JP4139752B2 - Image processing apparatus, image forming apparatus, image processing method, image processing program, and recording medium recording the program - Google Patents

Description

  The present invention relates to an image processing apparatus, an image forming apparatus, an image processing method, an image processing program, and a recording medium on which the program is recorded, which distributes an error generated between an input density and an output density in a target pixel to peripheral pixels. It is. Specifically, the present invention relates to an image processing apparatus that performs halftone processing on image data input for each pixel based on an error diffusion method.

  2. Description of the Related Art Conventionally, image data read by an image reading device such as a scanner or image data created using application software on a computer is output using an image output device such as a printer. At this time, if the gradation output capability of the image output device is lower than the gradation representation capability of the image data, image processing called halftone processing is performed on the image data in order to reproduce good gradation. Image output.

  In such halftone processing, generally two types of methods are mainly used: a dither method and an error diffusion method. Of these, the error diffusion method is currently used in inkjet printers and the like because it has high resolution and excellent tone reproducibility. The error diffusion method performs quantization to obtain a quantized value by comparing the density of a pixel of interest with a predetermined threshold for a certain pixel of interest, and obtains a difference in density before quantization as an error with respect to the quantized value. The obtained error is diffused to the density of the pre-quantization pixel located around the pixel of interest, thereby reducing the number of gradations and maintaining the density gradation of the entire image.

Here, a diffusion error e _{x + i, y +} for diffusing the error Ex _{, y} of the pixel of interest represented by coordinates (x, y) to surrounding pixels separated from the pixel of interest by the relative coordinates (i, j). _j is the diffusion coefficient a _{i, j} ,
e _{x + i, y + j} = (a _{i, j} / Σa _{i, j} ) × E _{x, y}
It is represented by

Conventionally, when a decimal number is included in the diffusion error, the numerical value of the decimal part is rounded down for the purpose of simplifying the hardware or speeding up the software processing. In this case, the total value of the diffusion errors e _{x + i, y + j} of each peripheral pixel may be greatly deviated from the error E _{x, y of the} target pixel, so that the image quality may be deteriorated.

  In order to solve this problem, in the image processing method described in Patent Document 1 below, the error of the pixel of interest is divided by the sum of the coefficients (diffusion coefficients) of the weight matrix, and the weight matrix includes the weight matrix. Each coefficient is multiplied and distributed to the corresponding surrounding pixels, and the remainder is distributed to the corresponding surrounding pixels according to a predetermined distribution order.

According to this image processing method, calculation of the decimal part is not necessary, so that even software processing can be executed at high speed, and the hardware structure can be simplified. Further, since the remainder corresponding to the numerical value of the decimal part is distributed to the corresponding peripheral pixels in accordance with a predetermined distribution order, it is possible to prevent image quality deterioration.
Japanese Patent Laid-Open No. 2-97169 (published on April 9, 1990)

  For example, in order to improve the processing capability of an image forming apparatus such as a digital copying machine, it is required to perform the halftone process at a high speed without degrading the image quality.

  Since processing of pixels on the same line as the target pixel cannot be pipelined, it is necessary to perform processing with one clock. In particular, the pixel immediately adjacent to the pixel of interest is a bottleneck for speeding up processing because it is very heavy and cannot be pipelined.

  On the other hand, since processing of a line different from the target pixel can be pipelined, if the pipeline is deepened (if the number of pipeline stages is increased), the processing speed can be easily increased. Therefore, it is required to eliminate the bottleneck.

  Further, in the above-mentioned Patent Document 1, since the pixel adjacent to the right side of the target pixel is included in the peripheral pixels to which the remainder is distributed, the processing of the pixel adjacent to the right side of the target pixel becomes heavier than usual, and the processing speed decreases. Will do.

  The present invention has been made in view of the above-described problems, and an object of the present invention is to provide an image processing apparatus capable of performing halftone processing at high speed while suppressing deterioration in image quality.

In order to solve the above problems, an image processing apparatus according to the present invention is an image processing apparatus that distributes an error between an input density and an output density of a target pixel to surrounding pixels, and the input density is quantized with a predetermined threshold value. Quantization means for obtaining the output density, error calculation means for calculating an error caused by the quantization, and diffusion error calculation means for calculating a diffusion error in which the error is distributed to each peripheral pixel. The diffusion error calculation means truncates the decimal part of the diffusion error distributed to the peripheral pixel that is the next pixel of interest, while subtracting the decimal part of the diffusion error distributed to other peripheral pixels. and rounded toward the smaller, rounding the fractional part of the diffused error for those absolute value decreases the diffusion errors, if the diffusion error is a positive value is the fractional part of the diffused error cut While the temple, is characterized in that the diffused error is performed by when the negative value represented by complement fractional part of the diffusion errors rounded up.

The image processing apparatus according to the present invention is an image processing apparatus that distributes an error that occurs between an input density and an output density at a pixel of interest to peripheral pixels, and the input density is quantized with a predetermined threshold value. The above-mentioned quantization error calculation means, an error calculation means for calculating an error caused by the quantization, and a diffusion error calculation means for calculating a diffusion error in which the error is distributed to each peripheral pixel are provided. The means includes a decimal processing means for rounding a decimal part of the diffusion error to a smaller absolute value of the diffusion error, and the decimal processing means has the diffusion error if the diffusion error is a positive value. The decimal part of the diffusion error is rounded down if the diffusion error is a negative value represented by a complement .

