JP2002158807A - Image simulation device and method, and computer- readable storage medium storing program for executing the method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an image simulation device which is capable of accurately predicting the reflectance distribution of an image outputted from an image recording device. SOLUTION: This image simulation device is equipped with a dot position calculating means which calculates the position of a recorded dot, an average level detecting means which detects the average level of all inputted image data or a part of the inputted image data with the central focus on the target pixels, a basic reflectance data generating means which generates the reflectance data of the target pixel from the basic reflectance data corresponding to the inputted image data and average level, and a reflectance distribution means which calculates the reflectance distribution of the outputted image of the image output device on the basis of the generated dot reflectance data and inputted image data.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a simulation apparatus, and more particularly to an image for predicting a reflectance distribution of an image to be output from an image output apparatus to be evaluated in order to quantitatively evaluate the image quality of the image output apparatus. The present invention relates to a simulation device.

[0002]

2. Description of the Related Art Image quality is generally evaluated by the observer's subjectivity and is usually qualitative, but attempts to objectively and quantitatively evaluate this subjective and qualitative image quality have been performed for a long time. Has been made several times. As one of the methods, a method of quantifying image noise, for example, roughness due to density unevenness occurring in an image which should be uniform in density, which is disclosed in Japanese Patent Application Laid-Open No. 1-286084, discloses a luminance distribution of an optically read image to be evaluated. After two-dimensional Fourier transform
The dimensioned values are corrected by visual spatial frequency characteristics, and the integrated values are used as image noise. This is intended to improve the correspondence between the subjective roughness and the objective evaluation amount by weighting the frequency components that are easily noticeable in the noise. In this way, the quantitative evaluation method of image quality generally improves the correlation between subjective image quality and objective physical quantity by correcting the measured physical quantity with human visual characteristics. A similar method is used to evaluate the jaggedness (jaggies) and sharpness of a line. Also, Japanese Patent Application Laid-Open
No. 23191 also reads an image to be evaluated with a general-purpose scanner and obtains image noise.

[0003] The development of the above-described image quantification technique has made it possible to quantitatively evaluate the image quality. However, for the evaluation, the image to be evaluated is scanned with a scanner or microdensitometer. It is necessary to read optically with an image input device. Therefore, since high-precision and high-resolution reading is required for evaluation, a sufficient speed cannot be obtained in the image capturing step, and image quality evaluation often takes a very long time. In addition, a target image recording apparatus is required for the evaluation, and it is indispensable in product development that the development of the recording apparatus has progressed to some extent so that an image can be output. Therefore, it is impossible to predict the image quality of the recording device at the beginning of development. For example, when developing an image processing method for an image recording device under development, it is not possible to evaluate the quality of the image processing method even if the image recording device is started at the same time as developing the image recording device. I was Also, in order to check how the image quality can be improved if the specifications of the developed recording device are partially changed (for example, the recording density of the recording device is changed), it is necessary to actually change the recording device whose specifications have been changed. In this way, a prototype is produced and evaluated, which takes a very long time.

Japanese Patent Application Laid-Open No. 2000-22858 discloses that the reflectivity of an output image output from an image recording apparatus is not based on actual image output but on the basis of dot reflectivity distribution data of the image recording apparatus to be evaluated. This is for calculating the distribution, and enables the image quality of an image recording apparatus such as a printer to be predicted and evaluated in a short time.

[0005]

[Problems to be solved by the invention]

However, the recording characteristics of an electrophotographic output device are not stable. For example, when the same dot image is output by changing the dot arrangement cycle, the dot arrangement becomes smaller as the dot arrangement cycle becomes smaller. In some cases, the strength or size tends to increase. Although such a phenomenon varies depending on the developing method and the like, as a result of experiments, this tendency was relatively remarkable in an output device such as a two-component magnetic brush developing method. FIG. 15 is a diagram showing the dot shape of the output dot.
It is an output image of an isolated one dot with a pixel cycle of 2 * 12, 8 * 8, 4 * 4. The above tendency is observed even in a dot arrangement cycle of 10 pixels or more in which latent image overlap is unlikely to occur, and the average exposure amount given on the photoconductor results in the same dot pattern during image formation. Is considered to have affected the toner adhesion amount and the like. In such an output device, since the output image differs depending on the average exposure amount, that is, the average level of the input image data, even in the same image pattern, the reflectance distribution of the output image is not obtained by the method using the single dot reflectance distribution data as described above. Is difficult to calculate accurately.

