the gradation conversion processing unit 604, and error diffusion processing (ED processing) or average density storage processing (MD processing) is performed as a pseudo halftone expression.
[0032]
Next, the gradation conversion processing unit 604 according to the present invention will be described in detail.
[0033]
● Tone conversion processor
FIG. 7 is a block diagram illustrating a detailed configuration of the gradation conversion processing unit 604 in the embodiment. In the embodiment, a binary MD method enabling texture control will be described as an example.
[0034]
A random number (to be described later) is added to the image signal D from the color / monochrome conversion unit 603, and a signal DR ′ subjected to division processing by a constant “17” (to be described later) and error data E generated by the binarization processing are included. The error is input to the error correction unit 702. Then, error correction, which will be described later, is performed and output to the binarization unit 701 as an image signal DE.
[0035]
The binarization unit 701 inputs an error-corrected image signal DE, a binarized slice value S described later, and an average density value m described later, and compares the image signal DE with the binarized slice value S. As a result, a binary output N is obtained. Also, the binarization error data E is calculated by subtracting the image signal DE and the average density value m.
[0036]
A binarization result delay unit 703 inputs a binarized binary output N, performs a delay of a predetermined number of lines, and uses the delayed data as a plurality of lines binarization results Nmn and B * ij and an average density The data is sent to the calculation unit 704 and the threshold value calculation unit 705.
[0037]
The average density calculation unit 704 inputs the delayed multiple line binarization result Nmn, calculates a mean density value m by performing a product-sum operation with a preset coefficient, and adds an addition unit 706 and a binarization unit The average density value m is output to 701.
[0038]
The threshold value calculation unit 705 inputs the multi-line binarization result B * ij of the above-described binarization result delay unit 703, the input multivalue data D, and the output T of the hysteresis control amount calculation unit 708, A threshold control amount in an arbitrary area is calculated according to the B * ij signal that is a past binarization state (pattern), and is sent to the adder 706 as a binarized slice value S ′.
[0039]
The addition unit 706 receives signals of the average density value m of the average density calculation unit 704 and the binarized slice value S ′ of the threshold value calculation unit 705, performs addition processing, and binarizes the result. The slice value is output to the binarization unit 701.
[0040]
The random number generation unit 710 generates an m-sequence random number R of “−17 to 17” by a method described later, and outputs it to the selector 712 and the sign inversion and data holding unit 711.
[0041]
The sign inversion and data holding unit 711 performs code inversion of the random number R input from the random number generation unit 710, holds data only between certain pixels described later, and then outputs the held random number to the selector 712.
[0042]
The selector 712 switches between the random number R input from the random number generator 710 and the stored random number from the sign inversion and data holding unit 711 based on a pixel position signal at a timing described later.
[0043]
The addition amount control unit 713 controls the random number output value using a method described later according to the value of the image signal D.
[0044]
The addition unit 707 performs addition processing between the input image signal D and the addition amount control unit 713. The hysteresis control amount calculation unit 708 calculates a hysteresis control amount by a method described later in accordance with a signal from the addition unit 707, and outputs the hysteresis control amount to the threshold value calculation unit 705. The division unit 709 divides the input image signal DR by the constant 17 and outputs only the quotient. At this time, all the remainder is rounded down.
[0045]
With the above configuration, the gradation conversion processing unit 604 performs binarization processing.
[0046]
Next, each processing unit of the gradation conversion processing unit 604 will be described in detail. First, the random number generation unit 710 generates a random number with the same configuration as in FIG.
[0047]
First, in initialization, “0” is written in the register of p [ii]: (0 ≦ ii ≦ 25), and “1” is set only in the register of p [12]. Then, before outputting the random number value, the following calculation is performed after calculating p [0] = (p [25] ^ p [24] ^ p [23] ^ p [22] & 1) for each pixel. To generate random values of -17 to 17.
[0048]
Random number = (1-2 * p [22]) * (((p [15] * 64 + p [16] * 32 + p [17] * 16 + p [18] * 8 + p [19] * 4 + p [20] * 2 + p [21] * 17/128)
In the embodiment, random numbers of −17 to 17 are used, but the random number generation unit may be changed to generate random values of −15 to 15 by the following calculation.