In addition, the image forming apparatus according to the present invention is characterized in that the image processing apparatus having the above-described configuration is integrally provided. The image processing method according to the present invention occurs between the input density and the output density in the target pixel. In an image processing method of an image processing apparatus for distributing an error to surrounding pixels, a quantization step for quantizing the input density with a predetermined threshold to obtain the output density, and an error calculation step for calculating an error caused by the quantization step And a diffusion error calculation step of calculating a diffusion error in which the error is distributed to each peripheral pixel, and the diffusion error calculation step is a decimal number of diffusion errors to be distributed to the peripheral pixel to be the next pixel of interest. The fractional part of the diffusion error distributed to other peripheral pixels is rounded down to the smaller absolute value of the diffusion error, and the diffusion error is reduced to the smaller absolute value of the diffusion error. Rounding off the decimal part of the error means that if the diffusion error is a positive value, the decimal part of the diffusion error is truncated, whereas if the diffusion error is a negative value represented by a complement, the decimal part of the diffusion error is rounded off. It is characterized by being performed by rounding up the part .

The image processing method according to the present invention is an image processing method for an image processing apparatus for distributing an error generated between the input density and output density at the target pixel to peripheral pixels, quantizes the input density at a predetermined threshold value A quantization step for setting the output density, an error calculation step for calculating an error caused by the quantization, and a diffusion error calculation step for calculating a diffusion error in which the error is distributed to each peripheral pixel. It said diffusion error calculation step, any fractional portion of the diffused error, the absolute value and Nde including fractional step rounding towards the smaller the diffusion errors, the small number of processing steps, the diffusion error is positive value For example, the decimal part of the diffusion error is rounded down, while the decimal part of the diffusion error is rounded up if the diffusion error is a negative value represented by a complement .

  An image processing program according to the present invention is an image processing program for operating the image processing apparatus having the above configuration, and causes a computer to function as each unit of the image processing apparatus.

  A recording medium according to the present invention is a computer-readable recording medium on which the image processing program is recorded.

In the image processing apparatus according to the present invention, as described above, the diffusion error calculation means truncates the decimal part of the diffusion error distributed to the peripheral pixel that is the next pixel of interest, while the diffusion distributed to other peripheral pixels. The decimal part of the error is rounded to the smaller absolute value of the diffusion error, and the decimal part of the diffusion error is rounded to the smaller absolute value of the diffusion error. If this is the case, the decimal part of the diffusion error is rounded down. On the other hand, if the diffusion error is a negative value represented by a complement, the decimal part of the diffusion error is rounded up .

Thus, that truncates the fractional portion of the diffusion error to be distributed to the peripheral pixels following the pixel of interest, since the only simple rounding, that the load of processing in the peripheral pixels following the pixel of interest increases There is an effect to prevent. Further, the fractional part of the diffusion error to be distributed to other surrounding pixels, by rounding towards the absolute value of the diffused error is small, Ru can be prevented accumulated diffusion error deviates greatly. Therefore, since the influence on the image quality by performing a simple rounding process is small when it corresponds to the peripheral pixel to be the next pixel of interest, an effect of suppressing the deterioration of the image quality is exhibited.

In the image processing apparatus according to the present invention, as described above, the diffusion error calculation unit includes a decimal processing unit that rounds the decimal part of the diffusion error to a smaller absolute value of the diffusion error . The decimal processing means truncates the decimal part of the diffusion error if the diffusion error is a positive value, and rounds up the decimal part of the diffusion error if the diffusion error is a negative value represented by a complement. It is. As a result, the deviation of the diffusion error before and after the rounding process can be reduced, so that an increase in the deviation due to the accumulation of the diffusion error can be suppressed, and the deterioration of the image quality can be suppressed. .

  In addition, even the image forming apparatus integrally including the image processing apparatus having the above configuration can achieve the above-described effects.

In the image processing method according to the present invention, as described above, the diffusion error calculation step truncates the decimal part of the diffusion error distributed to the peripheral pixel that is the next pixel of interest, while being distributed to other peripheral pixels. Rounding the decimal part of the diffusion error to the smaller absolute value of the diffusion error and rounding the decimal part of the diffusion error to the smaller absolute value of the diffusion error. If the value is, the decimal part of the diffusion error is rounded down. On the other hand, if the diffusion error is a negative value represented by a complement, the decimal part of the diffusion error is rounded up . As a result, there is an effect of preventing an increase in processing load on the peripheral pixel that is the next pixel of interest. Further, by rounding the decimal part of the diffusion error distributed to other peripheral pixels to the smaller absolute value of the diffusion error, it is possible to prevent the accumulated diffusion error from being greatly shifted, so that the next target pixel In the case of corresponding peripheral pixels, a simple rounding process has a small influence on the image quality, and thus has an effect of suppressing the deterioration of the image quality.

The image processing method according to the present invention, as described above, the diffusion error calculation step, the fractional part of diffused error includes a fractional step rounding towards the absolute value of the diffused error is small, the The decimal processing step rounds down the fractional portion of the diffusion error if the diffusion error is a positive value, and rounds up the fractional portion of the diffusion error if the diffusion error is a negative value represented by a complement . . As a result, the deviation of the diffusion error before and after the rounding process can be reduced, so that an increase in the deviation due to the accumulation of the diffusion error can be suppressed, and the deterioration of the image quality can be suppressed. .

  Each unit in the image processing apparatus can be executed on a computer by an image processing program. Furthermore, the image processing program can be executed on an arbitrary computer by storing the image processing program in a computer-readable recording medium.

[Embodiment 1]
An embodiment of the present invention will be hereinafter explained with reference to FIGS. 1 to 8. FIG. 2 shows a schematic configuration of the digital color copying machine (image forming apparatus) of the present embodiment. As illustrated, the digital color copying machine 10 includes an image input device 11, an image processing device 12, an image output device 13, and an operation panel 14.

  The image input device 11 is configured to include a scanner unit including, for example, a CCD (Charge Coupled Device). The image input device 11 reads a reflected light image from a document with a CCD, generates RGB (R: red, G: green, B: blue) analog signals, and uses the generated RGB analog signals as the image processing device 12. Output to.

