JP2007208786A - Generation of dither matrix - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide optimization technology of a dither matrix with paying attention to robustness. <P>SOLUTION: In a method of generating the dither matrix for storing a plurality of thresholds for determining formation states of dots to each printing pixel of printed images which should be formed on printed media according to input image data in each element, the method determines the matrix evaluation values which are evaluation values, showing the correlation with a plurality of goal states that are supposed having difference of at least either the observation distance or the printing resolution for each candidate of the stored elements, based on the formation states of dots supposed by each candidate of the stored elements of target threshold for evaluation among the plurality of thresholds and determines the stored element of the target threshold from among the candidates, based on the matrix evaluation values determined in this way. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to a technique for printing an image by forming dots on a print medium.

  2. Description of the Related Art Printing apparatuses that form dots on a printing medium and print images are widely used as output apparatuses for images created by computers and images taken by digital cameras. In such a printing apparatus, since the gradation value of dots that can be formed with respect to the input gradation value is small, gradation expression is performed by halftone processing. As one of the halftone processes, a systematic dither method using a dither matrix is widely used. Since the systematic dither method greatly affects the image quality depending on the contents of the dither matrix, for example, as disclosed in Patent Document 1, analysis such as simulated annealing or genetic algorithm using an evaluation function taking human vision into consideration Dither matrix optimization has been proposed by methods.

JP-A-7-177351 JP-A-7-81190 Japanese Patent Laid-Open No. 10-329381

  However, in the past, dither matrix optimization was performed assuming a certain observation environment and printing resolution assumed in advance, so if the observation environment and printing resolution differ from those assumed, the dither matrix Optimality was significantly reduced.

  The present invention has been made to solve the above-described problems in the prior art, and an object thereof is to provide a dither matrix optimization technique that focuses on robustness.

In order to solve at least a part of the above-described problems, the present invention provides a plurality of methods for determining a dot formation state on each print pixel of a print image to be formed on a print medium according to input image data. A method is provided for generating a dither matrix that stores a threshold value for each element.
The method assumes a difference between at least one of the observation distance and the print resolution based on the dot formation state assumed for each candidate storage element of the target threshold value to be evaluated among the plurality of threshold values. An evaluation value determination step of determining a matrix evaluation value, which is an evaluation value representing a correlation with the target state, for each candidate,
A storage element determination step for determining a storage element for the threshold value of interest from the candidates based on the determined matrix evaluation value;
For at least a part of the plurality of threshold values, repeating the evaluation value determining step and the storage element determining step while changing the target threshold value,
It is characterized by providing.

  In the dither matrix generation method of the present invention, the threshold storage element is determined based on the evaluation value representing the correlation with a plurality of target states assuming at least one difference between the observation distance and the print resolution. It is possible to generate a dither matrix having high robustness with respect to variations in print resolution. Here, “correlation with the target state” means that, for example, in an evaluation function using a granularity index or RMS granularity, the granularity index or RMS granularity is small.

  The dither matrix of the present invention uses intermediate data (number data) for specifying the dot formation state as disclosed in, for example, Japanese Patent Application Laid-Open Nos. 2005-236768 and 2005-269527. Such a technique has a broad concept including a conversion table (or correspondence table) generated using a dither matrix. Such a conversion table is not only generated directly from the dither matrix generated by the generation method of the present invention, but may be adjusted or improved. In such a case, the conversion table is also generated by the generation method of the present invention. Corresponds to the use of a dither matrix.

  Further, it is not always necessary to perform the repetition process for all of the plurality of threshold values, and for example, it may be performed only for a part of the highlight area. This is because the object of the present invention can be achieved by performing at least some of the plurality of threshold values.

  In the dither matrix generation method, the matrix evaluation value is a granularity evaluation value calculated by a calculation process including a Fourier transform process, and includes a visual transfer function determined based on a visual spatial frequency characteristic, and the Fourier You may make it calculate by the convolution integral with the constant calculated beforehand by the conversion process.

In the dither matrix generation method,
Of the plurality of threshold values to be stored in each element of the dither matrix, the focus is determined as the focus threshold value, which is the threshold value for which the element to be stored is undetermined and in which dot formation is most likely to be turned on. A threshold determination step,
The repeating step may include a step of repeating each of the focus threshold value determining step, the evaluation value determining step, and the storage element determining step for at least a part of the plurality of threshold values,
Or
In the dither matrix generation method,
A preparatory step of preparing a dither matrix as an initial state for storing a plurality of threshold values for determining the presence or absence of dot formation for each pixel according to an input gradation value,
A storage element replacement step of replacing a part of a plurality of threshold values stored in the element with a threshold value stored in another element;
With
The evaluation value determination step includes a step of determining a matrix evaluation value for a dot formation state assumed when the replacement of the threshold value is determined.
The repeating step may include a step of repeating each of the storage element replacement step, the evaluation value determination step, and the storage element determination step for at least some of the plurality of threshold values. In addition, in the present embodiment, “for each storage element candidate” and “target threshold value” in the claims are “for each of a plurality of replaced storage element candidates” and “for a plurality of replaced threshold values”. Each corresponds.

