JP2002152514A - Image processor, image processing method and imaging apparatus - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an image processor, an image processing method and an imaging apparatus in which visually preferable recording is performed with excellent resolution and halftone and high image quality by superposing a noise on a required part of image data through simpler circuitry. SOLUTION: A halftone output processing section generates a halftone correction curve at step s1 using a reference correction curve stored at a curve storing section, and a plurality of correction amounts stored at a correction amount storing section and stores correction values at an output conversion table storing section. At step s2, a range of input density value between n1 and n2 corresponding to a predetermined range of correction value between m1 and m2 is determined. At step s3, a decision is made whether the input density value falls within a range between n1 and n2 and if it falls within that range, noise is superposed on image data at step s5.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

[0001] 1. Field of the Invention [0002] The present invention relates to an image processing apparatus, an image processing method, and an image forming apparatus for performing a noise superimposing process for superimposing noise on data.

[0002]

2. Description of the Related Art When an image having continuous tones and an image with a reduced number of tones are output by a digital image forming apparatus or the like, in order to improve the tone reproducibility, the image processing apparatus needs to perform two-step printing. Halftone processing is performed using a method such as a value dither method, an error diffusion method, a multi-value dither method, or a multi-value error diffusion method. However, such a halftone process has a problem that a pseudo contour or density unevenness is generated in an output image or graininess is deteriorated. As a countermeasure, there has been proposed an image processing apparatus that obtains a visually more preferable image by superimposing noise on input image data. In the image signal processing method and the apparatus described in Japanese Patent No. 2894117, noise of spatial frequency characteristics that are hardly perceived visually is superimposed on the input image signal in advance according to the image signal level. As a result, image noise and false contours of the original document can be canceled without losing the sharpness and color tone of the image, and a visually desirable image can be obtained. Also, JP-A-9-20052
The image processing apparatus described in Japanese Patent Application Publication No. 3 (1993) -223 is configured to determine whether or not an image signal belongs to a gradation group that produces a false contour at the time of output, and superimpose noise on pixels belonging to the gradation group determined at the time of image output. Means.

[0003]

However, the means for judging whether a pixel belongs to a gradation group that generates a false contour described in Japanese Patent Application Laid-Open No. Hei 9-200523 is a method for controlling the contrast of the amount of optical information. , And an arithmetic unit or the like for comparing the result with a threshold value, and a complicated circuit configuration is required. Since the output characteristics of the image output device are different between the devices and the use conditions, etc., the gradation correction curve (table) in the halftone processing is different, but the same range of correction can be obtained by using the same gradation reproduction method. Pseudo contours and density unevenness occur in the density value range, and graininess deteriorates.

An object of the present invention is to provide an image processing apparatus which superimposes noise on a necessary portion of image data with a simpler circuit configuration and performs high-quality recording which is visually preferable and has excellent resolution and gradation. An object of the present invention is to provide an image processing method and an image forming apparatus.

[0005]

According to the present invention, there is provided a halftone output tone processing means for performing a tone correction process for setting a correction value corresponding to an input density value of image data and a halftone generation process;
A noise superimposing means for superimposing noise on the image data, wherein the noise superimposing means generates noise for image data in an input density value range corresponding to a correction value in a predetermined range. An image processing apparatus characterized by superimposing.

According to the present invention, the noise superimposing processing means
Since noise is superimposed on the image data in the range of the input density value corresponding to the correction value in the predetermined range, the noise is superimposed on a necessary portion of the image data with a simpler circuit configuration, which is visually preferable. In addition, it is possible to generate output image data capable of performing high-quality recording excellent in both resolution and gradation.

Further, the present invention is characterized in that the halftone output tone processing means performs a halftone generation process after performing the tone correction process.

According to the present invention, the noise superposition process can be applied when the tone correction process and the halftone generation process are performed separately.

Further, the present invention is characterized in that the halftone output gradation processing means performs the gradation correction processing and the halftone generation processing simultaneously.