  The image processing device 12 is configured by an ASIC (Application Specific Integrated Circuit), performs image processing on the RGB analog signal received from the image input device 11, generates CMYK image data, and sends it to the image output device 13. Output. The image output device 13 receives CMYK image data for one page from the image processing device 12, and outputs an image on a recording sheet based on the data.

  Although not shown, the operation panel 14 includes a liquid crystal display device for performing an interface with a user and buttons for operation instructions. The operation panel 14 instructs each of the devices 11 to 13 by communication with the devices 11 to 13. Or the operation state of each device 11 is displayed on the liquid crystal display device.

  Next, a more detailed configuration and function of the image processing apparatus 12 in the present embodiment will be described. As shown in FIG. 2, the image processing apparatus 12 includes an A / D (analog / digital) conversion unit 20, a shading correction unit 21, an input tone correction unit 22, a region separation processing unit 23, a color correction unit 24, and a black generation. The undercolor removal unit 25, the spatial filter processing unit 26, the output tone correction unit 27, the tone reproduction processing unit (halftone generation unit) 28, and a control unit 29 are provided.

  The A / D converter 20 A / D converts the RGB analog signal received from the image input device 11 to generate digital RGB image data. The shading correction unit 21 performs processing for removing various distortions generated in the illumination system, the imaging system, and the imaging system of the image input device 11 on the RGB image data received from the A / D conversion unit 20. The input tone correction unit 22 adjusts the color balance of the RGB image data (RGB reflectance data) from which various distortions have been removed by the shading correction unit 21, and at the same time, for example, as in the density data, The image data is converted into easy-to-handle image data.

  The region separation processing unit 23 separates each pixel in the input image into one of a character region, a dot region, and a photographic region with respect to the image data received from the input tone correction unit 22. Based on the separation result, the region separation processing unit 23 outputs a region identification signal indicating to which region the pixel belongs to the black generation and under color removal unit 25 and the spatial filter processing unit 26 and also performs input tone correction. The image data received from the unit 22 is output to the subsequent color correction unit 24 as it is. Note that the region separation processing unit 23 may output the region identification signal to the gradation reproduction processing unit 28.

  The color correction unit 24 converts the RGB image data into CMY (C: cyan, M: magenta, Y: yellow) image data, and in order to realize faithful color reproduction, the color correction unit 24 includes CMY color materials including unnecessary absorption components. A process for removing color turbidity based on spectral characteristics is performed. The black generation and under color removal unit 25 generates K (black) image data from the CMY image data received from the color correction unit 24, and subtracts the generated K image data from the original CMY image data to create a new CMY image. Generate data. As a result, the CMY three-color image data is converted into CMYK four-color image data.

  The spatial filter processing unit 26 performs a spatial filter process using a digital filter on the CMYK image data received from the black generation and under color removal unit 25 based on the region identification signal received from the region separation processing unit 23 to obtain a spatial frequency. Correct the characteristics. This prevents blurring of the output image and deterioration of graininess. For example, for a character region separated by the region separation processing unit 23, in order to improve the reproducibility of a black character or a color character in particular, a high frequency enhancement amount is increased by a sharp enhancement process. The halftone area separated by the area separation processing unit 23 is subjected to a low-pass filter process for removing the input halftone component.

  The output tone correction unit 27 performs output tone correction processing for converting data such as density data into a halftone dot area ratio that is a characteristic value of the image output device 13.

  The gradation reproduction processing unit 28 performs gradation reproduction processing (halftone generation processing) in which an image is finally separated for each pixel and processed so that each gradation can be reproduced. As the gradation reproduction process, a binary or multi-value dither method, an error diffusion method, or the like can be used. In this application, an error diffusion method is used. Details of the gradation reproduction processing unit 28 will be described later.

  The CMYK image data subjected to the above processing is temporarily stored in a storage means (not shown), read out at a predetermined timing, and output to the image output device 13. The image output device 13 outputs image data onto a recording medium such as paper. Examples of the image output device 13 include a color image output device using an electrophotographic method or an ink jet method, but are particularly limited. is not.

  The control unit 29 is configured by a general CPU (Central Processing Unit), and controls each unit 20 to 28 in the image processing apparatus 12 to perform a series of image processing.

  Next, the gradation reproduction process performed by the gradation reproduction processing unit 28 in the present embodiment will be described in detail. As described above, the error diffusion method used in the present embodiment performs quantization to obtain a quantized value by comparing the input image data of a target pixel with a predetermined threshold for a target pixel. The difference between the input image data with respect to the value is obtained as an error, and the obtained error is diffused to the input image data of the pre-quantization pixel located around the target pixel to reduce the number of gradations, and the entire image The density gradation is maintained.

Here, a diffusion error e _{x + i, y +} for diffusing the error Ex _{, y} of the pixel of interest represented by coordinates (x, y) to surrounding pixels separated from the pixel of interest by the relative coordinates (i, j). _j is the diffusion coefficient a _{i, j} ,
e _{x + i, y + j} = (a _{i, j} / Σa _{i, j} ) × E _{x, y}
It is represented by

  The peripheral pixels to which the diffusion error is distributed are pixels that have not yet been quantized on the image data. In general, transmission of image data for one screen is performed by sequentially sending image data of pixels in the right direction of the same line starting from the upper left pixel, and repeating this for the lower line. Therefore, the peripheral pixels to which the diffusion error is distributed can be selected from all pixels in the right direction of the same line of the target pixel and all pixels on the line below the target pixel.

FIG. 3 shows the relationship between the pixel of interest used in this embodiment and its peripheral pixels. As shown in the figure, in the present embodiment, relative coordinates (1, 0) , ( The pixels located at −1, 1), (0, 1), (1, 1) are selected as peripheral pixels A, B, C, and D.