In the dither matrix generation method, the evaluation value determination step includes:
Calculating a plurality of RMS granularities by executing a calculation process including a low-pass filter process using a plurality of low-pass filters assuming a difference between at least one of the observation distance and the print resolution;
Determining the matrix evaluation value based on the calculated plurality of RMS granularities;
May be included.

  As described above, optimization considering human visual characteristics can be performed using a low-pass filter without directly using visual spatial frequency characteristics VTF. In addition, since the process using the low-pass filter does not require a conversion process between the frequency domain and the spatial domain, the burden of the calculation process can be reduced.

  In the dither matrix generation method, the plurality of low-pass filters includes a step of performing an inverse Fourier transform on a plurality of characteristics defined in a frequency domain assuming at least one difference between the observation distance and the print resolution. It may be configured.

  In this way, a frequency characteristic closer to the human visual spatial frequency characteristic VTF can be expressed by a low-pass filter.

It is confirmed that the dither matrix generated in this way can achieve the original effects of the present invention by reliably implementing the present invention if, for example, the following objective features that can be observed from the outside are observed. it can. That is, conversely, a dither matrix configured to have the following characteristics by other generation methods can exhibit the effects inherent in the present invention. That is,
A dither matrix that stores, in each element, a plurality of threshold values for determining a dot formation state on each print pixel of a print image to be formed on a print medium in accordance with input image data,
A dither matrix characterized in that a granularity index representing an evaluation value of the granularity of the printed image has a plurality of bottoms with respect to a variation in observation distance between 100 mm and 600 mm;
Or
A dither matrix that stores, in each element, a plurality of threshold values for determining a dot formation state on each print pixel of a print image to be formed on a print medium in accordance with input image data,
A dither matrix characterized in that a granularity index representing an evaluation value of the granularity of the printed image has a flat bottom with respect to a variation in observation distance between 300 mm and 400 mm. .

  The flat bottom means that a single observation distance or print resolution is evaluated in the above-mentioned predetermined range in the optimization for the observation distance or print resolution as seen in the graininess index curve M01 (FIG. 6A). This means a bottom that is so flat that it cannot be constructed. On the other hand, a plurality of bottoms as seen in the graininess index curve M11 (FIG. 6B) appear when a single observation distance or print resolution is evaluated in the optimization for the observation distance or print resolution. It is impossible. The “granularity index” in the claims means a value calculated by the calculation formula shown in FIG.

  The present invention is directed to causing a computer to implement various forms such as a dither matrix, a dither matrix generation apparatus, a printing apparatus and a printing method using the dither matrix, and a printed material generation method, or the functions of these methods or apparatuses. The present invention can be realized in various forms such as a computer program, a recording medium that records the computer program, and a data signal that includes the computer program and is embodied in a carrier wave.

  In addition, the use of a dither matrix in the printing device, printing method, and printed material generation method is based on whether or not dots are formed for each pixel by comparing the threshold value set in the dither matrix and the gradation value of the image data for each pixel. However, for example, the presence or absence of dot formation may be determined by comparing the sum of the threshold value and the gradation value with a fixed value. Furthermore, the presence / absence of dot formation may be determined according to the data generated in advance based on the threshold value and the gradation value without directly using the threshold value. In general, the dither method of the present invention directly or indirectly determines the presence / absence of dot formation according to the gradation value of each pixel and the threshold value set at the corresponding pixel position of the dither matrix (for example, as described above). (Japanese Patent Laid-Open No. 2005-236768).

Below, in order to demonstrate the effect | action and effect of this invention more clearly, embodiment of this invention is described in the following orders.
A. Dither matrix optimization in embodiments of the present invention:
B. A method of generating a dither matrix in each embodiment of the present invention:
B-1. Optimization (granularity index) in the first embodiment of the present invention:
B-2. Optimization (RMS granularity) in the second embodiment of the present invention:
C. Variation:

A. Dither matrix optimization in embodiments of the present invention:
FIG. 1 is an explanatory diagram conceptually illustrating a part of the dither matrix. In the illustrated matrix, 128 elements in the horizontal direction (main scanning direction), 64 elements in the vertical direction (sub-scanning direction), a total of 8192 elements, were selected uniformly from the range of gradation values 1 to 255. A threshold value is stored. Note that the size of the dither matrix is not limited to the size illustrated in FIG. 1 and can be various sizes including a matrix having the same number of vertical and horizontal elements.