[0049]
Random number = (1-2 * p [2]) * (p [18] * 8 + p [19] * 4 + p [20] * 2 + p [21])
Here, what is important is that the maximum value of generated random numbers (17 in the embodiment) needs to be equal to or more than half of the number (17 in the embodiment) to be divided by a dividing unit 709 described later (fractional part rounded down). Is that there is.
[0050]
In the embodiment, since the number to be divided by the division unit 706 is 17, 17/2 = 8 (fractional part rounding down), and the maximum random number generation value of the random number generation unit 710 needs to be set to a value of 8 or more. There will be (in the embodiment, it is set to 17 of 8 or more). If the number to be divided by the division unit 706 is 7, 7/2 = 3 (decimal number is rounded down), and the maximum random number generation value of the random number generation means 310 needs to be 3 or more. Needless to say.
[0051]
In this way, random number generation is performed for all pixels.
[0052]
Next, the random number inversion and data holding unit 711 uses only the sign of the random number value of the random number generation unit 710 generated at the pixel position “p × X” (an even number of p ≧ 2 and X: an address value in the main scanning direction). Inverted and held for “p / 2” pixels, then the output configuration. For example, when the value of p is “2”, the pixel position “p × X”, that is, the random value generated at the pixel position “0, 2, 4, 6, 8, 10, 12, 14,... Are temporarily stored, and the sign of the random value held at the pixel positions “1, 3, 5, 7, 9, 11, 13, 15,...” Is inverted and output. Of course, it is not necessary to keep the random number values of all the pixels, and a configuration of refreshing pixel by pixel is sufficient.
[0053]
On the other hand, the selector 712 is configured to switch and output the random number value of the random number generation unit 710 generated for each pixel and the random number value from the sign inversion and data holding unit 711 according to the pixel position signal.
[0054]
This pixel position signal selects a random value from the sign inversion and data holding unit 711 only when the pixel position is “p × X + p / 2” (where p ≧ 2 is an even number, X is an address value in the main scanning direction). In all other cases, the random number value from the random number generator 710 is selected.
[0055]
When the large random number value in the random number generation unit 710 described above is larger than ½ of the number (17 in the embodiment) divided by the division unit 709 described later (17 in the embodiment), the addition amount control unit 713 An important point is a configuration that performs output control according to the input multilevel signal D only for a large random number.
[0056]
FIG. 8 shows the addition amount control of the addition amount control unit 713 in the program language C. Here, what is important is a method for setting the constant SL in which the output RD of the selector 712 is divided by the constant SL.
[0057]
The constant SL is determined so that the result of RD / SL is ½ of the number divided by the division unit 709. That is, in the embodiment, since the number divided by the division unit 709 is 17, 17/2 = 8 (fractional part round down), and the SL value is calculated from RD / SL = 8, 17 / SL = 8 (fractional part round down). It must be set to “2”.
[0058]
When the input multilevel signal D is N1 (for example, 16) or less, the minimum necessary random number is added by the calculation of “P1 = RD / SL”. Here, the minimum necessary random number means that the amplitude of the random number is set to “−8 to 8” because the division unit 709 divides by “17”. That is, assuming that the random number fluctuation is α (16 here), the number divided by the division unit 709 is (α + 1) (17 here).
[0059]
When the input multilevel signal D is greater than N1 and less than or equal to N2 (for example, 32), the calculation of “P1 = (RD−RD / SL) * (D−N1) / (N2−N1) + RD / SL”. Thus, a random number whose amplitude is controlled is added. The point here is that the amplitude is controlled only for the portion exceeding the minimum required random number. That part is the “(RD− R D / SL) * (D−N1) / (N2−N1) ”.
[0060]
Similarly, when the input multilevel signal D is N3 (for example, 201) or more and smaller than N4 (for example, 233), “P1 = (RD−RD / SL) * (N4−D) / (N4−N3) + RD”. The random number whose amplitude is controlled is added in the same manner as the above-described process by the calculation of / SL ". At this time, the portion whose amplitude is controlled with a random number more than necessary is similarly “(RD−RD / SL) * (N4−D) / (N4−N3)”.