The diffusion coefficient a _{i, j} of each peripheral pixel is determined in advance and stored in a diffusion coefficient storage unit 32 described later. It should be noted that it is desirable to prepare a plurality of predetermined diffusion matrixes (for example, 4 groups) having diffusion coefficients a _{i, j} of each peripheral pixel as elements, and select one group at random for each pixel of interest. . In this case, it is possible to prevent a pattern that does not exist in the original image such as moire fringes from occurring in a region where the same density continues.

  FIG. 1 shows a schematic configuration of the gradation reproduction processing unit 28. The gradation reproduction processing unit 28 includes a quantization processing unit (quantization unit, error calculation unit) 30, a diffusion error calculation unit (diffusion error calculation unit) 31, a diffusion coefficient storage unit 32, and a diffusion error storage unit 33. It is.

The quantization processing unit 30 acquires and adds the accumulated diffusion error Σex _{, y} from the diffusion error storage unit 33 to the input image data (input density) of the target pixel (x, y), and adds The image data is compared with a predetermined threshold and quantized. For example, assuming that the threshold value is 128, input image data having a value of 0 to 255 is binarized to “0” or “255”. It is also possible to quantize to three or more values using a plurality of threshold values. The quantized image data is output to the image output device 13 as output image data (output density). Further, the quantization processing unit 30 calculates a difference obtained by subtracting the added image data from the quantized image data as an error. The calculated error is sent to the calculation unit of each peripheral pixel A to D in the diffusion error calculation unit 31.

As described above, the diffusion error calculation unit 31 calculates the diffusion error distributed to the peripheral pixels A to D based on the error calculated by the quantization processing unit 30. Details of the diffusion error calculation unit 31 will be described later. As described above, the diffusion coefficient storage unit 32 stores a plurality of sets of diffusion matrices including the diffusion coefficients a _{i, j} of the peripheral pixels A to D.

  The diffusion error storage unit 33 accumulates and holds the diffusion error for each pixel until the corresponding image data is quantized. That is, the diffusion error distributed from the target pixel P to the peripheral pixels A to D is added to the diffusion error held in the diffusion error storage unit 33 and held.

  In an actual circuit, the diffusion error accumulated for each pixel is held in a FIFO (first in first out) type memory when the pixel does not correspond to the peripheral pixels A to D, while the pixel is stored in the peripheral pixels A to D. If this is the case, the diffusion error distributed from the pixel of interest P is added by the adder and held by the latch.

  Next, a detailed configuration of the diffusion error calculation unit 31 will be described. The diffusion error calculation unit 31 includes a simple calculation unit (simple calculation unit, calculation unit, decimal processing unit) 40 for the peripheral pixel A, and a normal calculation unit (calculation unit) 41, code for each of the other peripheral pixels B to D. The configuration includes a determination unit 42, a bit determination unit 43, and a correction unit (decimal processing means) 44.

The simple calculation unit 40 and the normal calculation unit 41 receive the error _{Ex, y} from the target pixel P, receive the diffusion coefficient corresponding to the peripheral pixel from the diffusion coefficient storage unit 32, perform the above-described equation, and perform the diffusion error. Is calculated. For example, as shown in FIG. 6A, when all the diffusion coefficients a _{i, j} corresponding to the peripheral pixels A to D are set to 1, the diffusion error is calculated by calculating the following equation.

e _{x + i, y + j} = (1/4) × E _{x, y} (1)
The decimal part of the calculated diffusion error is rounded down by the simple calculation unit 40 for the peripheral pixel A, and rounded by the correction unit 44 for the peripheral pixels B to D as described later.

  In the present embodiment, the calculation of the diffusion error in the peripheral pixel that is the next target pixel P, that is, the peripheral pixel A is performed by a simple calculation. Thereby, the calculation time of the diffusion error in the peripheral pixel A is shortened, and the time until the quantization process in the next target pixel P is performed is shortened. Therefore, halftone processing can be performed at high speed.

  For example, in the case of a diffusion matrix as shown in FIG. 6B, in the normal calculation, the following equation is calculated to calculate the diffusion error.

Pixel A: e _{x, y + 1} = (5/16) × E _{x, y}
Pixel B: e _{x + 1, y-1} = (3/16) × E _{x, y}
Pixel C: e _{x + 1, y} = (5/16) × E _{x, y}
Pixel D: e _{x + 1, y + 1} = (3/16) × E _{x, y}
On the other hand, in the simple calculation, the diffusion error is calculated by performing addition or subtraction instead of multiplication. Specifically, since the surrounding pixel A on which the simple calculation is performed is 5/16 = (1/16) + (1/4), the calculation of the following equation is performed to calculate the diffusion error.

Pixel A: e _{x, y + 1} = {(1/16) + (1/4)} × E _{x, y}
In general, when multiplying m digits and n digits, it is necessary to prepare (m + n) digits as a product. Further, when the number of digits increases, the number of AND gates that perform logical product and the number of adders that perform addition significantly increase, delaying the processing and increasing the circuit scale.

On the other hand, by using the addition or subtraction, when calculating the diffusion errors to be distributed, the error E _x, the coefficient to be multiplied by _{y (a i, j / Σa} i, j) is required multiplication is unnecessary coefficients Therefore, the available diffusion coefficient a _{i, j} is limited. However, since the number of digits does not increase as compared with the case of performing multiplication, the circuit can be simplified and the arithmetic processing can be performed quickly. Note that if the division is performed by a power of 2, only the bit shift operation needs to be performed, so that the calculation processing load can be further reduced.