According to the present invention, the noise superposition process can be applied when the tone correction process and the halftone generation process are performed simultaneously.

Further, the present invention is characterized in that the halftone output gradation processing means simultaneously performs the gradation correction processing and the halftone generation processing by multi-value dither processing.

According to the present invention, since the halftone output gradation processing means simultaneously performs the gradation correction processing and the halftone generation processing by the multivalue dither processing, the noise superposition processing is applied to the multivalue dither processing. It is possible to reduce the pseudo contour generated around the switching of the pixel where the dot becomes larger as the density becomes higher in the dither matrix.

Further, the present invention is used for gradation correction processing when a predetermined correction value range is set to m1 or more and m2 or less and a corresponding input density value range is set to n1 or more and n2 or less. An n1 corresponding to m1 is obtained by sequentially examining the gradation correction curve from the minimum input density value to a high density, and an n2 corresponding to m2 is obtained by sequentially examining the input density value n1 + 1 to the high density.
Alternatively, by examining the gradation correction curve in order from the maximum input density value to the low density, n2 corresponding to m2 is obtained.
, And means for determining n1 corresponding to m1 by sequentially examining from the input density value n2-1 to the low density.

According to the present invention, there is provided a means for obtaining an input density value corresponding to a correction value by sequentially examining a gradation correction curve. Therefore, the processing speed for obtaining a range of input density values on which noise is superimposed is increased. be able to.

Further, the present invention is characterized in that a plurality of predetermined correction value ranges are set.

According to the present invention, since a plurality of predetermined correction value ranges are set, noise superimposition processing can be performed on a plurality of input density value ranges.

Further, according to the present invention, when the image data is color image data, the gradation correction curve is set for each color component.

According to the present invention, when the image data is color image data, the gradation correction curve is set for each color component, so that appropriate gradation correction processing can be performed for each color component. Before the gradation correction processing, the noise superimposition processing can be performed in a range of an appropriate input density value corresponding to the processing.

Further, according to the present invention, when the image data is color image data, the predetermined correction value range is set for each color component.

According to the present invention, when the image data is color image data, the predetermined range of the correction value is set for each color component, so that an appropriate range of the input density value is set for each color component. Can be subjected to noise superimposition processing.

Further, the present invention is characterized in that the maximum value and the minimum value of the noise added to the image data by the noise superimposing processing means are set for each of the predetermined correction value ranges.

According to the present invention, the maximum value and the minimum value of the noise added to the image data by the noise superimposing processing means are as follows:
Since the correction value is set for each of the predetermined correction value ranges, an appropriate amount of noise can be superimposed on each of a plurality of appropriate input density value ranges.

Further, the present invention is characterized in that the number of bits of the noise data added to the image data by the noise superimposition processing means is set for each of the predetermined correction value ranges.

According to the present invention, since the number of bits of noise data added to the image data by the noise superimposing means is set for each of the predetermined correction value ranges, the number of bits is set to an appropriate input density value range. An appropriate amount of noise can be superimposed on each, and unnecessary bits can be reduced.

Further, the present invention is characterized by including an image input device for reading a document to obtain image data, any one of the above image processing devices, and an image output device for outputting processed image data. Image forming apparatus.

According to the present invention, there is provided an image input device for reading a document to obtain image data, any one of the above image processing devices, and an image output device for outputting processed image data. Noise is superimposed on the required part of the image data with a simple circuit configuration, and it is visually preferable,
It is possible to output a high-quality image with excellent gradation.

According to the present invention, there is provided a tone correction process for setting a correction value corresponding to an input density value of image data, a halftone output tone process for performing a halftone generation process, and a noise superposition process for superimposing noise on the image data. And a noise superimposing process in which noise is superimposed on image data in a range of input density values corresponding to a correction value in a predetermined range. is there.

According to the present invention, since the noise superimposing process superimposes noise on image data in the range of input density values corresponding to the correction value in the predetermined range, the image data can be processed with a simpler circuit configuration. Noise is superimposed on the necessary part of
It is possible to generate output image data that is visually preferable and can perform high-quality recording with excellent resolution and gradation.