An object of the present invention is to solve these problems, and an object of the present invention is to provide an image simulation apparatus capable of predicting a reflectance distribution of an image to be output from an image recording apparatus with high accuracy. I do.

[0008]

In order to solve the above problems, an image simulation apparatus for simulating an output image of an image output apparatus includes a dot position calculating means for calculating a dot position to be recorded, and an input image data. Average level detecting means for detecting the average level of the whole of the input image data or a part of the input image data centering on the pixel of interest, and the dot reflectance data of the pixel of interest according to the input image data and the average level. And a reflectance distribution means for calculating a reflectance distribution of an output image of the image output device from the generated dot reflectance data and the input image data. .
Therefore, it is possible to realize an image simulation apparatus capable of calculating a highly accurate reflectance distribution regardless of the characteristics of an input image. Further, it is possible to easily perform a desired image quality evaluation using the reflectance distribution calculated without actually outputting an image.

The dot position calculating means is configured to calculate the dot position to be recorded from the recording density of the image output device and the dot position fluctuation data, so that the effect of the dot position fluctuation on the output image is evaluated. This makes it possible, and also makes it possible to more accurately predict the reflectance distribution of an image that will be output from the image recording apparatus, including dot position fluctuations. Further, even in an image recording apparatus having a large variation in the output image quality (the repetition reproducibility is not good) or an image recording apparatus having a noisy output image (the S / N ratio is not good), the dot position variation is not included in the output image. It is possible to accurately predict the influence.

Further, by providing a dot reflectance variation means for varying the generated dot reflectance data of the pixel of interest based on the dot reflectance variation data, it is possible to evaluate the effect of dot variations on the output image. It is possible to evaluate the effect of higher accuracy, including higher accuracy, on the output image, including the higher accuracy, and to reflect the image that will be output from the image recording device. The rate distribution can be predicted with higher accuracy, including the variation in dots.

Further, by providing a means for performing a convolution operation on the calculated reflectance distribution of the output image of the image output device using a predetermined response function to obtain a final reflectance distribution, for example, It is possible to accurately predict the reflectance distribution of an image including image quality deterioration such as blur and blur output from an image recording apparatus such as an electrophotographic recording apparatus that forms an image by a plurality of image forming processes such as transfer and fixing. It becomes possible.

According to another aspect of the present invention, there is provided an image simulation method for simulating an output image of an image output device, a dot position calculating step of calculating a dot position to be recorded; An average level detecting step of detecting an average level of a part of the input image data, and generating basic reflectance data for generating dot reflectance data of a target pixel from the basic reflectance data according to the input image data and the average level And a reflectance distribution calculating step of calculating a reflectance distribution of an output image of the image output device from the selected dot reflectance data and the input image data. Therefore, it is possible to perform an image simulation capable of calculating a highly accurate reflectance distribution irrespective of the characteristics of an input image, and to easily obtain a desired reflectance distribution using a reflectance distribution calculated without actually outputting an image. Image quality evaluation can be performed.

In the dot position calculating step, the effect of the dot position fluctuation on the output image can be evaluated by calculating the dot position to be recorded from the recording density of the image output device and the dot position fluctuation data. And the reflectance distribution of an image that will be output from the image recording apparatus can be predicted with higher accuracy, including dot position fluctuation. Further, even in an image recording apparatus having a large variation in the output image quality (the repetition reproducibility is not good) or an image recording apparatus having a noisy output image (the S / N ratio is not good), the dot position variation is not included in the output image. It is possible to accurately predict the influence.

Further, by including a dot reflectance variation step of varying the generated dot reflectance data of the target pixel based on the dot reflectance variation data, it is possible to evaluate the effect of dot variations on the output image. It is possible to evaluate the effect of higher accuracy, including higher accuracy, on the output image, including the higher accuracy, and to reflect the image that will be output from the image recording device. The rate distribution can be predicted with higher accuracy, including the variation in dots.

Further, the method includes a step of performing a convolution operation on the calculated reflectance distribution of the output image of the image output device by using a predetermined response function to obtain a final reflectance distribution. It is possible to accurately predict the reflectance distribution of an image including image quality deterioration such as blur and blur output from an image recording apparatus such as an electrophotographic recording apparatus that forms an image by a plurality of image forming processes such as transfer and fixing. It becomes possible.