The sign determination unit 42 determines whether or not the error _{Ex, y} received from the quantization processing unit 30 is a negative value. For this purpose, as shown in FIG. 7, the sign bit of the error data received from the quantization processing unit 30 is used. In the case of FIG. 7, the negative number is represented by 2's complement. The sign determination unit 42 may determine whether the diffusion error calculated by the normal calculation unit 41 is a negative number.

  The bit determination unit 43 determines whether or not the logical sum of the bits of the decimal part of the diffusion error calculated by the normal calculation unit 41 is 1. That is, in the case of FIG. 7, since the diffusion error is obtained by multiplying the error by ¼, the lower 2 bits become the bits of the decimal part. Therefore, it is determined whether or not the logical sum of the lower 2 bits is 1. This makes it possible to determine whether or not there is a decimal value in the diffusion error.

The correction unit 44 receives the determination results of the sign determination unit 42 and the bit determination unit 41, and based on these determination results, the error _{Ex, y} is a negative value and the value of the decimal part is included in the diffusion error. If it exists, a correction process is performed in which the decimal part of the diffusion error is rounded down and 1 is added, and in other cases, the decimal part of the diffusion error is rounded down. That is, if there is a decimal value in the diffusion error, the decimal part is rounded down if the diffusion error is positive, and the decimal part is rounded up if it is negative. The diffusion error is rounded down to a smaller value.

For example, in the case of a diffusion matrix as shown in FIG. 6A, if the error E _{x, y} = 25, the diffusion error e _{x + i, y + j of} each peripheral pixel A to D is obtained from the above equation (1). 6.25, and if the fractional part is discarded as in the prior art, the diffusion error e _{x + i, y + j} is 6. That is, when the diffusion error e _{x + i, y + j} is a positive number and includes a decimal part, the absolute value (magnitude) of the diffusion error is rounded down to a smaller value by rounding off the decimal part. become.

On the other hand, if the error E _{x, y} = −25, the diffusion error e _{x + i, y + j} of each of the peripheral pixels A to D becomes −6.25. e _{x + i, y + j} is −7. That is, when the diffusion error e _{x + i, y + j} is a negative number and includes a decimal part, the decimal part is rounded off to increase the absolute value of the diffusion error. In this case, the diffusion error that is rounded toward the larger absolute value is accumulated, so that the accumulated diffusion error is too large and the image quality may be deteriorated.

In contrast, in the present embodiment, with respect to surrounding pixels B to D, the diffusion error e _{x + i,} when _{y + j} comprises is and fractional part a negative number, by performing the rounding up process of fractional part Then, the absolute value of the diffusion error is rounded down. In this case, the absolute value of the diffusion error is not rounded toward the larger value, and it is possible to prevent the accumulated diffusion error from being too large and degrading the image quality.

  There are two methods for rounding up the fractional part: a method in which 1 is added after the decimal part is rounded down, and a method in which the decimal part is rounded down after the 1 is added. The former method is processed in comparison with the latter method. This is desirable because the number of bits required for the processing is reduced, so that the circuit scale is reduced and the processing speed is improved.

  On the other hand, with respect to the peripheral pixel A, the same truncation processing as that in the past is performed. In this case, since the processes of the code determination unit 42, the bit determination unit 43, and the correction unit 44 are omitted, the processing load does not increase. Further, even if the absolute value of the diffusion error of the peripheral pixel A is rounded toward the larger value, the absolute value of the diffusion error accumulated when corresponding to the peripheral pixels B to D is rounded to the smaller value. The effect on image quality is considered to be small. Actually, when the processing as in the present embodiment was performed, the influence on the image quality was hardly seen.

  Next, the processing of the sign determination unit 42, the bit determination unit 43, and the correction unit 44 will be specifically described in the case where the diffusion error is data as shown in FIG. As shown in the figure, the sign bit is included at the head of the diffusion error. When the sign bit is “0”, the diffusion error is a positive number, and when it is “1”, the diffusion error is a negative number. Therefore, the sign of the diffusion error can be determined by referring to this code bit.

On the other hand, in the bit determination process, a logical sum of bits that have become a decimal part is obtained by performing division. For example, when dividing by 4 (= 2 ² ), the lower 2 bits become a decimal part, and when dividing by 8 (= 2 ³ ), the lower 3 bits become a decimal part, and the logical sum of these bits is obtained. It will be. If the logical sum is “1”, at least one bit among the bits that become the decimal part is “1”, which means that some numerical value exists in the decimal part. On the other hand, if the logical sum is “0”, all the bits that have become the decimal part are “0”, which means that there is no numerical value in the decimal part.

  Then, by obtaining the logical product of the sign bit and the logical sum, it is possible to determine whether or not the diffusion error is a negative number and the number of decimal parts is present. If the logical product is “1”, the diffusion error is a negative number and the number of fractional parts exists, and therefore, the rounding process of the fractional part is performed as described above. On the other hand, if the logical product is “0”, the decimal portion is cut off as in the conventional case.

  A rounding process may be performed instead of the rounding process or the rounding process. That is, it may be rounded to the nearest integer by referring to the decimal part of the diffusion error. For example, if the diffusion error is +6.75, it may be rounded to +7, and if it is −6.75, it may be rounded to -7. In this case, the deviation of the diffusion error before and after the rounding process can be reduced, and the accumulated diffusion error can be suppressed from greatly shifting, and the deterioration of the image quality can be suppressed.

  The rounding process may be performed as follows. That is, when the first decimal place bit is “1”, since a + 0.5 ≦ x <a + 1 (where a is an integer), the decimal part is rounded down and 1 is added. On the other hand, in other cases, that is, when the bit at the first decimal place is “0”, the decimal part is rounded down.

  Therefore, it is only necessary to refer to the first decimal place bit, and it is not necessary to refer to other fractional parts and positive and negative signs. Therefore, the circuit configuration can be omitted and the processing speed can be improved as compared with the above embodiment. .