Further, the present invention is characterized in that the halftone output gradation processing is performed after the gradation correction processing and then the halftone generation processing.

According to the present invention, the noise superposition process can be applied when the tone correction process and the halftone generation process are performed separately.

Further, the present invention is characterized in that in the halftone output gradation process, a gradation correction process and a halftone generation process are performed simultaneously.

According to the present invention, the noise superposition processing can be applied when the gradation correction processing and the halftone generation processing are performed simultaneously.

Further, in the present invention, the halftone output gradation processing is characterized in that the gradation correction processing and the halftone generation processing are simultaneously performed by multi-value dither processing.

According to the present invention, the halftone output gradation processing
Since the tone correction process and the halftone generation process are performed simultaneously by the multi-value dither process, the noise superimposition process can be applied in the case of the multi-value dither process, and the dots become larger as the density becomes higher in the dither matrix. It is possible to reduce the pseudo contour generated around the switching of the pixel.

Further, the present invention is used for gradation correction processing when a predetermined correction value range is set to m1 or more and m2 or less and a corresponding input density value range is set to n1 or more and n2 or less. An n1 corresponding to m1 is obtained by sequentially examining the gradation correction curve from the minimum input density value to a high density, and an n2 corresponding to m2 is obtained by sequentially examining the input density value n1 + 1 to the high density.
Alternatively, by examining the gradation correction curve in order from the maximum input density value to the low density, n2 corresponding to m2 is obtained.
Is obtained, and n1 corresponding to m1 is obtained by sequentially examining from the input density value n2-1 to the low density.

According to the present invention, since the input density value corresponding to the correction value is obtained by sequentially examining the gradation correction curve, the processing speed for obtaining the input density value range on which noise is superimposed can be increased. .

Further, the present invention is characterized in that a plurality of predetermined correction value ranges are set.

According to the present invention, since a plurality of predetermined correction value ranges are set, noise superimposition processing can be performed on a plurality of input density value ranges.

Further, according to the present invention, when the image data is color image data, the gradation correction curve is set for each color component.

According to the present invention, when the image data is color image data, the gradation correction curve is set for each color component, so that appropriate gradation correction processing can be performed for each color component. Before the gradation correction processing, the noise superimposition processing can be performed in a range of an appropriate input density value corresponding to the processing.

Further, according to the present invention, when the image data is color image data, the predetermined correction value range is set for each color component.

According to the present invention, when the image data is color image data, the predetermined range of the correction value is set for each color component, so that an appropriate range of the input density value is set for each color component. Can be subjected to noise superimposition processing.

Further, the present invention is characterized in that the maximum value and the minimum value of the noise added to the image data in the noise superimposition processing are set for each of the predetermined correction value ranges.

According to the present invention, the maximum value and the minimum value of the noise added to the image data by the noise superimposition process are set for each of the predetermined correction value ranges.
An appropriate amount of noise can be superimposed on each of a plurality of appropriate input density value ranges.

[0045]

FIG. 1 is a block diagram showing a configuration of an image forming apparatus 11 including an image processing apparatus 13 according to an embodiment of the present invention. The image forming apparatus 11 is, for example, a digital copying machine using an electrophotographic system or an inkjet system. The image forming apparatus 11 includes the image input apparatus 1
2. The image processing apparatus 13 includes an image processing apparatus 13 and an image output apparatus 14. The image processing apparatus 13 includes an analog / digital (hereinafter, abbreviated as "A / D") conversion unit 21, a shading correction unit 22, an input gradation correction unit 23, Color correction unit 24, image area separation processing unit 25, black generation and under color removal unit 26, spatial filter processing unit 27, noise superimposition processing unit 28, halftone output gradation processing unit 29 curve storage unit 30, correction amount storage unit 31 And an output conversion table storage unit 32.

