How to perform a color space conversion

Abstract

To provide a color space conversion method which performs exhaustive control of conversion by high throughput of color conversion and in each color space while using a normal multi-dimension table.SOLUTION: A method is for executing in a computer-assisted manner, color data conversion of a project from a color space of a supply source to a color space of a supply destination by using a conversion table based on a conversion rule. The method includes the following steps of: determining combinations of all colors with respect to n colors in the color space of the supply source where the color component is not zero; generating a sub space conversion table every combination of the colors and storing the sub space conversion table; generating all true subsets including an empty set, generating them as an individual redundant sub space conversion table, and storing the individual redundant sub space conversion table in each sub space conversion table; and allocating a corresponding sub space table to each input having color components of n colors on the basis of the color component which is not zero by using the stored sub space conversion table.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a method for performing the conversion of project color data from a source color space to a destination color space using a conversion table based on conversion rules. [Background technology]

[0002] In the printing industry, color conversion is sometimes necessary to create a dataset of color print products to be printed.

[0003] The starting point is a digital layout. A digital layout can include, for example, color images captured by photographs or scans, illustrations, or documents. Such layouts are templates that are reproduced exactly as they are in the form of a printed product. Such layouts are designed or developed in any format and, in terms of color, represent what is desired according to the intended purpose. Therefore, each layout object has a clearly identifiable color appearance. As is well known, in the case of printed products, for example, by simply printing screened inks on each other, each color makes a certain contribution through its effect, and the final result is created by the interaction of different color layers, thus creating a color appearance by mixing only a few colors.

[0004] The color appearance of each layout object is defined by color values ​​(image pixels, outline colors, or fill colors) that represent the data source. In the case of image pixels, there are typically millions of pixels, each with its own color value. These source color values ​​always refer to the supplier's color space, which has a specific number of colors. This means that each object in the layout is assigned to a color space typically associated with the device, which can be a specific RGB color space such as sRGB or AdobeRGB, a CMYK color space, black only (grayscale), or other print color spaces. The object's color values ​​are quantified as RGB values, CMYK or grayscale values ​​(0% to 100% color), or other color values, where the total number of device colors in the supplier's color space is denoted by n.

[0005] Color spaces are typically represented by ICC color profiles (ISO 15076-1:2010) and by layouts in PDF and PDF / X files (ISO 15930 series) that contain or reference these ICC color profiles.

[0006] Layouts are reproduced for vastly different reasons and purposes. A wide variety of printing processes and presses can be used for reproduction. This has the potential to apply a specific number of colors to the carrier material in a specific way; that is, the colors used by the devices in the printing system. These colors define or form the basis of the target color space and therefore include all possible combinations of colors used by the devices in the printing system. They can also be the device colors of a monitor. These are referred to as the m device colors of the target color space. Often, conversion to device-independent values ​​such as Lab or spectral colors is also necessary when verifying post-print measurement results or providing a device-independent database for display on any device. This is why the term "m values ​​of the target color space" is commonly used.

[0007] Standardized color spaces are typically used as the source color space during layout design, but printing is performed using specific output systems with their own unique color behavior. Therefore, for each halftone dot in the layout, a predetermined combination of n device colors from the source color space needs to be converted to a combination of m values ​​from the destination color space required for further processing. The goal is to produce an output that is as close as possible to the original, i.e., the digital layout, and ideally, to reproduce the same appearance to the human eye.

[0008] A halftone point, or pixel, is any point on a layout that results from the specified rasterization of a layout object. This relates, for example, to the so-called image resolution for creating print forms. If a grid with i rows and j columns is placed on the layout, the resolution can be expressed as i × j pixels. Individual pixels can be identified from one another by their color structure.

[0009] In particular, color conversion is performed when converting layout data into printable data with the desired print color set. This results in, for example, uniform and authentic CMYK data for offset printing. Color conversion is also performed to bind and simulate the color appearance of this print data before printing. The color appearance is usually represented either in a device-independent manner in the CIELAB color space (abbreviated as Lab) or using spectral reflectance coefficients. Print data with an assigned color space is converted into device-independent color data. These are displayed on a calibrated screen or a special proofing printing system (a so-called "proof," usually an inkjet system). In connection with this, there is the task of adapting print data to other printing processes while preserving the impression of the original colors as much as possible; that is, the task of generating new print data for other inks from existing print data through conversion.

[0010] Generally, for typical printing processes with four colors or less, these conversion processes are largely established and standardized by the corresponding data systems.

[0011] However, in packaging printing, for example, four or more printing colors are generally used. Traditionally, brand colors are added as spot colors, and images are constructed with product-specific colors (for example, a light gray printing color is added for dairy products, and various shades of brown are added for chocolate products). In addition, white printing ink is often added to transparent film packaging. Each ink used occupies a printing unit of the printing press and requires its own printing form in ink transfer. Colors are applied sequentially, and in principle, all colors can be combined with each other (overprintable). The wholeness in separate printing forms leads to the process of creating print data, or consequently, the term "separation."