[0061]
When the input multilevel signal D is N4 or more, only the minimum necessary random number is added by the calculation of “P1 = RD / SL”. Furthermore, when the input multilevel signal D is out of the above range, all the input random numbers RD are output from the addition amount control unit 713 as the random number P1.
[0062]
The adding unit 707 performs a process of adding the random number P1, the input multilevel signal D, and the constant 8 described above. The addition of the constant 8 is also an important point here. This is because the constant that is divided by the division unit 709 described later is “17”, and the remainder of division is 16 at the maximum, so the amplitude of the random number to be added needs to be an even number of 16 or more. A constant 8 is obtained from the calculation. This is added as a bias component.
[0063]
Of course, if the number divided by the dividing unit 709 is “5”, the constant added by the adding unit 707 is “2”. Although not shown, a limiter is applied so that the addition result falls within the range of “0” and “255”. The signal from the adder 707 is input to the divider 709 and the hysteresis control amount calculator 708.
[0064]
The division unit 709 performs an operation of dividing by the constant 17 as already described above. At this time, the output signal is only the quotient obtained by the division, and all the remainders are rounded down. In other words, in the embodiment, a comparator for comparing “remainder after division” and “random number” used in the conventional example is not required, and the process of converting to an 8-bit signal is possible only by the quotient of the division process. Needless to say, the 4-bit image quality is higher than that of the conventional example. The output signal DR ′ from the division unit 709 is input to an error correction unit 702, which will be described later, and error correction processing is performed.
[0065]
Next, a binarization method for performing texture control will be described. As described above, the error correction unit 702 receives the image signal DR and the binarized error data E, calculates the image signal DE obtained by performing error correction on the image signal DR ′, and outputs the image signal DE to the binarization unit 701. The output is configured as shown in FIG.
[0066]
The input binarization error data E is halved by the division circuit 901. The result is branched into two systems, one of which is input to the subtraction circuit 902 and the other is input to the line buffer 903. The subtraction circuit 902 calculates a difference EB (= EE−E / 2) between the binarization error data E and E / 2, and inputs the result to the addition circuit 904. At this time, although not shown, the possible value of the binarization error data E is set to “−6 to +6” by the limiter process.
[0067]
The adder circuit 904 calculates the sum of the EA delayed by one line by the line buffer 903 for one bit of a plurality of bits (3 bits in the embodiment) and the EB from the subtractor circuit, and outputs the sum to the adder circuit 905. . The addition circuit 905 calculates the sum of the addition result EA + EB and the image signal DR ′, and outputs it as the image signal DE. That is, in the error correction unit 702, as shown in FIG. 10, the binarization error EA when the pixel A on one line is binarized with respect to the pixel of interest “*” and the pixel B one pixel before are displayed. A process of adding the value of the binarization error EB when binarized to the value of the target pixel is performed.
[0068]
Next, the binarization unit 701 inputs the image signal DE described above, a binarized slice value S described later, and an average density calculated value m described later, and compares them to obtain a binary output N. And binarization error data E are output as shown in FIG.
[0069]
The input image signal DE is branched into two systems, one of which is input to the comparison circuit 1101 and the other is input to the subtraction circuit 1102. The comparison circuit 1101 compares the image signal DE with the binarized slice value S and outputs a binary output N as follows.
[0070]
When DE> S, N = 1
N = 0 when DE ≦ S
Further, the subtracting circuit 1102 subtracts the value of the image signal DE from the average density calculation value m and outputs the result as binarized error data E.
[0071]
E = m-DE
At this time, as described above, although not shown, the limiter process is performed so that the value of E falls within the range of “−6 to +6”.
[0072]
Next, the binarization result delay unit 703 inputs the binary output N from the binarization unit 701, performs a delay of a predetermined number of lines, and calculates the average density as a plurality of line binarization results Nmn, B * ij. Data is sent to the calculation unit 704 and the threshold value calculation unit 705, and is configured as shown in FIG.
[0073]
First, the input binary output N is sent from the line buffer 1201 for one bit to one line to the line buffer 1202, and the data is delayed for each line. At the same time, a delay of one pixel is sequentially performed by a delay 1208 from a delay 1203 including a delay circuit for one pixel. Then, the output of the delay 1206 and the output of the delay 1207 are output as N14 and N15, respectively.