The A / D converter 21 outputs RGB (R: red, RGB) image data provided from the image input device 12.
(G: green, B: blue) reflectance signals are converted into digital signals. The shading correction unit 22 has an A / D
A shading correction process is performed on the converted reflectance signal. The shading correction processing is performed by the image input device 1
This is performed in order to remove various types of distortion generated in the image signal due to the configurations of the illumination system, the imaging system, and the imaging system. The input tone correction unit 23 performs an input tone correction process on the reflectance signal that has been subjected to the shading correction process. The input tone correction processing is performed by converting the reflectance signal into an image
3 is a process of converting the signal into an easy-to-handle signal. The input tone correction unit 23 may further perform a color balance process on the reflectance signal. The color correction unit 24 converts the RGB density signals into CMY (C: cyan, M: magenta, Y: yellow) density signals, and realizes CMY color signals in the image output device 15 in order to realize faithful color reproduction. A color correction process is performed on the density signal. More specifically, the color correction process is a process for removing color turbidity based on the spectral characteristics of CMY toner and ink containing unnecessary absorption components from the CMY density signal.

The image area separation processing section 25 performs area separation processing on the image data into a character area, a photograph area, a halftone dot area, and the like based on the CMY density signals output from the color correction section 24. The separation result in the image area separation processing unit 25 is supplied to the black generation and under color removal unit 26 and the spatial filter processing unit 27, and may also be supplied to the halftone output gradation processing unit 28. The black generation and under color removal unit 26 performs black generation processing for generating a black color signal based on the CMY color signals constituting the density signal output from the color correction unit 24. The black generation and under color removal unit 26 performs under color removal processing on the CMY color signals. The under color removal processing is processing for subtracting the black color signal generated in the black generation processing from the CMY color signal to obtain a new CMY color signal. As a result of these processes, the CMY density signals are converted into image data composed of CMYK (K: black) color signals. The spatial filter processing unit 27
The CMYK image data obtained by the black generation and under color removal unit 26 is subjected to a spatial filtering process using a digital filter. As a result, the spatial frequency characteristics of the image such as edge enhancement are corrected, so that it is possible to prevent the image output from the image output device 15 from being blurred or having graininess deterioration.

The noise superimposition processing unit 28 is a noise superimposition processing unit that superimposes, as noise, a table value of a noise matrix table prepared in advance or an output value from a random number generation circuit on the CMYK image data after the spatial filter processing. is there. The halftone output tone processing unit 29 is a halftone output tone processing unit that performs a tone correction process and a halftone generation process on the CMYK image data after the noise superimposition process. The halftone generation process is a process that divides an image into a plurality of pixels so that a tone can be reproduced. Further, the halftone output gradation processing section 29 may perform a process of converting the density value of the image data into a dot area ratio which is a characteristic value of the image output device 14. The density signal processed by the halftone output gradation processing section 29 is supplied to the image output device 14.

Hereinafter, the noise superimposition processing section 28 and the halftone output gradation processing section 29 will be further described. In addition,
The noise superimposition process and the halftone generation process for the density values of the CMYK color components differ only in the actual input density value on which the noise is superimposed. Therefore, the noise superimposition process and the halftone process for the density value of any one color component are different. Only the output gradation processing is described.

First, the gradation correction processing in the halftone output gradation processing section 29 will be described. FIG. 2 is a graph showing a reference correction curve 41 and a gradation correction curve 42 used for the gradation correction processing. The horizontal axis indicates the input density value of the image data, and the vertical axis indicates the correction value for the input density value. In FIG.
An 8-bit correction value 0 to 255 is returned (output) for an 8-bit input density value 0 to 255.
When the CMYK image data is supplied to the image processing device 14, the halftone output gradation processing unit 29 stores the reference correction curve 41 and the correction amount storage unit 3 stored in the curve storage unit 30.
A tone correction curve 42 to be actually used is created by using a plurality of correction amounts stored in 1. Based on the created gradation correction curve, the output conversion table storage unit 32 stores the correction values 0 to 255 corresponding to the input density values 0 to 255 as an output conversion table. Even if the image output devices are designed in the same manner, the output characteristics differ due to design tolerances and the like. Further, even if the same device is used, the output characteristics vary depending on the use conditions and the use period of the device. Therefore, by setting this gradation correction curve and output conversion table from the reference correction curve and the correction amount stored in advance, a desired Output characteristics are obtained.