  Next, the flow of the processing operation in the gradation reproduction processing unit 28 will be described with reference to FIGS. FIG. 4 shows the flow of processing operations in the gradation reproduction processing unit 28. First, when input image data is input to the target pixel P, the quantization processing unit 30 acquires the diffusion error accumulated from the diffusion error storage unit 33 and adds it to the input image data (step S1). Next, the quantization processing unit 30 performs a quantization process on the added input image data and outputs it as output image data, and calculates a difference from the output image data as an error (step S2).

  Next, the diffusion error calculation unit 31 determines a diffusion coefficient for each of the surrounding pixels A to D by selecting one set from a plurality of sets of diffusion matrices and acquiring it from the diffusion coefficient storage unit 32 (step S3). ). Next, the diffusion error calculator 31 calculates a diffusion error (step S4).

  FIG. 5 shows the flow of the diffusion error calculation process. First, for the neighboring pixel A on the right side, the simple calculation unit 40 performs simple calculation processing on the error acquired from the quantization processing unit 30 (step S10), and a value obtained by rounding down the decimal part from the calculated value is defined as a diffusion error. (Step S11).

  On the other hand, for other peripheral pixels B to D, first, the normal calculation unit 41 performs normal calculation processing on the error acquired from the quantization processing unit 30 (step S12). Next, when the sign of the error is negative and the logical sum of the bits of the decimal part is “1” (YES in step S13 and YES in step S14), the decimal part is rounded down from the calculated value in step S12. , "1" is added as the diffusion error (step S15), otherwise, the value obtained by rounding down the fractional part from the calculated value at step S12 is set as the diffusion error (step S16). Then, after calculating the diffusion error in steps S11, S15, and S16, the process returns to the original processing routine shown in FIG.

  Next, the diffusion error calculation unit 31 acquires the diffusion error accumulated in the pixels corresponding to the respective peripheral pixels A to D from the diffusion error storage unit 33, and adds the diffusion error calculated in step S4 to the accumulated diffusion error. The error is added, and the added diffusion error is stored in the diffusion error storage unit 33 (step S5).

  Then, after performing the above processing for all the pixels (step S6), the processing operation in the gradation reproduction processing unit 28 is terminated.

  In the above embodiment, the diffusion coefficient of the peripheral pixel A is simply calculated by the simple calculation unit 40, and the decimal part of the calculated diffusion error is rounded down. However, as with the other peripheral pixels B to D, If the diffusion error is a positive value, the decimal part may be rounded down, and if the diffusion error is negative, the process may be changed to round up the decimal part. In this case, as shown in FIG. 8, the calculation unit of the peripheral pixel A in the diffusion error calculation unit 31 of the gradation reproduction processing unit 28 is replaced with the code determination unit 42 and the bit determination in the simple calculation unit 40 shown in FIG. The unit 43 and the correction unit 44 are added.

[Embodiment 2]
Next, another embodiment of the present invention will be described with reference to FIGS. The digital color copying machine of the present embodiment is different from the digital color copying machine shown in FIGS. 1 to 7 in the configuration of the calculation unit of the peripheral pixel A in the diffusion error calculation unit 31 of the gradation reproduction processing unit 28. The configuration of is the same. In addition, the same code | symbol is attached | subjected to the structure which has the function similar to the structure demonstrated in the said embodiment, and the description is abbreviate | omitted.

  In the present embodiment, the calculation unit of the peripheral pixel A in the diffusion error calculation unit 31 of the gradation reproduction processing unit 28 is changed from the simple calculation unit 40 shown in FIG. In other words, a normal calculation is performed on the error acquired from the quantization processing unit 30 to calculate a diffusion error, and the decimal part is rounded down. In this case, the processing load increases as compared with the simple calculation unit 40, but the sign determination unit 42, the bit determination unit 43, and the correction unit 44 are omitted as compared with the calculation units of the peripheral pixels B to D. The circuit scale is simplified and the processing burden is reduced.

  FIG. 10 shows the flow of the diffusion error calculation process for the peripheral pixels A to D in this embodiment. As illustrated, first, normal calculation processing is performed on the error acquired from the quantization processing unit 30 (step S20). Next, if the sign of the error is negative, the logical sum of the bits of the decimal part is “1”, and the pixel is other than the peripheral pixel A right next to the target pixel P (YES in step S21) “YES” in step S22 and NO in step S23), “1” is added from the calculated value in step S20, and a value obtained by rounding down the decimal part is defined as a diffusion error (step S25). On the other hand, in other cases, a value obtained by discarding the decimal part from the calculated value in step S20 is set as a diffusion error (step S24). Then, after calculating the diffusion error in steps S24 and S25, the process returns to the original processing routine shown in FIG.

[Embodiment 3]
Next, another embodiment of the present invention will be described with reference to FIG. FIG. 11 shows a schematic configuration of a print system in the present embodiment. As illustrated, the printing system includes a computer 50 and a printer 51 connected to the computer. The computer 50 includes an application execution unit 52, a printer driver 53, a communication port driver 54, and a communication port 55. When an image data print instruction is executed by the application execution unit 52, the application execution unit 52 sends the image data to the printer driver 53. The printer driver 53 performs various processes on the image data sent from the application execution unit 52, and then performs an electrophotographic or inkjet printer via a communication port driver 54 and a communication port 55 such as RS232C / LAN. (Image output device) 51 for output.

  In the printing system of the present embodiment, the image input device 11 corresponds to the computer 50 and the image output device 13 corresponds to the printer 51 as compared with the digital color copying machine shown in FIGS. Among the configurations of the image processing apparatus 12, the color correction unit 24, the black generation and under color removal unit 25, and the gradation reproduction processing unit 28 are included in the printer driver 53 of the computer 50, and the other configurations are included in the printer 51. It is. The printer 51 may be a digital multi-function peripheral having a copy function and a fax function in addition to the printer function.