[0074]
The binarized data delayed by one line by the line buffer 1201 is delayed by delays 1209 to 1214, and outputs of delays 1209 to 1213 are output as N21 to N25. The binarized data further delayed by one line by the line buffer 1202 is delayed by delay 1215 to delay 1220, and the outputs of delay 1215 to delay 1219 are output as N31 to N35.
[0075]
At the same time, outputs from delay 1206 to delay 1208 are output as B10, B20, and B30, respectively. The binarized data delayed by one line by the line buffer 1201 is output as B32 to B02 and Bi12 to Bi32 after being delayed. Further, the binarized data delayed by one line by the line buffer 1202 is output as B31 to B01 and Bi11 to Bi31 after being delayed.
[0076]
In other words, the average density calculation unit 704 is subjected to delay processing of a plurality of lines and a plurality of pixels of data obtained by binarizing a two-dimensional image, and a plurality of lines binarization result Nmn is as shown in FIG. This is input to the average density calculation unit 704.
[0077]
Next, the average density calculation unit 704 inputs the multi-line binarization result Nmn, performs a product-sum operation from a preset coefficient and the delayed binary result, and performs the binarization unit 701 and the addition unit. The data m used in 706 is output, and is configured as shown in FIG.
[0078]
That is, the multiplication circuit 1401 inputs the binarized data N15 and the coefficient M15, and outputs the multiplication result of both. The multiplication circuit 1402 receives the binarized data N14 and the coefficient M14, and outputs the multiplication result of both. Similarly, the above calculation is performed by each of the multiplication circuit 1403 to the multiplication circuit 1412, and all the multiplication results are added by the addition circuit 1413. The result is output as an average density calculation value m. FIG. 15 is a diagram illustrating an example of coefficients when the average density calculation process is performed.
[0079]
Next, the hysteresis control amount calculation unit 708 changes the value of the constant ALF (= 32) according to the input signal DR and outputs it as the S ′ signal. This is for adjusting the hysteresis amount in an arbitrary density region. That is, this enables texture control in an arbitrary density region.
[0080]
FIG. 16 shows the calculation process of the hysteresis control amount in the program language C. When the input signal DR is less than or equal to the constant LR1 (= 16), processing is performed to set ll to “0”, and the input signal DR is greater than the constant LR1 and less than or equal to the constant LR2 (= 48). In this case, ll is obtained by the following equation.
[0081]
ll = ((DR-LR1) * (ALF * 256 / (LR2-LR1))) / 256;
By this calculation, the value of ll gradually approaches 0 to the constant ALF (= 32) as the value of the input signal DR increases from the constant LR1 to the constant LR2.
[0082]
On the other hand, when the input signal DR is larger than the constant LR2 and equal to or smaller than the constant LR3 (= 233), 11 is output as a constant constant ALF. When the input signal DR is larger than the constant LR3 and equal to or smaller than the constant LR4 (= 255), ll is obtained by the following equation.
[0083]
ll = ALF-((DR-LR3) * (ALF * 256 / (LR4-LR3))) / 256;
This indicates that the output 11 gradually approaches 0 from the constant ALF as the value of the input signal DR increases from LR3 to the constant LR4. Further, when the input signal DR is larger than LR4, a process for setting 11 to 0 is performed.
[0084]
After the above processing, the value obtained by subtracting the constant ALFm (= 16) from ll is output as the output signal T. The purpose of this subtraction is to change the signal T of the hysteresis control amount calculation unit 708 from a negative value to a positive value. This makes it possible to control the texture in an arbitrary density region within a wide latitude range.
[0085]
Next, the threshold value calculation unit 705 will be described. FIG. 17 shows the threshold value calculation process in the program language C.
[0086]
First, the threshold value calculation unit 705 converts the values of the input signal T of the hysteresis control amount calculation unit 708 into constants LT1 (= 2), LT2 (= 4), LT3 (= 8), and LT4 (= 16, respectively. ) To obtain variables A (= T / LT1), B (= T / LT2), (C (= T / LT3), D (= T / LT4) used internally.