  FIG. 2 is an explanatory diagram illustrating the concept of dot formation using a dither matrix. For the sake of illustration, only some elements are shown. In determining the presence or absence of dot formation, as shown in FIG. 2, the gradation value of the image data is compared with the threshold value stored at the corresponding position in the dither matrix. If the gradation value of the image data is larger than the threshold value stored in the dither table, a dot is formed, and if the gradation value of the image data is smaller, no dot is formed. The hatched pixels in FIG. 2 mean pixels on which dots are formed. In this way, if the dither matrix is used, it is possible to determine the presence or absence of dot formation for each pixel by a simple process of comparing the gradation value of the image data and the threshold value set in the dither matrix. The gradation number conversion process can be performed quickly. Furthermore, when the gradation value of the image data is determined, whether or not dots are formed in each pixel is determined solely by the threshold value set in the dither matrix. It is possible to positively control the dot generation state by the threshold storage position set in the matrix.

  As described above, since the systematic dither method can positively control the occurrence of dots according to the threshold storage position set in the dither matrix, the dot dispersion can be achieved by adjusting the threshold storage position setting. And other image quality can be controlled. This means that the halftone process can be optimized for various target states by the dither matrix optimization process.

  FIG. 3 is an explanatory diagram conceptually illustrating the spatial frequency characteristics of the threshold values set for each pixel of the blue noise dither matrix having blue noise characteristics as a simple example of adjustment of the dither matrix. The spatial frequency characteristic of the blue noise matrix is a characteristic having the largest frequency component in a high frequency region in which the length of one cycle is 2 pixels or less. Such spatial frequency characteristics are set in consideration of human visual characteristics. That is, the blue noise dither matrix is a dither matrix in which the threshold storage position is adjusted so that the largest frequency component is generated in the high frequency region in consideration of the human visual characteristic that the sensitivity is low in the high frequency region.

  FIG. 4A conceptually shows a visual spatial frequency characteristic VTF (Visual Transfer Function) which is a sensitivity characteristic with respect to a visual spatial frequency of a human when an observation state is assumed with an observation distance of 300 mm. FIG. By using the visual spatial frequency characteristic VTF, the human visual sensitivity is modeled as a transfer function called the visual spatial frequency characteristic VTF, thereby quantifying the graininess of the dots after the halftone process appealing to the human visual sense. It becomes possible. The value quantified in this way is called the graininess index. The visual spatial frequency characteristic VTF is also referred to as a VTF function in this specification.

  FIG. 4B shows a typical empirical formula representing the visual spatial frequency characteristic VTF. The visual spatial frequency characteristic VTF is defined as a function of the angular spatial frequency f. On the other hand, the spatial frequency f of the angle can be expressed as a function of the observation distance L and the spatial frequency u on the print image plane.

  Such quantification of the granularity that appeals to human vision enables fine optimization of the dither matrix for the human visual system. Specifically, a Fourier transform is performed on a dot pattern assumed when each input gradation value is input to the dither matrix to obtain a power spectrum FS, and a filter process for multiplying the visual spatial frequency characteristic VTF is performed. After that, the graininess index that can be obtained by integration with all input tone values (FIG. 4C) can be used as the evaluation value of the dither matrix. The coefficient K in FIG. 4C is a coefficient for matching the obtained value with human senses. In this example, the optimization can be achieved by adjusting the threshold storage position so that the evaluation value of the dither matrix becomes small.

  Thus, conventionally, with respect to the image evaluation method, the dither matrix optimization problem and other halftone processing optimization problems have been evaluated assuming a specific observation state. Variations in were not considered. On the other hand, the observation state usually varies depending on the user who is the observation subject. For this reason, in an environment different from the observation distance and the printing resolution assumed in advance, there has been a problem that the recognized image quality is excessively deteriorated.

  In an embodiment of the present invention, a method for generating an optimal dither matrix in consideration of robustness against fluctuations in observation distance and print resolution is disclosed. Note that the change in observation distance and the change in print resolution are physically equivalent as will be described later.

B. Method for generating optimal dither matrix in each embodiment of the present invention:
In the embodiment of the present invention, an optimal dither matrix generation method having high robustness against fluctuations in observation distance is realized. However, the optimization of the dither matrix can be performed not only by generating the dither matrix but also by adjusting the dither matrix by exchanging the storage position of the threshold value of the dither matrix as shown in a modified example described later. Dither matrix optimization is applied to some parts such as optimization for some input tone values (for example, only areas with low dot density) and some element areas (for example, only the central part or the peripheral part of the dither matrix). Can also be done.

B-1. Optimization (granularity index) in the first embodiment of the present invention:
FIG. 5 is a flowchart showing the processing routine of the dither matrix generation method in the first embodiment of the present invention. In the first embodiment of the present invention, the dither matrix is optimized based on the above-described graininess index.