Another aspect of the invention is a computer-readable storage medium storing a program for executing the above-described image simulation method. Therefore, an apparatus for constructing an image simulation system can be generally used without changing an existing system.

[0017]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An image simulation apparatus according to the present invention comprises a dot position calculating means for calculating a dot position to be recorded, and an average of the entire input image data or a part of the input image data centered on a pixel of interest. Average level detection means for detecting the level; basic reflectance data generation means for generating dot reflectance data of the pixel of interest from the basic reflectance data according to the input image data and the average level; and the generated dot reflectance data. And a reflectance distribution means for calculating a reflectance distribution of an output image of the image output apparatus from the input image data and the input image data.

[0018]

FIG. 1 is a block diagram showing the configuration of an image simulation apparatus according to a first embodiment of the present invention. In FIG. 1, an image simulation apparatus 1 according to the present embodiment includes:
Image density input unit 11, dot position calculation unit 12, reflectance distribution calculation unit 13, input image data input unit 14, average level storage unit 15, reflectance data generation unit 16, and basic reflectance data storage And a reflectance distribution output unit 18. In the case of a binary printer, the input image data input by the input image data input unit 14 is 0 or 255 representing whether the dot is ON or OFF.
This is a data string (or a data string of 0 or 1), and in the case of a multi-value printer, it is a data string of usually 8 bits (0 to 255). The recording density of a recording apparatus is generally
(Dotper inch), and the dot position calculating means determines the position where each dot is to be printed (equal intervals in both the x and y directions at the pitch of the reciprocal of the recording density; see FIG. 2). Is calculated. Here, an example of the basic reflectance data indicating the reflectance distribution of the dots is shown in FIG. In the figure, the actual data is in the form of a function (for example, f
(R) or f (x, y)) or 2D LUT
(Lookup table) and stored. These data are prepared in advance based on the output image measurement result or prediction / estimation. The average level is the average level of image data within a range of about ten to several tens of pixels (rectangular, circular, elliptical, etc.) around the target pixel, and the lower limit when all image data within the range is 0 (OFF). (0), and when all are 255 (FULL ON), take the upper limit (255). These average level detections are basically performed at least when the target pixel itself is not OFF (0), but the average level of the entire input image data is used as the average level of each target pixel without detecting the average level for each pixel. You can also. The basic reflectance data described above is
It is dot reflectance data at an average level of a certain reference, and when the average level of the pixel of interest is higher than the reference average level, the basic reflectance data is set so that at least one of its intensity and size is larger, If the average level of the target pixel is smaller than the reference average level,
At least one of the intensity and size of the basic reflectance data is set to be smaller.

A specific example of generating dot reflectance data will be described below. FIG. 4 shows an average reflectance distribution obtained by averaging the reflectance distribution of each isolated one dot shown in FIG. The parameters are 4 * 4 pixels, 8 * 8 pixels, 12 * 12 pixels, and 16 * 16 pixel periods in the dot array period, and the average level of the image data at this time is 255 / (4 *
4) 255 / (8 * 8), 255 / (12 * 12),
255 / (16 * 16). Then, when the minimum value Rmin of each average reflectance distribution is plotted against the average level, the result is as shown in FIG. 5, and the minimum value of the average dot reflectance decreases as the average level of the input image data increases. . Here, the relationship between Rmin and the average level is formulated (in this example, Rmin = c + d * log
By approximation in the form of [average level]), the value of Rmin can be determined for an arbitrary average level. Then, any one of the above four types of average reflectance distribution or a formula thereof is defined as basic reflectance data, and the basic reflectance data is determined according to the value of Rmin determined by the average level (of each pixel of interest) of the evaluated image. The dot reflectance data of each pixel of interest is generated by expanding and contracting the reflectance data in the vertical direction.