Next, the halftone generation processing performed after the gradation correction processing will be described. The halftone generation processing performs dither processing or error diffusion processing. When performing dither processing to reduce the number of reproduced gradations to 17 by threshold processing using a 4 × 4 threshold matrix shown in FIG. 3, a pseudo contour is generated in an output image. Therefore, of the correction values that are the actual output values, the range of the correction value that generates a false contour in the halftone generation processing is determined in advance, and the input density value corresponding to this range is obtained from the gradation correction curve and the output conversion table.
By superimposing noise on the image data in the range of the obtained input density value, it is possible to suppress a false contour that is easily perceived by human eyes.

As shown in FIG. 4, in the error diffusion processing for generating an intermediate tone by diffusing the error in the target pixel 43 to the peripheral pixels 44, the threshold value is set to 128 and the input density value is set to 128.
If this is the case, the output density value is 255, and if the input density value is less than 128, the output density value is 0. An output image obtained by the error diffusion processing has a portion where graininess is deteriorated. Therefore,
Of the correction values that are the actual output values, a range of correction values at which graininess deteriorates in the halftone generation processing is determined in advance, and an input density value corresponding to this range is obtained from the gradation correction curve and the output conversion table. By superimposing noise on the image data in the range of the obtained input density value, the granularity can be improved. Note that the range of the correction value may be an output value that causes density unevenness.

A method of obtaining a range of the input density value corresponding to the correction value in the predetermined range will be described. Here, the range of the predetermined correction value is m1 or more and m2 or less, and the corresponding range of the input density value is n1 or more and n1 or more.
2 or less. The range from m1 to m2 is determined in advance so that a pseudo contour and density unevenness occur as described above. FIG. 5 is a diagram showing a range of the input density value corresponding to the range of the correction value on the gradation correction curve. From the minimum input density value of the tone correction curve (table) of 0 to a high density, the tone correction curve is sequentially compared with m1 on the tone correction curve.
An input density value that is 1 or more is obtained. If there are a plurality of input density values for which the correction value is m1, the average density value of the corresponding plurality of input density values is set to n1. When calculating the average value, the decimal part is rounded down or rounded up. If the first correction value that is equal to or greater than m1 is greater than m1, the correction value at that time is compared with the correction value corresponding to the next lower input density value, and the input density value closer to m1 is set to n1. I do. Next, when obtaining n2, the input density value n1 + 1 on the gradation correction curve is compared with m2 in order from high density to high density, and an input density value having a table value equal to or more than m2 is obtained first. Thereafter, it can be obtained in the same manner as when n1 is obtained. The noise superimposing unit 28 superimposes noise on the image data whose input density value is in the range of n1 or more and n2 or less, and outputs the resulting data to the halftone output gradation processing unit 29. The image data of the other input density values is output to the halftone output gradation processing unit 29 without any noise superimposition.

A case will be described in which the halftone output tone processing section 29 performs a multi-value dither process for simultaneously performing the tone correction process and the halftone generation process. If the dither matrix size is 2 × 2 multi-value dither processing, each pixel of the 2 × 2 matrix has an output conversion table. This output conversion table is created based on the gradation correction curve in the gradation correction processing.