  In step S100, two evaluation functions are determined. In this embodiment, the two evaluation functions are composed of an evaluation function with an observation distance L of 300 mm and an evaluation function with an observation distance L of 450 mm in the granularity index (FIG. 4C). .

  FIG. 6 is an explanatory diagram showing how the dither matrix is optimized in the first embodiment of the present invention. FIG. 6A shows the state of dither matrix optimization that is highly robust against changes in observation distance. FIG. 6A shows three granularity index curves MB01, MB02, and M01 representing the variation of the granularity index with respect to the variation of the observation distance. The graininess index curve MB01 represents the graininess index of the dither matrix optimized for an observation distance of 300 mm. The graininess index curve MB02 represents the graininess index of the dither matrix optimized for an observation distance of 450 mm. The graininess index curve M01 represents the graininess index of the dither matrix optimized for both 300 mm and 450 mm observation distances. However, the print resolution is assumed to be fixed at 720 dpi.

  As can be seen from the graininess index curve MB01, the dither matrix optimized for an observation distance of 300 mm has a low graininess index when the observation distance is 300 mm. It can be seen that the graininess index increases. As can be seen from the graininess index curve MB02, the same applies to the dither matrix optimized for an observation distance of 450 mm. On the other hand, the dither matrix optimized for the observation distances of 300 mm and 450 mm has a suppressed granularity index in a wide range centered between 300 mm and 450 mm, as can be seen from the granularity index curve M01. I understand. In this embodiment, the generation of the dither matrix having high robustness against the variation in the observation distance is realized by using the above-described two evaluation functions.

  On the other hand, the present embodiment can also realize high robustness against fluctuations in printing resolution. FIG. 6B shows how the dither matrix is optimized with high robustness against variations in print resolution. The graininess index curve MB11 represents the graininess index of the dither matrix optimized for a printing resolution of 720 dpi. The graininess index curve MB12 represents the graininess index of the dither matrix optimized for a printing resolution of 1440 dpi. The graininess index curve M01 represents the graininess index of the dither matrix optimized for both 720 dpi and 1440 dpi printing resolution. However, the observation distance is assumed to be fixed at 300 mm. A dither matrix having high robustness against fluctuations in print resolution can be used as a dither matrix that realizes high image quality at a plurality of print resolutions, for example.

  Such optimization includes an evaluation function that sets the spatial frequency u to a spatial frequency corresponding to 720 dpi, and an evaluation function that sets the spatial frequency u to a spatial frequency corresponding to 1440 dpi in the granularity index (FIG. 4C). This can be realized by determining the plurality of evaluation functions described above. As can be seen from the equation in FIG. 4B, the variation in observation distance and the variation in print resolution are physically equivalent.

  In this way, when the optimization target state (high robustness to fluctuations in observation distance and print resolution) and a plurality of evaluation functions for achieving this target state are set, the process proceeds to step S200 (FIG. 5). ).

  In step S200, a target threshold value determination process is performed. The target threshold value determination process is a process for determining a threshold value to be a storage element determination target. In this embodiment, the threshold value is determined by selecting in order from a threshold value having a relatively small value, that is, a threshold value having a value at which dots are easily formed. Thus, if the dots are selected in order from the threshold at which dots are likely to be formed, the elements stored in order from the threshold for controlling the dot arrangement in the highlight area where the graininess of the dots is conspicuous are fixed. This is because a large degree of design freedom can be given to a highlight region where graininess is conspicuous.

  In step S300, a dither matrix evaluation process is performed. The dither matrix evaluation process is a process for quantifying the optimality of the dither matrix based on the plurality of evaluation functions set as described above.

  FIG. 7 is a flowchart showing the processing routine of the dither matrix evaluation process in the first embodiment of the present invention. In the dither matrix generation method according to the present embodiment, first, it is assumed that a dot is formed in a pixel corresponding to a determined element whose threshold value to be stored is an already determined element, and the threshold value to be stored is an undecided element A granularity index is calculated as an evaluation value for each blank element on the assumption that dots are formed in any one blank element. The calculation of the graininess index is performed for every two evaluation functions. Next, the storage element is determined using the two calculated evaluation functions. Specifically, the following processing is performed.

  In step S310, the parameters of the visual spatial frequency characteristic VTF (FIG. 4B) are adjusted. In this embodiment, parameter adjustment for setting the observation distance L to 300 mm in the equation of FIG. 4B and parameter adjustment for setting the observation distance L to 450 mm in the equation of FIG. 4B are performed. In this embodiment, two observation distances L are assumed, but three or more observation distances L may be assumed.