[0087]
Next, the value of the binarized slice value S ′ is changed to variables A, B, and B according to the binarization result arrangement state (pattern) of the output B ′ * ij from the binarization result delay unit 703 by a method described later. Control by C, D and constants. FIG. 18 is a diagram illustrating a binarization result arrangement state (pattern). In this example, the pixel immediately before the target pixel is not referenced for high-speed processing. Of course, when a sufficiently high-speed logic can be built, it goes without saying that there is no problem even if the pixel immediately before the target pixel is referred to.
[0088]
Next, processing for controlling the binarized slice value S according to the binarization result arrangement (pattern) will be described.
[0089]
When the binarization state around the pixel of interest is as follows, the binarized slice value S is forcibly set to a constant 15 of max and output. This is to make it difficult to force dots.
[0090]
B32 == 0 && B22 == 1 && B12 == 0 && B21 == 0 && B11 == 1 && B01 == 0 or
Bi12 = 0 && Bi22 == 1 && Bi32 == 0 && B01 == 0 && Bi11 == 1 && Bi21 == 0
Further, even when the binarization situation around the pixel of interest is the following and the input value data D is less than 31 (31 out of 0 to 255), the binarized slice value S is forcibly set to a constant of max. 15 is output. This is also for making it difficult to forcibly hit dots under the above conditions.
[0091]
B12 == 0 && B02 == 0 && Bi12 == 0 && Bi22 == 0 && Bi32 == 0 &&
B11 == 0 && B01 == 0 && Bi11 == 1 && Bi21 == 0 && Bi31 == 0 && B20 == 0
On the other hand, when the input multivalued data D is 31 (31 out of 0 to 255) or more under the above conditions, the binarized slice value S is set to the average density calculated value m and output is performed. This is to prevent the texture control from being performed when the past binarization result has a specific arrangement (pattern). Of course, the constant 31 is not a fixed value but a parameter, and can be set to another value such as 48 or 64.
[0092]
At this time, it goes without saying that if the value of 31 is increased, texture control is more likely to be actively applied. Conversely, if the value is decreased, texture control is less likely to be applied.
[0093]
When the binarization situation around the pixel of interest is as follows, the binarized slice value S is set to a value obtained by subtracting the variable A from the average density calculated value m (S = m−A) and output. .
[0094]
B02 == 0 && Bi12 == 0 && B11 == 0 && B01 == 1 && Bi11 == 1 && Bi21 == 0 && B20 == 0
This is to make it easier to forcibly hit dots under the above conditions. Also at this time, the processing is performed without referring to the binarization result immediately before the target pixel.
[0095]
Similarly, the binarized slice value S is binarized using the internal variables A, B, C, D and constants without referring to the result immediately before the target pixel, according to each binarization result pattern. The slice value S ′ is controlled. As a result, when the hysteresis control amount calculation value T is positive, control is performed so that the dot is easily hit, and when the hysteresis control amount calculation value T is negative, control is performed so that the dot is not easily hit.
[0096]
When the above processing is sequentially performed for each pixel, the output value B ′ * ij of the binarization result delay unit is set to an arbitrary density region according to the hysteresis control amount calculation value T. Accordingly, it is possible to control the texture to an arbitrary shape.
[0097]
In the embodiment, control is performed so that the texture becomes a 2 × 2 pixel unit. This makes it possible to form an image in which an arbitrary number of dots are collected and stabilized in an area where one pixel is not stable due to the characteristics of the printer.
[0098]
The binarized slice value S ′ obtained in this way is input to the adding unit 706 together with the output m of the average density calculating unit 704 to be added. At this time, when the signal of S ′ is 15, the binarized slice value S is output as 15, and otherwise, the calculation of S = S ′ + m is performed and output. FIG. 19 shows the above calculation in the program language C.
[0099]
After the binarized slice value S is obtained by the above addition process, the binarization unit 701 performs the binarization process, and the binary signal is output from the gradation conversion processing unit 604, and the printer The unit 505 is configured to print out.
[0100]
[Modification]
Next, a modification of the above-described gradation conversion processing unit will be described. In the modification, the configuration around the random number generator shown in FIG. 7 is simplified.