FIG. 2 is a schematic diagram showing an example of an image when dots are recorded. The position where the dot is printed is obtained from the printing density of the printing apparatus, and the black dots in the figure indicate the positions where the dots should be printed. Whether or not a dot is recorded at the position where the dot is recorded is determined by the input image data described above, and the reflectance data generated at the target pixel is formed at the calculated dot position (pasted as electronic data) ). In the reflectance distribution calculation unit 13 of FIG. 1, the pitch is finer than the recording density (FIG. 2).
, The reflectance at each point is calculated. For example, when obtaining the reflectance of the point A, the distance (or coordinates) from the center of the dot A which is closer is obtained by substituting the distance (or coordinates) into the dot reflectance data formula. Further, at a point such as a point B which is affected by a plurality of dots (dots A and B in this example), the reflection is performed by multiplying the reflectance according to the distance (or coordinate) from the center of each dot. Find the rate. In this way, the reflectance of each point is sequentially obtained, and the reflectance distribution of the image is obtained. If the average value of the reflectance distribution is determined, the image density can be determined, and the gamma characteristic and the gradation density characteristic of the printing apparatus can be evaluated. Also,
A simple image evaluation can be made by graphing the reflectance distribution or converting the reflectance signal into a luminance signal corresponding to the reflectance and displaying it on a CRT monitor. By inputting the calculated data of the reflectance distribution of the image to the image quality evaluation device (or program), a desired image quality evaluation amount can be calculated. For example, various image quality evaluation methods such as noise evaluation of an image and obtaining an MTF from the reflectance distribution of the line pair image shown in FIG. 5 can be applied.

When the reflectance of the non-image portion (background portion), that is, the reflectance of the recording paper cannot be approximated to 1.0, the reflectance Rp of the image recording medium (paper or the like) is set to Rp (see FIG. 3). First, the dot reflectance data is normalized to data obtained by dividing the dot reflectance data by Rp, and the reflectance distribution data of the output image is calculated using the normalized values as described above. , Continuous reflectance distribution data can be obtained. Further, the physical quantity of the output image does not need to be limited to the reflectance, and any physical quantity such as (optical) density and lightness can be used. Further, the same applies to the dot reflectance data, and distribution data of an arbitrary physical quantity such as density and brightness can be used. At this time, the method of superimposing the physical quantity in the overlapping portion of the dots is set according to the selected physical quantity. You.

FIG. 6 is a block diagram showing the configuration of an image simulation apparatus according to a second embodiment of the present invention. In the figure, the same reference numerals as those in FIG. 1 indicate the same components. As different components, the image simulation apparatus 1 of the present embodiment includes a dot position variation data storage unit 19,
A dot reflectance variation data storage unit 20, a dot reflectance data variation unit 21, a dot reflectance data generation unit 22,
Convolutions 23 and 24 and response function units 25 and 2
6 is included. In this embodiment, the first
The reflectance distribution is calculated in the same procedure as that of the embodiment, but dot position variation data as variation data of recording characteristics is given, and the dot position is calculated based on the dot position variation data and the recording density of the image recording apparatus. It is configured to: By giving as data the amount of change in each dot position generated due to the mechanical accuracy and control accuracy of the printing apparatus, dots are printed at positions shifted from positions originally determined by the printing density as shown in FIG. In this case, it is possible to calculate the reflectance distribution. Therefore, it is possible to easily and quantitatively evaluate the influence of the dot displacement on the output image by simulation. More specifically, in the case of a laser printer, the dot position variation data is data such as a photoconductor speed variation and a scanning position shift due to a tilt of the rotary polygon mirror. Based on these dot position variation data, the amount of deviation from the basic dot position (the dot position to be recorded) determined from the recording density is calculated for each dot, and added to the basic dot position to obtain the dot including the variation. The position is calculated. Here, FIG. 8 shows the configuration of the dot position calculation unit 12 when the dot position change data is given as the spatial frequency characteristics of the dot position change. A white noise is generated, and the white noise is Fourier-transformed by a Fourier transformer (hereinafter abbreviated as FFT) 123 and converted into a frequency space. In the filtering 124, the data after the Fourier transform is multiplied by the spatial frequency characteristic of the dot position variation, and then the Fourier inverse transformer (hereinafter, inverse FF) is used.
Noise (fluctuation) having the desired spatial frequency characteristic by performing Fourier inverse transform using 125)
Is generated. This is added by the adder 126 to the basic dot position calculated by the basic dot position calculation unit 122 from the recording density stored in the recording density storage unit 121 by the adder 126, so that each of the dots having the dot position variation of the spatial frequency characteristic input is obtained. The position is calculated.

FIG. 9 is a characteristic diagram showing an example of the spatial frequency characteristic of the dot position variation given as the dot position variation data. It is composed of various spatial frequency components such as a random dot position error due to a processing error (C in the figure) and low-frequency unevenness (A in the figure) of the image carrier (photoconductor in electrophotography). in this way,
By giving the dot position variation data as the spatial frequency characteristics, it is possible to more accurately predict the reflectance distribution of the image output from the image recording apparatus. Also,
By simulating the spatial frequency characteristics of the dot position variation by changing the shape and size of the dot, it is possible to easily evaluate the qualitative and quantitative effects of the dot position variation on the output image.