  In step S320, the corresponding threshold value corresponding dot is turned on. The determined threshold means a threshold at which the storage element is determined. In this embodiment, since the threshold value is selected in order from the value at which dots are likely to be formed as described above, when a dot is formed as the threshold value of interest, the pixel corresponding to the element storing the determined threshold value is not used. Dots are always formed. Conversely, at the smallest input tone value at which dots are formed at the threshold value of interest, no dots are formed at pixels corresponding to elements other than the element storing the determined threshold value.

  FIG. 8 is an explanatory diagram showing a state in which dots are formed in each of the eight pixels corresponding to the elements storing the thresholds at which dots are likely to be formed first to eighth in the dither matrix M. This dot pattern is used to determine in which pixel the ninth dot is to be formed. That is, it is used to determine the storage element of the target threshold value at which the ninth dot is most likely to be formed.

  FIG. 9 is an explanatory diagram showing a matrix obtained by quantifying the state in which dots are formed in each of the eight pixels in FIG. 8, that is, a dot density matrix that quantitatively represents the dot density. The number 0 means that no dot is formed, and the number 1 means that a dot is formed. The graininess index is calculated based on this matrix.

  In step S330, the corresponding dot of the element of interest is turned on. In step S340, the graininess index is calculated from one of the two evaluation functions for which the parameters have been adjusted. Such processing is executed for all elements of interest (step S350). Further, similar processing is performed on the other of the two evaluation functions (step S360).

  In step S370, comprehensive evaluation values are determined for all elements of interest. In this embodiment, the comprehensive evaluation value is calculated as the sum of two graininess indexes calculated by each of the two evaluation functions. The comprehensive evaluation value is not limited to the above method, and may be calculated by, for example, obtaining a sum after performing predetermined weighting on each of the two granularity indexes as necessary. Thus, when the comprehensive evaluation value is determined for all the elements of interest, the process proceeds to step S400 (FIG. 5).

  In step S400, a storage element determination process is performed. The storage element determination process is a process for determining a storage element of the target threshold value (threshold in which 9th dot is most likely to be formed in this example). In the present embodiment, the storage element is determined from elements having the smallest overall evaluation value.

  When such processing is performed for all threshold values from the threshold at which dots are most easily formed to the threshold at which dots are hardly formed, the dither matrix generation processing is completed (step S500).

  Note that such processing is not necessarily performed for all of the plurality of threshold values, and can be performed only for a part of the highlight area, for example. Specifically, for example, a highlight region where the number of dots is from zero to a predetermined number is determined by an experienced engineer based on experience and the granularity is particularly problematic from the threshold value at which the number of dots becomes a predetermined number The threshold may be determined by the above-described method.

  In step S600, the optimality is confirmed. The confirmation of the optimality is performed by performing halftone processing using the dither matrix generated in this way and analyzing the printed image subjected to the halftone processing. The analysis of the printed image is performed by confirming that the graininess index is suppressed in a wide range by changing the observation distance between 300 mm and 450 mm. Thereby, in the present embodiment, it can be confirmed that the present invention is applied and the effects inherent in the invention are exerted.

Specifically, for example, it can be confirmed that the present invention is implemented according to the following criteria.
(1) As shown in the graininess index curve M01 (FIG. 6A), the graininess index of the printed image has a flat bottom with respect to fluctuations in observation distance and print resolution. The flat bottom means a bottom that is so flat that it cannot be configured by using a single observation distance or print resolution as an evaluation in optimization for the observation distance or print resolution.
(2) As shown in the graininess index curve M11 (FIG. 6B), the graininess index of the printed image has a plurality of bottoms with respect to fluctuations in observation distance and printing resolution. A plurality of bottoms cannot appear when a single observation distance or print resolution is evaluated in the optimization for the observation distance or print resolution.

  As described above, the first embodiment of the present invention can generate a dither matrix having high robustness against fluctuations in observation distance and printing resolution, and can implement the present invention and confirm the effect thereof. Can do.

B-2. Optimization (RMS granularity) in the second embodiment of the present invention:
FIG. 10 is a flowchart showing the processing routine of the dither matrix generation method in the second embodiment of the present invention. In the second embodiment of the present invention, the dither matrix is optimized based on a specific RMS granularity newly found by the present inventors. Such optimization is realized by changing the dither matrix evaluation process in step S300 to the dither matrix evaluation process in step S300a.

  FIG. 11 is a flowchart showing the processing routine of the dither matrix evaluation process in the second embodiment of the present invention. This evaluation process is realized by changing the three steps S310, S340, and S360 to steps S310a, S340a, and S360a, respectively.

  In step S310a, a low-pass filter selection process is performed. The low-pass filter selection process has a role corresponding to the parameter adjustment in step S310. In other words, this embodiment is configured to be selected from two low-pass filters corresponding to an evaluation function with an observation distance L of 300 mm and a low-pass filter corresponding to an evaluation function with an observation distance L of 450 mm. ing. The meaning of the correspondence relationship will be described later.