[0012] Machines with 7 to 10 ink units are not uncommon in flexographic, offset lithography, and gravure printing. Designers of branded products can choose printing inks from thousands of spot colors, including over 2,000 hues in the PANTONE (trademarked) system. These inks are manufactured and supplied by ink manufacturers. In so-called digital printing, inkjet and toner-based printing presses are used, often containing 6 to 8 ink units, but operating with fixed ink sets or changing them is too technically complex because inkjet inks and color toners require highly specific, machine-dependent processing characteristics. Typical color sets include CMYK, complemented by orange or red, green, blue or purple, and white.

[0013] Currently, while digital printing processes are slower than traditional printing processes, they significantly reduce setup effort because they eliminate the need to create print forms or change colors. This allows for faster, more economical printing and enables personalized printing. Therefore, even if there is a demand for rapid printing of conventionally produced packages or for personalization as needed (execution 1), the color appearance must be as identical as possible to previously printed products manufactured with individual spot colors. This is to allow different batches of products to be displayed on shelves. For this purpose, print data usable in traditional printing processes is converted from its source color space to the destination color space representing the digital printing process. In the case of extremely modified or personalized printing, different source data needs to be converted for each copy, which becomes a bottleneck.

[0014] Therefore, the color conversion described at the beginning converts from the source color space Q (e.g., having device colors) to the destination color space Z (e.g., having m device colors or three CIELAB values ​​L, a, b). This is done by applying a conversion rule TRV. Such rules refer to calculation formulas, conversion models, or conversion tables already created based on TRV. High throughput is important because it needs to be applied frequently per pixel (millions of pixels per second). To achieve this, interpolation is performed using predefined tables such as ICC industry standards. The table is constructed assuming n combinations of color values. Each of the n input colors can take values ​​between 0% and 100% ink coverage. Not all combinations can be listed on the table, but each input color is sampled at a specified resolution. An n-dimensional grid of squares containing all combinations of sampled levels is obtained. Between them, n-dimensional interpolation is applied. The accuracy depends on this sampling. A typical sample is n=3 (RGB / Lab), which yields 33 levels (33 3(approximately 36,000 table entries), and for n=4 (CMYK), there are 17 grayscale levels (6.25% increments, 17 4 (Approximately 84,000 table entries). The number of gradations represents the base in the exponent, and the number of inks n is the exponent. The number of gradations is the base of the power, and the number of inks n is the exponent. The generation of conversion tables is a method familiar to those skilled in the art. They are based, for example, on spectroscopic measurements of printed inks, calculations for estimation and / or interpolation, etc.

[0015] The size of the color table increases exponentially with the number of input colors n. Due to limited memory space, it becomes necessary to coarsely sample for practical reasons. For a typical n=7, only 6 or 7 levels are used. One example is the widely used open-source color management system LittleCMS, which uses 7 levels (16.67% increments). 7 This amounts to approximately 820,000 table entries. Therefore, the table structure has the problem that the larger the number of inks, the larger the table becomes, and the fewer gradients can be stored. Users expect the same level of precision they are used to with CMYK to be achieved with CMYK and additional colors. Therefore, 7 levels is quite coarse.

[0016] A known solution approach is disclosed in Patent Document 1. According to this, an assignment table with four or more input color components is divided into several assignment tables with a maximum of four input color components. This method aims to solve the problem of assignment tables being too large. In the prior art, even with 7-color printing, typically only four or fewer colors are printed overlapping at a single point on the printed sheet. Accordingly, a concrete proposal was made to solve the above problem by essentially reducing it to a 4-component table. For this reason, the reduction to a 4-component table is also being promoted. To make it more reliable, additional processes such as gray component replacement (GCR) and color component replacement (CCR) are applied when creating the separation table. Similar prior art can be found in Non-Patent Document 1 and Patent Document 2.

[0017] The known solution approach uses a model or a combination of a model and a table. A model is typically a mathematically based transformation rule. In this way, the Lab color values ​​for overprints can be estimated from individual print colors. This is done, for example, when displaying layouts or PDF files on a screen, and is fast but lacks accuracy. Further development of ICC, such as iccMAX, proposes either spectrally offsetting monochromatic colors or using a table for the CMYK portion and changing the value for each additional color. In either case, adding individual colors is highly inaccurate because it does not, or does not adequately, consider the interactions of the overprint colors in which these colors are involved.