According to the present invention, a dot reflectivity data changing means (step) for changing the dot reflectivity data selected by the dot reflectivity data selecting means (step) by the dot reflectivity change data is added. The configuration is such that the reflectance distribution of the output image is calculated from the dot reflectance data to which the fluctuation is added, the image input data, and the neighboring pixel data. The selected dot reflectance data is given a variation in at least one of its size, intensity, shape, and the like by the dot reflectance variation data. For example, in a laser printer, the reflectance distribution of dots formed by toner dusting or falling off during the image forming process varies.

In this embodiment, it is possible to input these variations in the dot reflectance distribution. As the dot reflectance variation data, for example, dot size, intensity,
In the example of FIG. 10, the dot size variation amount 20 in the dot reflectance variation data storage unit 20 is used.
-1 and the dot intensity variation 20-2 (relative value or absolute value) are given as dot reflectance variation data (see FIGS. 11 and 12). Dot reflectance data fluctuation unit 2
In 1, the random number generation units 21-1 and 21-2 generate uniform random numbers or normal random numbers (random numbers that follow a normal distribution), and the generated random numbers are represented by a dot size variation 20-1 and a dot intensity variation 20-. The multiplication level is multiplied by 2 to sequentially set the fluctuation level for changing the input dot reflectance data. On the other hand, the dot reflectivity data input to the dot reflectivity distribution data change unit 21 is subjected to a predetermined operation according to the change level to add a predetermined change, and is sent to the reflectivity distribution calculation unit. These are sequentially repeated for each target pixel to calculate the reflectance distribution of the image as described in the first embodiment. As described above, it is possible to calculate the reflectance distribution when recording is performed with dots whose reflectance distribution shape fluctuates at each dot, and it is possible to predict the reflectance distribution with higher accuracy, and to determine the reflectance distribution of the dots. It is possible to quantitatively evaluate the effect of the change on the image.

In the second embodiment, a convolution operation (convolution integration) is applied to the calculated reflectance distribution of the image as shown in FIG.
In the convolution calculation units 23 and 24. For example, in the case of an image recording apparatus such as an electrophotographic recording apparatus that forms an image by a plurality of processes such as development, transfer, and fixing, response function units 25 and 2 corresponding to the deterioration characteristics of each process.
For example, a convolution operation is sequentially performed on the reflectance distribution after the development using the response function in 5 to obtain a reflectance distribution to which the deterioration characteristic of each process is added. Of course, the response functions indicating these deterioration characteristics may be combined into one and added to the reflectance distribution input to the convolution calculation units 23 and 24. Although an example of an electrophotographic recording apparatus is shown here, the recording apparatus is not limited to this, and optical dots that blur an image recorded on paper due to scattering of light inside the recording paper may be used. It can be applied to the case where the influence of the gain is considered.

FIG. 13 shows an example in which the deterioration characteristics in the transfer and fixing processes are given as spatial frequency characteristics. The input reflectance distribution is converted into a spatial frequency space by the FFT 28, and is multiplied by a predetermined spatial frequency characteristic. , Inverse FFT2
9 to obtain a reflectance distribution to which a deterioration characteristic is added.

FIG. 14 is a block diagram showing the system configuration of the present invention. That is, the figure shows hardware constructed from a microprocessor or the like that executes software by the image simulation method in the above embodiment. In the figure, an image simulation system is an interface (hereinafter abbreviated as I / F) 3
1, CPU 32, ROM 33, RAM 34, display device 3
5. Hard disk 36, keyboard 37 and CD-R
The OM drive 38 is included. A general-purpose processing device is prepared, and a program for executing the image simulation method of the present invention is stored in a readable storage medium such as the CD-ROM 39. Furthermore, I / F3
A control signal is input from an external device via the control unit 1, and a program of the present invention is started by a command from an operator or automatically by the keyboard 37. Then, the CPU 32 performs image simulation control processing according to the above-described image simulation method according to the program, stores the processing result in a storage device such as the RAM 34 or the hard disk 36, and outputs the result to the display device 35 or the like as necessary. As described above, by using the medium on which the program for executing the image simulation method of the present invention is recorded, an apparatus for constructing an image simulation system can be generally used without changing an existing system.