  12 and 13 are explanatory diagrams showing two low-pass filters F300 and F450 to be selected in this embodiment. These low-pass filters F300 and F450 are obtained by simply replacing optical low-pass filter processing realized by passing an aperture having a constant area with digital processing. Such optical low-pass filter processing has been performed in the field of photographic film where RMS granularity has been used as a general evaluation measure.

  14 and 15 are explanatory diagrams showing the characteristics of the two low-pass filters F300 and F450 to be selected in this embodiment. As can be seen from FIG. 14, the low-pass filter F300 has a matrix size configured such that the VTF function with the observation distance L of 300 mm matches the cutoff frequency. On the other hand, as can be seen from FIG. 15, the low-pass filter F450 has a matrix size configured such that the cutoff frequency coincides with the VTF function with an observation distance L of 450 mm.

  In step S340a, RMS granularity calculation processing is performed. The RMS granularity calculation process is a process of calculating a standard deviation after low-pass filtering the dot density matrix (FIG. 9). The standard deviation can be calculated using a calculation formula (FIG. 16). Such processing is performed for all the target pixels as in the first embodiment (step S350). Further, similar processing is performed for both of the two low-pass filters F300 and F450 as in the first embodiment (step S360a).

  As described above, the present invention can also be realized by using the RMS granularity as an evaluation function. Further, even when RMS granularity is used as an evaluation function, optimization considering human visual characteristics can be realized by setting a low-pass filter in the same manner as visual spatial frequency characteristics VTF. In addition, since the evaluation process using the low-pass filter does not require a conversion process between the frequency domain and the spatial domain, the burden of the calculation process can be reduced.

C. Variation:
As mentioned above, although several embodiment of this invention was described, this invention is not limited to such embodiment at all, and implementation in various aspects is possible within the range which does not deviate from the summary. It is. For example, the present invention can optimize halftone processing for the following modifications.

C-1. In the second embodiment described above, the optical low-pass filter processing is replaced with digital processing, and the low-pass filters F300 and F450 configured to adjust the matrix size so that the cutoff frequency approaches the VTF function are used. However, for example, a low-pass filter may be configured based on the VTF function.

  FIG. 17 is an explanatory diagram illustrating a processing routine of low-pass filter generation processing according to a modification. In step S710, an image is prepared in which dots are turned on for only one pixel at the center of the image. In step S720, this image is subjected to two-dimensional Fourier transform. In step S730, the two-dimensional Fourier transformed image is multiplied by a plurality of VTF functions for which parameter adjustment has been performed. In the plurality of VTF functions, for example, the printing resolution is fixed to 720 dpi, and the observation distance L is set to 300 mm or 450 mm. In step S740, the frequency domain is transformed to the spatial domain by inverse Fourier transform. In step S750, the low-pass filter is cut out from the matrix data converted into the spatial domain and shaped. More specifically, elements smaller than a certain element value are rounded down to reduce the filter size, and the elements are converted to integers in order to reduce the processing load in the optimization process. Note that normalization is not performed. This is because it is unnecessary for the optimization process.

C-2. In the above-described embodiment, it is assumed that one threshold value storage element fluctuates. However, for example, the present invention can be applied to a case where a plurality of threshold value storage elements are simultaneously determined or changed. Can do. Specifically, for example, in the above-described embodiment, when the storage elements for the sixth threshold are determined and the storage elements for the seventh and eighth thresholds are determined, the seventh threshold storage element is also determined. The storage element may be determined based on the evaluation value when the dot is added to the storage element and the evaluation value when the dot is added to each of the storage elements of the seventh and eighth threshold values, or Only the storage element of the seventh threshold value may be determined. When each storage element of a plurality of thresholds is determined at a time, “for each candidate storage element of threshold value of interest” in the claims is “a plurality of storages storing each of a plurality of threshold values”. Corresponds to each element set.

C-3. In the above-described embodiment, the threshold storage elements are determined in order. However, for example, the dither matrix may be generated by adjusting the dither matrix as an initial state prepared in advance. . For example, a dither matrix is prepared as an initial state for storing in each element a plurality of threshold values for determining the presence or absence of dot formation for each pixel according to the input gradation value, and a plurality of threshold values stored in each element A part of this is replaced with a threshold value stored in another element in a randomly or systematically determined manner, and the dither matrix is adjusted by determining whether or not to replace based on the evaluation values before and after the replacement. May be generated. It should be noted that “for each storage element candidate” in the claims corresponds to “for each set of candidates for a plurality of replaced storage elements” in the present modification.