[0101]
FIG. 20 is a block diagram illustrating a detailed configuration of the gradation conversion processing unit in the modification. The same components as those shown in FIG.
[0102]
In FIG. 20, 2001 is a random number generator, which generates positive random numbers from 0 to 16. The specific configuration is the same as the configuration shown in FIG. That is, in initialization, “0” is written in the register of p [ii]: (0 ≦ ii ≦ 25), and “1” is set only in the register of p [12]. And before outputting random values, every pixel
p [0] = (p [25] ^ p [24] ^ p [23] ^ p [22] & 1)
After the above calculation is performed, random numbers of 0 to 16 are generated by the following calculation.
Random number = ((p [15] * 64 + p [16] * 32 + p [17] * 16 + p [18] * 8 + p [19] * 4 + p [20] * 2 + p [21] * 16) / 128)
Here, the reason why 16 or more random numbers are generated and finally divided by 128 is to eliminate the bias in the random number generation rate.
[0103]
Reference numeral 2002 denotes an adder that performs a process of adding the input random number R and the input multivalued data. A feature of the modification is that, unlike the addition unit 707 shown in FIG. 7, 1/2 of the maximum remainder value 16 divided by the division unit 709 is not added as a bias component. This is because the random number to be added takes only a positive value and does not take a negative value, so that a bias component is not necessary.
[0104]
Similarly to the configuration shown in FIG. 7, the output value from the adding unit 2002 is divided by the dividing unit 709 and only the quotient value is output. As a result, the comparator for comparing the remainder of the result of division and the random number, which has been performed in the conventional example, can be omitted, and the hardware scale can be simplified.
[0105]
Thereafter, a binarization process similar to that in the above-described embodiment is performed, and the binary signal is output from the gradation conversion processing unit 604 and printed out by the printer unit 505.
[0106]
The point in this modification is that the number divided by the division unit 709 is 17, so the maximum random number value generated by the random number generation unit 2001 is set to 16 or more (number divided by the division unit 709; 17-1). It is that you are. Of course, if the amount of random numbers added when the input multi-value data is other than “0” or “255” is increased, it is needless to say that the effect of improving the texture is increased. is there. Therefore, it is preferable to set it to 31 or less.
[0107]
In the above-described embodiment, the sign inversion and data holding unit 711 generates a random number that regularly changes to ± and adds it to the input multilevel data D. However, the present invention is not limited to this, and the sign inversion It goes without saying that the same effect can be obtained by adding random numbers of the random number generator that randomly changes to ± without using the data holding unit 711.
[0108]
Thereby, the scale of hardware can be reduced. However, random numbers that regularly change to ± shown in the embodiment have a lower low-frequency component and therefore tend to have less deterioration in image quality.
[0109]
Furthermore, in the above-described embodiment, when only the necessary minimum random number 8 (absolute value [numerical value of the division unit 709; 17/2] and the decimal part of the operation result is rounded down) is added, the addition amount control unit 713 Needless to say, can be omitted.
[0110]
When the number to be divided by the division unit 709 according to the above-described embodiment is an even number (for example, 18), the input multi-value data can be calculated by being doubled by 1-bit shift.
[0111]
This is because when dividing by 18, the maximum remainder is 17, so the random number amplitude to be added needs to be an odd number greater than or equal to 17, but the odd amplitude cannot be distributed evenly. (Because the bias component is 17/2 = 8.5 and cannot be divided). In other words, the adding unit 707 cannot set the bias component to a numerical value of 8.5.
[0112]
Therefore, the input multi-value data may be doubled for processing.
[0113]
The input multilevel data is doubled and the number divided by the division unit 709 is also doubled to 36 (18 × 2), and the bias component of the addition unit 707 is set to 17 ([numerical value of the division unit 709; 36 / 2-1] ), It is possible to divide the amplitude of random numbers to be added into equal ± 17. Thereby, even when the number to be divided by the dividing unit 709 is an even number, it can be realized with the above-described configuration.
[0114]
In the embodiment and the modification described above, binarization has been described, but the present invention is not limited to this. In other words, it can be applied to pre-processing such as quaternarization and quaternarization, and is not limited to the above-mentioned average density storage method (MD method), but is also applied to a general error diffusion method (ED method). Needless to say, you can.