The present invention is not limited to the above embodiment, and needless to say, various modifications and substitutions can be made within the scope of the claims.

[0030]

As described above, the image simulation apparatus for simulating the output image of the image output apparatus is provided with a dot position calculating means for calculating a dot position to be recorded, and an entire input image data or a pixel of interest. Average level detection means for detecting an average level of a part of the input image data at the center, and basic reflectance data for generating dot reflectance data of a pixel of interest from the basic reflectance data according to the input image data and the average level It is characterized by comprising a generating means and a reflectance distribution means for calculating a reflectance distribution of an output image of the image output device from the generated dot reflectance data and the input image data. Therefore, it is possible to realize an image simulation apparatus capable of calculating a highly accurate reflectance distribution regardless of the characteristics of an input image. Further, it is possible to easily perform a desired image quality evaluation using the reflectance distribution calculated without actually outputting an image.

Further, the dot position calculating means is configured to calculate the dot position to be recorded from the recording density of the image output device and the dot position fluctuation data, so that the influence of the dot position fluctuation on the output image can be evaluated. This makes it possible, and also makes it possible to more accurately predict the reflectance distribution of an image that will be output from the image recording apparatus, including dot position fluctuations. Further, even in an image recording apparatus having a large variation in the output image quality (the repetition reproducibility is not good) or an image recording apparatus having a noisy output image (the S / N ratio is not good), the dot position variation is not included in the output image. It is possible to accurately predict the influence.

Further, by providing a dot reflectivity changing means for changing the generated dot reflectivity data of the target pixel based on the dot reflectivity change data, it is possible to evaluate the influence of dot variations on an output image. It is possible to evaluate the effect of higher accuracy, including higher accuracy, on the output image, including the higher accuracy, and to reflect the image that will be output from the image recording device. The rate distribution can be predicted with higher accuracy, including the variation in dots.

Further, by providing means for obtaining a final reflectance distribution by performing a convolution operation on the calculated reflectance distribution of the output image of the image output device using a predetermined response function, It is possible to accurately predict the reflectance distribution of an image including image quality deterioration such as blur and blur output from an image recording apparatus such as an electrophotographic recording apparatus that forms an image by a plurality of image forming processes such as transfer and fixing. It becomes possible.

As another invention, according to an image simulation method for simulating an output image of an image output device, a dot position calculation step of calculating a dot position to be recorded, and a process of calculating the entire input image data or the center of a pixel of interest. An average level detecting step of detecting an average level of a part of the input image data, and generating basic reflectance data for generating dot reflectance data of a target pixel from the basic reflectance data according to the input image data and the average level And a reflectance distribution calculating step of calculating a reflectance distribution of an output image of the image output device from the selected dot reflectance data and the input image data. Therefore, it is possible to perform an image simulation capable of calculating a highly accurate reflectance distribution irrespective of the characteristics of an input image, and to easily obtain a desired reflectance distribution using a reflectance distribution calculated without actually outputting an image. Image quality evaluation can be performed.

In the dot position calculating step, the effect of the dot position fluctuation on the output image can be evaluated by calculating the dot position to be recorded from the recording density of the image output device and the dot position fluctuation data. And the reflectance distribution of an image that will be output from the image recording apparatus can be predicted with higher accuracy, including dot position fluctuation. Further, even in an image recording apparatus having a large variation in the output image quality (the repetition reproducibility is not good) or an image recording apparatus having a noisy output image (the S / N ratio is not good), the dot position variation is not included in the output image. It is possible to accurately predict the influence.

Further, by including a dot reflectivity change step of changing the generated dot reflectivity data of the target pixel based on the dot reflectivity change data, it is possible to evaluate the influence of dot variations on an output image. It is possible to evaluate the effect of higher accuracy, including higher accuracy, on the output image, including the higher accuracy, and to reflect the image that will be output from the image recording device. The rate distribution can be predicted with higher accuracy, including the variation in dots.

Further, the method includes a step of performing a convolution operation on the calculated reflectance distribution of the output image of the image output device using a predetermined response function to obtain a final reflectance distribution. It is possible to accurately predict the reflectance distribution of an image including image quality deterioration such as blur and blur output from an image recording apparatus such as an electrophotographic recording apparatus that forms an image by a plurality of image forming processes such as transfer and fixing. It becomes possible.