C-4. In the above-described embodiment, the optimality of the dither matrix is evaluated based on the granularity index and the RMS granularity. For example, Fourier transform is performed on the dot pattern, and the optimality of the dither matrix is determined using the VTF function. You may comprise so that it may evaluate. Specifically, the evaluation scale (Grainess scale: GS value) used by Dooley et al. Of Xerox may be applied to the dot pattern, and the optimality of the dither matrix may be evaluated based on the GS value. Here, the GS value is obtained by performing a predetermined process including a two-dimensional Fourier transform on the dot pattern to digitize the dot pattern, and performing integration after performing a filter process that multiplies the visual spatial frequency characteristic VTF. It is a graininess evaluation value that can be

C-5. The present invention can be applied regardless of the optimization method because the amount of evaluation calculation in the optimization process can be reduced. For example, it can be widely applied to optimization methods such as simulated annealing and genetic algorithms.

C-6. The dither matrix of the present invention uses intermediate data (number data) for specifying the dot formation state disclosed in, for example, Japanese Patent Application Laid-Open No. 2005-236768 and Japanese Patent Application Laid-Open No. 2005-269527. Applicable to technology. The “dither matrix” in the claims has a broad concept including a conversion table (or correspondence table) generated using the dither matrix. Such a conversion table is not only generated directly from the dither matrix generated by the generation method of the present invention, but may be adjusted or improved. In such a case, the conversion table is also generated by the generation method of the present invention. Corresponds to the use of a dither matrix.

Explanatory drawing which illustrated a part of dither matrix conceptually. Explanatory drawing which shows the idea of the presence or absence of the dot formation using a dither matrix. Explanatory drawing which illustrated notionally the spatial frequency characteristic of the threshold value set to each pixel of the blue noise dither matrix which has a blue noise characteristic. Explanatory drawing which showed notionally the visual spatial frequency characteristic VTF (Visual Transfer Function) which is a sensitivity characteristic with respect to the visual spatial frequency which a human has. The flowchart which shows the processing routine of the production | generation method of the dither matrix in 1st Example of this invention. Explanatory drawing which shows the mode of the dither matrix optimization in 1st Example of this invention. The flowchart which shows the process routine of the dither matrix evaluation process in 1st Example of this invention. Explanatory drawing which shows a mode that the dot was formed in each of the 8 pixels corresponding to the element in which the threshold in which the 1st-8th dot is easy to be formed was stored in the dither matrix M. Explanatory drawing which shows the dot density matrix in the state in which the dot was formed in each of eight pixels. The flowchart which shows the processing routine of the production | generation method of the dither matrix in 2nd Example of this invention. The flowchart which shows the process routine of the dither matrix evaluation process in 2nd Example of this invention. Explanatory drawing showing the formula which defines the RMS granularity used in 2nd Example of this invention. Explanatory drawing which shows two low-pass filters F300 and F450 used as selection object in 2nd Example of this invention. Explanatory drawing which shows the characteristic of the low-pass filter F300 used as selection object in 2nd Example of this invention. Explanatory drawing which shows the characteristic of the two low-pass filters F450 used as selection object in 2nd Example of this invention. Explanatory drawing which shows the calculation formula used by the RMS granularity calculation process in 2nd Example of this invention. Explanatory drawing which shows the process routine of the low-pass filter production | generation process in a 1st modification.

Explanation of symbols

F300 ... Low-pass filter F450 ... Low-pass filter

Claims (13)