  In the present embodiment, the printer driver 53 includes a color correction unit 56, a gradation reproduction processing unit 57, and a printer language translation unit 58. The color correction unit 56 performs the same processing as the color correction unit 24 and the black generation and under color removal unit 25 shown in FIG. Further, the gradation reproduction processing unit 57 performs the same processing as the gradation reproduction processing unit 28 shown in FIG. The printer language translation unit 58 translates the image data image-processed by the color correction unit 56 and the gradation reproduction processing unit 57 into a printer language such as a page description language (PDL).

  As described above, the gradation reproduction processing according to the present invention can be executed by the printer driver 53 of the computer 50.

  Finally, each block of the image processing apparatus 12 of the above-described embodiment, in particular, the gradation reproduction processing unit 28 may be configured by hardware logic, or may be realized by software using a CPU as follows. .

  That is, the image processing apparatus 12 includes a CPU (central processing unit) that executes instructions of a control program for realizing each function, a ROM (read only memory) that stores the program, and a RAM (random access memory) that expands the program. And a storage device (recording medium) such as a memory for storing the program and various data. An object of the present invention is a recording medium on which a program code (execution format program, intermediate code program, source program) of a control program of the print management apparatus 4 which is software for realizing the functions described above is recorded so as to be readable by a computer. This can also be achieved by supplying the print management apparatus 4 and reading and executing the program code recorded on the recording medium by the computer (or CPU or MPU).

  Examples of the recording medium include a tape system such as a magnetic tape and a cassette tape, a disk system including a magnetic disk such as a flexible disk / hard disk and an optical disk such as a CD-ROM / MO / MD / DVD / CD-R, and an IC card. A card system such as an optical card (including a memory card) or a semiconductor memory system such as a mask ROM / EPROM / EEPROM / flash ROM can be used.

  Further, the image processing apparatus 12 may be configured to be connectable to a communication network, and the program code may be supplied via the communication network. The communication network is not particularly limited. For example, the Internet, intranet, extranet, LAN, ISDN, VAN, CATV communication network, virtual private network, telephone line network, mobile communication network, satellite communication. A net or the like is available. Further, the transmission medium constituting the communication network is not particularly limited. For example, even in the case of wired such as IEEE 1394, USB, power line carrier, cable TV line, telephone line, ADSL line, infrared rays such as IrDA and remote control, Bluetooth, It can also be used with radio such as 802.11 radio, HDR, mobile phone network, satellite line, and terrestrial digital network. The present invention can also be realized in the form of a carrier wave or a data signal sequence in which the program code is embodied by electronic transmission.

The present invention is not limited to the above-described embodiments, and various modifications are possible within the scope shown in the claims. Further, the present invention can be obtained by appropriately combining technical means disclosed in different embodiments. Embodiments are also included in the technical scope of the present invention.
The image processing apparatus may be configured as follows.
That is, in the image processing apparatus that distributes an error generated between the input density and the output density at the target pixel to the peripheral pixels, the image processing apparatus quantizes the input density with a predetermined threshold to obtain the output density. Means, an error calculating means for calculating an error caused by the quantization, and a diffusion error calculating means for calculating a diffusion error in which the error is distributed to each peripheral pixel. The diffusion error calculating means includes: In addition, a configuration may be provided that includes simple calculation means for simply calculating the diffusion error distributed to the peripheral pixels as the target pixel.
In this case, the diffusion error calculation means includes a simple calculation means that simply calculates the diffusion error distributed to the peripheral pixel that will be the next pixel of interest, that is, the pixel to the right of the target pixel. Here, “simple calculation” means that the error is calculated by a simpler operation than a normal operation of multiplying the diffusion coefficient assigned to each peripheral pixel and dividing by the sum of the diffusion coefficients. . As a result, the processing of the right adjacent pixel which is very heavy and which cannot be pipelined can be lightened to enable high-speed operation, and the halftone processing can be executed at high speed.
Further, the image processing apparatus according to the above configuration, wherein the diffusion error calculation means multiplies the error by a diffusion coefficient assigned to each peripheral pixel, and divides the error by the sum of the diffusion coefficients; A decimal processing means for rounding a decimal part with respect to a calculation value of the calculation means, and the simple calculation means may be configured to perform the calculation of the calculation means by a combination of division and addition.
In this case, although the diffusion coefficient that can be used is limited, an increase in the number of digits required for the operation can be suppressed, so that the circuit can be simplified and the arithmetic processing can be performed quickly.
Further, the image processing apparatus according to the above configuration, wherein the diffusion error calculation means multiplies the error by a diffusion coefficient assigned to each peripheral pixel, and divides the error by the sum of the diffusion coefficients; A decimal processing unit that rounds a decimal part with respect to a calculation value of the calculation unit, and the simple calculation unit may perform a rounding process of the decimal processing unit by a process of rounding down the decimal part.
In this case, since only a simple rounding process is performed, there is an effect of preventing an increase in the processing load on the peripheral pixel which is the next pixel of interest. Also, even if simple rounding is performed on the next peripheral pixel as the target pixel, by performing appropriate rounding on other peripheral pixels, the total diffusion error of each peripheral pixel becomes larger than the error of the target pixel. The shift can be prevented, and the effect of preventing the deterioration of the image quality is achieved.
An image processing method in the image processing apparatus is an image processing method in an image processing apparatus that distributes an error between an input density and an output density at a target pixel to surrounding pixels, and the input density is quantized with a predetermined threshold. A quantization step for calculating the output density, an error calculation step for calculating an error caused by the quantization step, and a diffusion error calculation step for calculating a diffusion error in which the error is distributed to each peripheral pixel. The diffusion error calculation step may include a simple calculation step of simply calculating the diffusion error distributed to the peripheral pixels that will be the next pixel of interest.
In this case, the diffusion error calculation step includes a simple calculation step of simply calculating the diffusion error distributed to the peripheral pixel that will be the next pixel of interest, that is, the pixel adjacent to the right of the target pixel. As a result, the processing of the right adjacent pixel which is very heavy and which cannot be pipelined can be lightened to enable high-speed operation, and the halftone processing can be executed at high speed.