[0115]
Further, it goes without saying that the present invention is applicable not only to monochrome (monochrome) processing but also to color signals.
[0116]
As described above, according to the embodiment, random number addition is performed by combining the random number addition process for improving the texture and the 8-bit → 4-bit conversion process using random numbers as a pre-process of the t-value conversion process. While reducing the amount, it is possible to improve the texture as in the conventional case, and it is possible to perform preprocessing for converting the input data from 8 bits to 4 bits.
[0117]
In addition, the hardware scale can be reduced and the image quality can be improved.
[0118]
Even if the present invention is applied to a system composed of a plurality of devices (for example, a host computer, interface device, reader, printer, etc.), a device (for example, a copier, a facsimile device, etc.) composed of a single device. You may apply to.
[0119]
Another object of the present invention is to supply a storage medium storing software program codes for realizing the functions of the above-described embodiments to a system or apparatus, and store the computer (CPU or MPU) of the system or apparatus in the storage medium. Needless to say, this can also be achieved by reading and executing the programmed program code.
[0120]
In this case, the program code itself read from the storage medium realizes the functions of the above-described embodiments, and the storage medium storing the program code constitutes the present invention.
[0121]
As a storage medium for supplying the program code, for example, a floppy disk, a hard disk, an optical disk, a magneto-optical disk, a CD-ROM, a CD-R, a magnetic tape, a nonvolatile memory card, a ROM, or the like can be used.
[0122]
Further, by executing the program code read by the computer, not only the functions of the above-described embodiments are realized, but also an OS (operating system) operating on the computer based on the instruction of the program code. It goes without saying that the case where the functions of the above-described embodiment are realized by performing part or all of the actual processing and the processing is included.
[0123]
Further, after the program code read from the storage medium is written into a memory provided in a function expansion board inserted into the computer or a function expansion unit connected to the computer, the function expansion is performed based on the instruction of the program code. It goes without saying that the CPU or the like provided in the board or the function expansion unit performs part or all of the actual processing and the functions of the above-described embodiments are realized by the processing.
[0124]
【The invention's effect】
As described above, according to the present invention, while simplifying hardware, Multi-value image data of High-quality gradation conversion processing To do it can.
[0125]
[Brief description of the drawings]
FIG. 1 is a diagram showing a configuration of a conventional example in pre-processing of t-value conversion processing.
2 is a block diagram showing a configuration of a random number generation unit 101 shown in FIG.
FIG. 3 shows random number generation in the programming language C.
FIG. 4 shows the random number generation of the random number generation unit 109 in the program language C.
FIG. 5 is a block diagram illustrating a schematic configuration of a color copying machine according to the embodiment.
6 is a block diagram showing a configuration of an image processing unit 504 shown in FIG.
7 is a block diagram showing a detailed configuration of a gradation conversion processing unit 604 shown in FIG.
FIG. 8 shows the addition amount control of the addition amount control unit 713 in the programming language C.
9 is a diagram showing a detailed configuration of an error correction unit 702. FIG.
FIG. 10 is a diagram illustrating a process of adding a binarization error to a target pixel by an error correction unit 702.
11 is a diagram showing a detailed configuration of a binarization unit 701. FIG.
12 is a diagram illustrating a detailed configuration of a binarization result delay unit 703. FIG.
FIG. 13 is a diagram illustrating a data configuration used in a binarization result delay unit 703;
14 is a diagram showing a detailed configuration of an average density calculation unit 704. FIG.
15 is a diagram showing a configuration of coefficients used in an average density calculation unit 704. FIG.
FIG. 16 shows a calculation process of a hysteresis control amount in a program language C.
FIG. 17 shows the processing of the threshold value calculation unit 705 in the program language C.
FIG. 18 is a diagram illustrating a binarization result arrangement state (pattern).
FIG. 19 shows the calculation of the binarized slice value S in the programming language C.
FIG. 20 is a block diagram illustrating a detailed configuration of a gradation conversion processing unit in a modified example.