A method for generating a dither matrix that stores, in each element, a plurality of threshold values for determining a dot formation state on each print pixel of a print image to be formed on a print medium in accordance with input image data There,
Based on the dot formation state assumed for each storage element candidate of the target threshold value to be evaluated among the plurality of threshold values, a plurality of target states that assume at least one difference between the observation distance and the print resolution; An evaluation value determining step for determining a matrix evaluation value, which is an evaluation value representing the correlation, for each candidate;
A storage element determination step for determining a storage element for the threshold value of interest from the candidates based on the determined matrix evaluation value;
For at least a part of the plurality of threshold values, repeating the evaluation value determining step and the storage element determining step while changing the target threshold value,
A dither matrix generation method comprising: The dither matrix generation method according to claim 1,
The matrix evaluation value is a granularity evaluation value calculated by a calculation process including a Fourier transform process, and is a VTF function determined based on visual spatial frequency characteristics and a constant calculated in advance by the Fourier transform process. Dither matrix generation method calculated by convolution integration with. The dither matrix generation method according to claim 1, further comprising:
Of the plurality of threshold values to be stored in each element of the dither matrix, the focus is determined as the focus threshold value, which is the threshold value for which the element to be stored is undetermined and in which dot formation is most likely to be turned on. A threshold determination step,
The dither matrix generation method includes the step of repeating the steps of the focus threshold value determination step, the evaluation value determination step, and the storage element determination step for at least a part of the plurality of threshold values. The dither matrix generation method according to claim 1, further comprising:
A preparatory step of preparing a dither matrix as an initial state for storing a plurality of threshold values for determining the presence or absence of dot formation for each pixel according to an input gradation value,
A storage element replacement step of replacing a part of a plurality of threshold values stored in the element with a threshold value stored in another element;
With
The evaluation value determining step includes a step of determining the matrix evaluation value for a dot formation state assumed when the replacement of the threshold value is determined.
The dither matrix generation method includes a step of repeating the storage element replacement step, the evaluation value determination step, and the storage element determination step for at least a part of the plurality of threshold values. A dither matrix generation method according to any one of claims 1, 3, and 4,
The evaluation value determining step includes
Calculating a plurality of RMS granularities by executing a calculation process including a low-pass filter process using a plurality of low-pass filters assuming a difference between at least one of the observation distance and the print resolution;
Determining the matrix evaluation value based on the calculated plurality of RMS granularities;
A dither matrix generation method including: A dither matrix generation method according to claim 5, comprising:
The plurality of low-pass filters are configured by a method including a step of performing an inverse Fourier transform on a plurality of characteristics defined in a frequency domain, assuming a difference between at least one of the observation distance and the print resolution. Generation method. A dither matrix that stores, in each element, a plurality of threshold values for determining a dot formation state on each print pixel of a print image to be formed on a print medium in accordance with input image data,
The dither matrix is configured such that a granularity index representing an evaluation value of the granularity of the printed image has a plurality of bottoms with respect to a variation in observation distance between 100 mm and 600 mm. , Dither matrix. A dither matrix that stores, in each element, a plurality of threshold values for determining a dot formation state on each print pixel of a print image to be formed on a print medium in accordance with input image data,
The dither matrix is configured such that a granularity index representing an evaluation value of the granularity of the printed image has a flat bottom with respect to a variation in observation distance between 300 mm and 400 mm. , Dither matrix. A printing device for printing on a print medium,
Dot data generation that determines the dot formation state for each print pixel of the print image to be formed on the print medium according to the input image data and generates dot data representing the determined dot formation state And
According to the dot data, a print image generation unit that generates a print image by forming dots in the print pixels;
With
The dot data generation unit uses any one of the dither matrix generated by the method according to any one of claims 1 to 6 and the dither matrix according to claim 7 or 8. A printing apparatus configured to determine a dot formation state on each of the printing pixels. A printing method for printing on a print medium,
Dot data generation that determines the dot formation state for each print pixel of the print image to be formed on the print medium according to the input image data and generates dot data representing the determined dot formation state Process,
In accordance with the dot data, a print image generation step for generating a print image by forming dots in the respective print pixels;
With
The dot data generation step uses any one of the dither matrix generated by the method according to any one of claims 1 to 6 and the dither matrix according to claim 7 or 8. A printing method comprising a step of determining a dot formation state on each of the printing pixels. A method for generating a printed material for forming a print image on a print medium,
Dot data generation that determines the dot formation state for each print pixel of the print image to be formed on the print medium according to the input image data and generates dot data representing the determined dot formation state Process,
According to the dot data, a printed matter generating step for generating a printed matter by forming dots at the respective printing pixels;
With
The dot data generation step uses any one of the dither matrix generated by the method according to any one of claims 1 to 6 and the dither matrix according to claim 7 or 8. A method for generating printed matter, comprising a step of determining a dot formation state on each of the printing pixels. An apparatus for generating a dither matrix that stores, in each element, a plurality of threshold values for determining a dot formation state on each print pixel of a print image to be formed on a print medium in accordance with input image data There,
Based on the dot formation state assumed for each storage element candidate of the target threshold value to be evaluated among the plurality of threshold values, a plurality of target states that assume at least one difference between the observation distance and the print resolution; An evaluation value determination unit that determines a matrix evaluation value that is an evaluation value that represents the correlation of each candidate,
Based on the determined matrix evaluation value, a storage element determination unit that determines a storage element of the threshold value of interest from the candidates;
A dither matrix generating device comprising: A computer program for generating a dither matrix that stores, in each element, a plurality of threshold values for determining a dot formation state on each print pixel of a print image to be formed on a print medium in accordance with input image data Because
Based on the dot formation state assumed for each storage element candidate of the target threshold value to be evaluated among the plurality of threshold values, a plurality of target states that assume at least one difference between the observation distance and the print resolution; An evaluation value determination function for determining a matrix evaluation value, which is an evaluation value representing the correlation, for each candidate;
Based on the determined matrix evaluation value, a storage element determination function for determining a storage element of the target threshold value from the candidates;
For at least some of the plurality of thresholds, a repetition function that repeats each of the evaluation value determination process and the storage element determination process while changing the target threshold value;
A computer program comprising a program for causing the computer to realize the above.

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