FIG. 6 is a graph showing a reference correction curve 51 and a gradation correction curve 52 used for the gradation correction processing. The horizontal axis indicates the input density value of the image data, and the vertical axis indicates the correction value for the input density value. In FIG. 6, a 10-bit correction value of 0 to 102 corresponds to an 8-bit input density value of 0 to 255.
Returns 0. Halftone output gradation processing section 29
When the CMYK image data is supplied to the image processing device 14, the CMYK image data is actually used by using the reference correction curve 51 stored in the curve storage unit 30 and the plurality of correction amounts stored in the correction amount storage unit 31. A gradation correction curve 52 to be used is created. Based on this created gradation correction curve,
Correction values 0 to 102 corresponding to input density values 0 to 255
The values up to 0 are stored in the output conversion table storage unit 32 as an output conversion table. Even if the image output devices are designed in the same manner, the output characteristics differ due to design tolerances and the like. Further, even if the same device is used, the output characteristics vary depending on the use conditions and the use period of the device. Therefore, by setting this gradation correction curve and output conversion table from the reference correction curve and the correction amount stored in advance, a desired Output characteristics are obtained.

FIG. 7 is a view showing an output table of the multi-value dither processing of a 2 × 2 matrix size. An output table for the first to fourth pixels of the 2 × 2 multi-value dither processing is created from the gradation correction curve. If the correction value V is 0 ≦ V <255 with respect to the input density values 0 to 255, tb1 = V for the first output table, tb2 = 0 for the second output table, and tb3 = for the third output table. 0, the fourth output table is tb
4 = 0. If 255 ≦ V <510, the first output table is tb1 = 255, and the second output table is tb1 = 255.
b2 = V−255, the third output table is tb3 = 0,
The fourth output table is set to tb4 = 0. 510 ≦ V <
If 765, the first output table is tb1 = 25
5, tb2 = 255 for the second output table, tb3 = V−510 for the third output table, and tb4 = 0 for the fourth output table. If 765 ≦ V ≦ 1020, the first
Is tb1 = 255, the second output table is tb2 = 255, and the third output table is tb3 = 25.
5. The fourth output table is set to tb4 = V−765.

The plurality of output tables generated for each correction value as described above are stored in the output conversion table storage unit 3.
2 and use this to perform multi-value dither processing.

On the other hand, in the noise superimposition processing section 28, the range of the correction value in the multi-value dither processing is set to m1 =
The input density values n1 and n2 respectively corresponding to m1 and m2 are obtained in the same manner as in the case where the tone correction process and the halftone generation process are performed separately, with 530 or more and m2 = 550 or less. The noise superimposition processor 28 superimposes noise on the image data whose input density value is in the range of n1 or more and n2 or less, and outputs the resulting data to the halftone output gradation processor 29. The image data of the other input density values is output as is to the halftone output gradation processing section 29 without superimposing noise.

A plurality of predetermined correction value ranges from m1 to m2 may be set.

When the image data is color image data, a gradation correction curve is set for each color component of CMYK, and a plurality of predetermined correction value ranges from m1 to m2 are set for each color component. You. The range of the input density value corresponding to each may be obtained, and noise may be superimposed on each color component.

Further, when a plurality of correction value ranges are set, the maximum value and the minimum value, which are the amplitudes of noise added to each image data, may be set for each range.
Redundant noise data, for example, cyan is -7 to +
The number of bits may be set for each range as 4 bits so as to give noise up to 7, and as 2 bits for yellow so as to give noise from -1 to +1.

FIG. 8 is a flowchart showing a noise superimposing process which is an image processing method according to the present invention. First, in step s1, the halftone output gradation processing unit 29 stores the reference correction curve 41 and the correction amount storage unit 3 stored in the curve storage unit 30.
The tone correction curve 42 to be actually used is created by using the plurality of correction amounts stored in 1. The correction values 0 to 255 corresponding to the input density values 0 to 255 are created based on the created tone correction curve. To 255 are stored in the output conversion table storage unit 32 as output conversion tables. Next, in step s2, the halftone output gradation processing section 29 obtains n1 or more and n2 or less, which are input density value ranges corresponding to a predetermined correction value range of m1 or more and m2 or less. Proceed to s3. In step s3, the noise superimposition processing unit 28 checks the input density value of each pixel of the input image data and determines whether or not the input density value is in the range of n1 to n2. If it is within the range, proceed to step s4,
Performing a noise superimposition process on the image data and performing step s
Go to 5. If not, the process proceeds to step s5. In step s5, halftone generation processing based on a dither processing method or an error diffusion method is performed. At step s6, it is determined whether or not the processing has been completed for all the pixels. If not, the procedure returns to step s3 to repeat each processing. If all the pixels have been completed, the process ends.