  According to the present invention, an image processing apparatus is provided in which the calculation time of a diffusion error in a peripheral pixel that is the next pixel of interest is reduced. Thereby, in an image processing apparatus such as a digital color copying machine, it is possible to reduce the time required for image processing.

1 is a block diagram illustrating a schematic configuration of a gradation reproduction processing unit in a digital color copier that is an embodiment of the present invention. FIG. FIG. 2 is a block diagram showing a schematic configuration of the digital color copying machine. It is a figure which shows the relationship between the attention pixel and its peripheral pixel utilized in this embodiment. It is a flowchart which shows the processing operation of the said gradation reproduction process part. It is a flowchart which shows the processing operation of the calculation of the diffusion error performed by the processing operation of the said gradation reproduction process part. FIGS. 7A and 7B are diagrams showing examples of diffusion coefficients. It is a figure which shows the data structure of a diffusion error. It is a block diagram which shows the example of a change of the structure regarding the surrounding pixel A in the said gradation reproduction process part. It is a block diagram which shows schematic structure of the gradation reproduction process part in the digital color copying machine which is another embodiment of this invention. It is a flowchart which shows the processing operation of the calculation of the diffusion error performed by the processing operation of the said gradation reproduction process part. It is a block diagram which shows schematic structure of the printing system which is other embodiment of this invention.

Explanation of symbols

10 Digital color copier (image forming device)
12 Image processing apparatus 30 Quantization processing unit (quantization means, error calculation means)
31 Diffusion error calculation unit (Diffusion error calculation means)
40 Simple calculation unit (simple calculation means, calculation means, decimal processing means)
41 Normal calculation unit (calculation means)
42 Correction unit (decimal processing means)
50 Computer 53 Printer driver (image processing device)
P Target pixel A to D Peripheral pixel

Claims (7)

In an image processing apparatus that distributes an error occurring between an input density and an output density at a target pixel to surrounding pixels,
Quantization means for quantizing the input density with a predetermined threshold to obtain the output density;
An error calculating means for calculating an error caused by the quantization;
A diffusion error calculating means for calculating a diffusion error in which the error is distributed to each peripheral pixel;
The diffusion error calculation means truncates the decimal part of the diffusion error distributed to the peripheral pixel that is the next target pixel, while the absolute value of the diffusion error is reduced to the decimal part of the diffusion error distributed to the other peripheral pixels. It is rounded to the smaller one ,
Rounding the fractional portion of the diffusion error to the smaller absolute value of the diffusion error means that if the diffusion error is a positive value, the fractional portion of the diffusion error is truncated, while the diffusion error is represented by a complement. An image processing apparatus, wherein a negative value is performed by rounding up a decimal part of the diffusion error . In an image processing apparatus that distributes an error occurring between an input density and an output density at a target pixel to surrounding pixels,
Quantization means for quantizing the input density with a predetermined threshold to obtain the output density;
An error calculating means for calculating an error caused by the quantization;
A diffusion error calculating means for calculating a diffusion error in which the error is distributed to each peripheral pixel;
The diffusion error calculation means includes a decimal processing means for rounding the decimal part of the diffusion error to the smaller absolute value of the diffusion error ,
The decimal processing means truncates the decimal part of the diffusion error if the diffusion error is a positive value, and rounds up the decimal part of the diffusion error if the diffusion error is a negative value represented by a complement. An image processing apparatus.   An image forming apparatus comprising the image processing apparatus according to claim 1 or 2 integrally. In an image processing method of an image processing apparatus that distributes an error that occurs between an input density and an output density in a pixel of interest to peripheral pixels,
A quantization step of quantizing the input density with a predetermined threshold to obtain the output density;
An error calculation step of calculating an error caused by the quantization step;
A diffusion error calculation step of calculating a diffusion error in which the error is distributed to each peripheral pixel,
In the diffusion error calculation step, the decimal part of the diffusion error distributed to the peripheral pixel that is the next pixel of interest is discarded, while the decimal part of the diffusion error distributed to the other peripheral pixels is reduced to the absolute value of the diffusion error. It is rounded to the smaller one ,
Rounding the fractional portion of the diffusion error to the smaller absolute value of the diffusion error means that if the diffusion error is a positive value, the fractional portion of the diffusion error is truncated, while the diffusion error is represented by a complement. An image processing method characterized by being performed by rounding up a decimal part of the diffusion error if the negative value is a negative value . In an image processing method of an image processing apparatus that distributes an error that occurs between an input density and an output density in a pixel of interest to peripheral pixels,
A quantization step of quantizing the input density with a predetermined threshold to obtain the output density;
An error calculating step of calculating an error caused by the quantization;
A diffusion error calculation step of calculating a diffusion error in which the error is distributed to each peripheral pixel,
It said diffusion error calculation step, the fractional part of the diffusion errors, which Nde including fractional step rounding towards the absolute value of the diffused error is small,
The decimal processing step rounds down the fractional portion of the diffusion error if the diffusion error is a positive value, and rounds up the fractional portion of the diffusion error if the diffusion error is a negative value represented by a complement. An image processing method characterized by the above.   An image processing program for operating the image processing apparatus according to claim 1 or 2 for causing a computer to function as each unit of the image processing apparatus.   A computer-readable recording medium on which the image processing program according to claim 6 is recorded.

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