Claims (16)

In an image processing apparatus that outputs gradation-converted input multi-valued image data,
Random number generating means for generating a random value;
Random number control means for controlling the fluctuation width of the random number value generated by the random number generation means to be equal to or greater than a predetermined value, and controlling the fluctuation width of the random number value according to the pixel value of the image data;
Adding means for adding a random value controlled by the random number control means to each pixel value of the image data;
And a gradation conversion unit that performs gradation conversion using only the quotient of the result of dividing the addition result in the adder means by a predetermined division constant, the predetermined value is one less than the division constant An image processing apparatus characterized by the above. The random number control means controls the fluctuation range of the random value generated by the random number generation means to be the predetermined value when the pixel value is a value in a low density region and a high density region. The image processing apparatus according to claim 1 . The random number control means controls the fluctuation range of the random value generated by the random number generation means to be larger than the predetermined value when the pixel value is a value in the middle density range. The image processing apparatus according to claim 1 or 2 . The random number control means divides the random value generated by the random number generation means by a constant when the pixel value is equal to or less than a first specified value N1 and when the pixel value is equal to or greater than a fourth specified value N4 (N1 <N4). The image processing apparatus according to claim 1, wherein the processed value is output. The random number control means is configured such that when the pixel value is larger than the first prescribed value N1 and not more than a second prescribed value N2 (N1 <N2 <N4) and when the pixel value is a third prescribed value N3 (N1 <N2 <N3) or more, and when smaller than the fourth specified value N4, a value corresponding to the pixel value and the specified value is obtained by dividing the random value generated by the random number generating means by the constant. The image processing apparatus according to claim 4 , wherein a value obtained by adding is output. The random number generating means, the image processing apparatus according to any one of claims 1 to 5, wherein generating a random number amplitude becomes the predetermined value or more. It said addition means, the image processing apparatus according to any one of claims 1 to 6, characterized by further adding the half of the maximum value of remainder of division by the dividing constant as a bias value. If the division constant is even, the gradation conversion means, any one of claims 1 to 7, characterized in that the gradation conversion processing to the pixel value and the dividing constant and the predetermined value is doubled The image processing apparatus according to one item. In an image processing method for gradation-converting input multi-value image data and outputting it,
A random number generation step for generating a random value;
A random number control step of controlling the random value generated in the random number generation step so that a fluctuation amount of the random value is equal to or greater than a predetermined value, and controlling a fluctuation amount of the random value according to a pixel value of the image data;
An addition step of adding the random value controlled in the random number control step to each pixel value of the image data;
And a grayscale conversion step of performing tone conversion using only the quotient of the result of dividing the addition result in the adder step at a predetermined division constant, the predetermined value is one less than the division constant An image processing method characterized by the above. In the random number control step, when the pixel value is a value in a low density region and a high density region, control is performed so that a fluctuation width of the random value generated in the random number generation step becomes the predetermined value. The image processing method according to claim 9 . In the random number control step, when the pixel value is a value in an intermediate density range, the random number generated in the random number generation step is controlled to be larger than the predetermined value. The image processing method according to claim 9 or 10 . The random number control step divides the random value generated in the random number generation step by a constant when the pixel value is equal to or less than the first specified value N1 and when the pixel value is equal to or greater than the fourth specified value N4 (N1 <N4). The image processing method according to claim 9 , wherein the processed value is output. In the random number control step, when the pixel value is larger than the first prescribed value N1 and not more than a second prescribed value N2 (N1 <N2 <N4) and when the pixel value is a third prescribed value N3 (N1 <N2 <N3) or more, and when smaller than the fourth specified value N4, a value corresponding to the pixel value and the specified value is obtained by dividing the random value generated in the random number generating step by the constant. the image processing method according to claim 1 2, characterized in that outputs a value obtained by adding the. The random number generation step, the image processing method according to any one of claims 9 to 1 3 and generates a random number amplitude becomes the predetermined value or more. The addition step, the image processing method according to any one of claims 9 to 1 4, characterized by further adding the half of the maximum value of remainder of division by the dividing constant as a bias value. If the division constant is even, the gradation conversion process, according to claims 9 to 1 5, characterized in that the gradation conversion processing to the pixel value and the dividing constant and the predetermined value is doubled Image processing method.

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