[0063]

As described above, according to the present invention, noise is superimposed on a necessary portion of image data with a simpler circuit configuration, and it is visually preferable and high-quality recording excellent in both resolution and gradation. Can be generated, and a high-quality image can be formed.

Further, according to the present invention, the noise superimposition processing can be applied when the gradation correction processing and the halftone generation processing are performed separately.

According to the present invention, the noise superimposition processing can be applied when the gradation correction processing and the halftone generation processing are performed simultaneously.

Further, according to the present invention, it is possible to apply the noise superimposition processing in the case of the multi-value dither processing, and it is possible to apply the pseudo contour generated around the switching of the pixel where the dot becomes larger as the density becomes higher in the dither matrix. Can be reduced.

Further, according to the present invention, the processing speed for obtaining the range of the input density value on which the noise is superimposed can be increased.

Further, according to the present invention, it is possible to perform a noise superimposing process on a range of a plurality of input density values.

Further, according to the present invention, it is possible to perform appropriate gradation correction processing for each color component, and to perform noise superimposition processing in an appropriate input density value range before the gradation correction processing. Can be.

Further, according to the present invention, an appropriate amount of noise can be superimposed on each of a plurality of appropriate input density value ranges.

Further, according to the present invention, an appropriate amount of noise can be superimposed on an appropriate input density value range, and unnecessary bits can be reduced.

[Brief description of the drawings]

FIG. 1 is an image processing apparatus 13 according to an embodiment of the present invention.
FIG. 2 is a block diagram illustrating a configuration of the image forming apparatus 11 including the image forming apparatus.

FIG. 2 is a graph showing a reference correction curve 41 and a gradation correction curve 42 used for gradation correction processing.

FIG. 3 is a diagram illustrating a 4 × 4 threshold matrix of dither processing in halftone generation processing.

FIG. 4 is a diagram illustrating the concept of error diffusion processing in halftone generation processing.

FIG. 5 is a diagram showing a range of an input density value corresponding to a range of a correction value on a gradation correction curve.

FIG. 6 is a graph showing a reference correction curve 51 and a gradation correction curve 52 used for gradation correction processing.

FIG. 7 is a diagram illustrating an output table of a 2 × 2 matrix size multi-value dither process in the halftone output gradation process.

FIG. 8 is a flowchart illustrating a noise superimposing process which is an image processing method according to the present invention.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 11 Image forming apparatus 12 Image input apparatus 13 Image processing apparatus 14 Image output apparatus 21 A / D conversion part 22 Shading correction part 23 Input gradation correction part 24 Color correction part 25 Image area separation processing part 26 Black generation under color removal part 27 Spatial filter processing unit 28 noise superimposition processing unit 29 halftone output gradation processing unit 30 curve storage unit 31 correction amount storage unit 32 output conversion table storage unit 41,51 reference correction curve 42,52 gradation correction curve

──────────────────────────────────────────────────続 き Continued on the front page (51) Int.Cl. ⁷ Identification symbol FI Theme coat ゛ (Reference) H04N 1/46 H04N 1/46 Z F-term (Reference) 5B057 AA11 CA01 CA08 CA12 CB01 CB07 CB12 CC01 CE11 CE13 CE16 CH07 CH18 DB02 DB06 DB08 5C077 LL02 LL19 MP01 MP08 NN04 PP15 PP33 PP39 PQ08 PQ11 PQ23 RR09 5C079 HB03 LA12 LC05 NA02 NA04 NA05 NA09

Claims (20)