Another feature of the present invention is a computer-readable storage medium storing a program for executing the above-described image simulation method. Therefore, an apparatus for constructing an image simulation system can be generally used without changing an existing system.

[Brief description of the drawings]

FIG. 1 is a block diagram illustrating a configuration of an image simulation apparatus according to a first embodiment of the present invention.

FIG. 2 is a schematic diagram illustrating an example of an image when dots are recorded.

FIG. 3 is a diagram illustrating an example of basic reflectance data indicating a reflectance distribution of dots.

FIG. 4 is a diagram showing an average reflectance distribution obtained by averaging the reflectance distribution of each isolated one dot.

FIG. 5 is a diagram showing a reflectance distribution of a line pair image.

FIG. 6 is a block diagram illustrating a configuration of an image simulation apparatus according to a second embodiment of the present invention.

FIG. 7 is a schematic diagram showing a state in which dot positions are shifted in consideration of a variation amount of each dot position.

FIG. 8 is a block diagram illustrating a configuration of a dot position calculation unit when dot position change data is given as a spatial frequency characteristic of dot position change.

FIG. 9 is a characteristic diagram illustrating an example of a spatial frequency characteristic of a dot position variation given as dot position variation data.

FIG. 10 is a block diagram showing a part of the configuration of a second embodiment in which dot reflectance variation data is taken into account.

FIG. 11 is a characteristic diagram illustrating a reflectance distribution in consideration of a dot size variation amount.

FIG. 12 is a characteristic diagram showing a reflectance distribution in consideration of a dot intensity variation.

FIG. 13 is a block diagram showing a configuration for converting a reflectance distribution into a spatial frequency space.

FIG. 14 is a block diagram showing a system configuration of the present invention.

FIG. 15 is a diagram illustrating a dot shape of an output dot.

[Explanation of symbols]

REFERENCE SIGNS LIST 1 image simulation apparatus 11 recording density storage unit 12 dot position calculation unit 13 reflectance distribution calculation unit 14 input image data input unit 15 average level storage unit 16 reflectance data generation unit 17; basic reflectance data storage section; 18; reflectance distribution output section; 19; dot position variation data storage section; 20; dot reflectance variation data storage section; 21; dot reflectance data variation section; 22; dot reflection Rate data generators 23 and 24; convolution calculators 25 and 26; response function unit 27; reflectance distribution calculation selector 28; FFT 29; inverse FTT.

Claims (9)

[Claims] 1. An image simulation apparatus for simulating an output image of an image output apparatus, comprising: a dot position calculating means for calculating a dot position to be recorded; and input image data centered on the entire input image data or a pixel of interest. Average level detection means for detecting a part of the average level, and basic reflectance data generation means for generating dot reflectance data of the target pixel from the basic reflectance data according to the input image data and the average level. And a reflectance distribution means for calculating a reflectance distribution of an output image of the image output device from the dot reflectance data and the input image data. 2. The image simulation apparatus according to claim 1, wherein said dot position calculation means is configured to calculate a dot position to be recorded from a recording density of an image output device and dot position variation data. 3. The image simulation apparatus according to claim 1, further comprising a dot reflectance changing unit that changes the generated dot reflectance data of the target pixel based on the dot reflectance variation data. 4. A means for obtaining a final reflectance distribution by performing a convolution operation on the calculated reflectance distribution of the output image of the image output device using a predetermined response function. The image simulation device according to any one of the above. 5. An image simulation method for simulating an output image of an image output device, comprising: a dot position calculation step of calculating a dot position to be recorded; and input image data centered on the entire input image data or a pixel of interest. An average level detecting step of detecting a part of the average level, and a basic reflectance data generating step of generating dot reflectance data of the pixel of interest from the basic reflectance data according to the input image data and the average level. A reflectance distribution calculating step of calculating a reflectance distribution of an output image of the image output device from the obtained dot reflectance data and the input image data. 6. The image simulation method according to claim 5, wherein said dot position calculation step calculates a dot position to be recorded from a recording density of an image output device and dot position variation data. 7. The image simulation method according to claim 5, further comprising a dot reflectance changing step of changing the generated dot reflectance data of the target pixel based on the dot reflectance variation data. 8. A step of performing a convolution operation on the calculated reflectance distribution of the output image of the image output device using a predetermined response function to obtain a final reflectance distribution. The image simulation method according to any one of the above. 9. A computer-readable storage medium storing a program for executing the image simulation method according to claim 5.