[Claims] 1. A halftone output gradation processing unit for performing a gradation correction process and a halftone generation process for setting a correction value corresponding to an input density value of image data, and a noise superimposition processing unit for superimposing noise on image data. And a noise superimposing unit configured to superimpose noise on image data in a range of input density values corresponding to a correction value in a predetermined range. 2. The image processing apparatus according to claim 1, wherein the halftone output gradation processing means performs a halftone generation process after performing a gradation correction process. 3. An image processing apparatus according to claim 1, wherein said halftone output tone processing means performs a tone correction process and a halftone generation process simultaneously. 4. An image processing apparatus according to claim 3, wherein said halftone output gradation processing means simultaneously performs a gradation correction process and a halftone generation process by multi-value dither processing. 5. The range of the predetermined correction value is m1.
As described above, when the input density value is set to m2 or less and the corresponding input density value range is set to n1 or more and n2 or less, the tone correction curve used for the tone correction process is examined in order from the minimum input density value to the high density. Then, n1 corresponding to m1 is obtained, and n2 corresponding to m2 is obtained by sequentially examining from the input density value n1 + 1 to high density, or the tone correction curve is sequentially examined from the maximum input density value to low density. 5. An apparatus according to claim 1, further comprising means for obtaining n2 corresponding to m2 by going forward and sequentially examining from input density value n2-1 to low density to obtain n1 corresponding to m1. The image processing device according to any one of the above. 6. The image processing apparatus according to claim 1, wherein a plurality of predetermined correction value ranges are set. 7. The image processing apparatus according to claim 1, wherein when the image data is color image data, a gradation correction curve is set for each color component. . 8. The apparatus according to claim 1, wherein when the image data is color image data, the predetermined correction value range is set for each color component. The image processing apparatus according to any one of the preceding claims. 9. The apparatus according to claim 6, wherein the maximum value and the minimum value of the noise added to the image data by the noise superimposing processing means are set for each of the predetermined correction value ranges. The image processing device according to any one of the above. 10. The apparatus according to claim 6, wherein the number of bits of the noise data added to the image data by the noise superimposition processing means is set for each of the predetermined correction value ranges. The image processing device according to one of the above. 11. An image input device for reading an original to obtain image data, an image processing device according to any one of claims 1 to 10, and an image output device for outputting processed image data. An image forming apparatus comprising: 12. A tone correction process for setting a correction value corresponding to an input density value of image data, a halftone output tone process for performing a halftone generation process, and a noise superimposition process for superimposing noise on the image data. In the image processing method to be performed, in the noise superimposing process, the noise is superimposed on image data in an input density value range corresponding to a correction value in a predetermined range. 13. The image processing method according to claim 12, wherein in the halftone output gradation processing, a halftone generation processing is performed after performing a gradation correction processing. 14. The image processing method according to claim 12, wherein in the halftone output gradation process, a gradation correction process and a halftone generation process are performed simultaneously. 15. The image processing method according to claim 14, wherein in the halftone output gradation processing, a gradation correction processing and a halftone generation processing are simultaneously performed by multi-value dither processing. 16. The range of the predetermined correction value is m
When the range of the input density value is set to n1 or more and n2 or less, the tone correction curve used for the tone correction process is examined in order from the minimum input density value to the high density. Then, n1 corresponding to m1 is obtained, and n2 corresponding to m2 is obtained by sequentially examining from the input density value n1 + 1 to the high density, or the tone correction curve is sequentially obtained from the maximum input density value to the low density. 16. The method according to claim 12, wherein n2 corresponding to m2 is obtained by checking, and n1 corresponding to m1 is obtained by sequentially checking from input density value n2-1 to low density. The image processing method according to any one of the above. 17. The range of the predetermined correction value,
17. A method according to claim 12, wherein a plurality of parameters are set.
The image processing method according to any one of the above. 18. The image processing method according to claim 12, wherein when the image data is color image data, a gradation correction curve is set for each color component. . 19. The apparatus according to claim 12, wherein when the image data is color image data, the predetermined correction value range is set for each color component. The image processing method described in the above. 20. The apparatus according to claim 17, wherein a maximum value and a minimum value of noise added to the image data in the noise superimposing process are set for each of the predetermined correction value ranges. The image processing method according to any one of the above.