[0018] Although there are more accurate models for more appropriately calculating the overprint operation of color mixing, such models are not suitable for high-speed processing applicable to the conversion of millions of pixels. Furthermore, although the models provide Lab values or spectra, they do not provide the color values of the device, so they are not suitable for direct conversion between devices ("device link"). This is because the color values of the output device often follow special separation rules (see below) and usually require specific processing to improve quality. However, the conversion to device color has become very common.

Prior Art Documents

Patent Documents

[0019]

Patent Document 1

Patent Document 2

Non-Patent Documents

[0020]

Non-Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0021] The invention aims to improve the method of performing color space conversion so that while using a normal multi-dimensional table having the highest possible accuracy, high throughput is achieved for color conversion and at the same time, the conversion in each color space can be comprehensively controlled.

Means for Solving the Problems

[0022] A technical solution to this problem is provided by a method having the features described in claim 1 of the claims. Further advantages and features are revealed in the dependent claims.

[0023] The number and types of colors targeted by the project are given, i.e., n colors in the supplier's color space. These include standard colors, basic colors, etc. They may also include, for example, brand-specific special colors.

[0024] Furthermore, m values ​​from the color space of the supply destination are specified.

[0025] The conversion is performed using a conversion table.

[0026] According to the present invention, all color combinations of n colors in a source color space whose color components are non-zero are determined. For each of these color combinations, a sub-region table is generated and stored. Finally, all true subsets, including a null set for each of these sub-space transformation tables, are generated and stored as separate redundant sub-space transformation tables.

[0027] The entire set of stored subspace transformation tables is applied to the transformation by assigning a subspace transformation table corresponding to each combination of n color components, based on the non-zero color components.

[0028] The present invention has the advantages of making the selection of an appropriate transformation table easier, ensuring that the selected table has the smallest possible dimensions (and therefore the most efficient interpolation), and eliminating the need to painstakingly augment it with empty dimensions to ensure that the data to be ultimately transformed matches an existing larger table. Furthermore, redundant tables require little to no additional memory.

[0029] According to another advantageous proposal of the present invention, instead of generating a subspace transformation table, an existing one is determined and stored. This eliminates the computational procedure.

[0030] Some color pairs, such as complementary colors, are not used together because their printing variations affect opposite color directions, making them an unstable combination. Intermediate colors can be achieved much more easily and stably with other colors (for example, gray tones of black).

[0031] In a typical, standard print screen, only four patterns can be overprinted without interference noise (moire) or sensitivity to alignment errors (register variations); therefore, in this case, the screen colors are limited to four or fewer. Even without such limitations imposed by screen technology, a combination of three to four colors is usually sufficient.

[0032] Furthermore, the total ink coverage is limited, and in many cases, from a printing technology (adhesion, drying) perspective, processing is only successful with a total coverage of 200% to 400%. This eliminates the need to consider combinations exceeding the total ink coverage, thus providing a benchmark for reducing the amount of data generated and stored.

[0033] These rules initially relate to the source color space Z for generating separation in color conversion, but as soon as the print data becomes available, they can also become the source for determining the color appearance. Therefore, these rules also address the potential possibility of any combination of colors in the source color space Q occurring.

[0034] According to the present invention, all necessary or specified combinations of n colors in the source color space Q are the n colors in the source color space Q, and a subspace conversion table is stored for each combination. Here, m color combinations in the destination color space Z are assigned to each color combination in the source color space Q, and these subspace tables are used for color space conversion. Extracting the m colors in the destination color space Z from the table can be done directly or indirectly, for example, after corresponding additional calculations or interpolation.

[0035] A method for converting color data in a project from a source color space with n colors to a destination color space with m colors, based on a conversion table in which multiple input color data from the source color space correspond to one of the output color data from the destination color space, is used to generate color data for all input color data in the project using the conversion table. The corresponding output color data is then obtained directly or indirectly from the input color data conversion table, making it available within the dataset. The color data of each layout object in the project that exists in the source color space is converted to some extent to the color data in the destination color space.

[0036] This invention enables accurate table storage and direct conversion (from n colors Q to m colors Z) even when many colors are used. To this end, the number of stored entries is efficiently reduced according to this invention.

[0037] Therefore, according to the present invention, instead of storing an exhaustive table of the entire n-dimensional color space, it is proposed to store a subspace table. Each of the n colors must exist in at least one subspace. By selecting k colors from the n colors, a k-dimensional subspace is generated.

[0038] According to the advantageous proposal of the present invention, each of the n colors is sampled in the same manner from 0% to 100% in all the subspaces in which it occurs, in order to ensure consistency. According to the present invention, it is assumed that the subspaces have identical duplicate entries across them. These entries must be consistent from the standpoint of consistency. For example, each table contains duplicate k-dimensional zero combinations (entries in the unprinted substrait).

[0039] In this invention, a normal color conversion (i.e., each combination of n colors to be converted) can be employed. That is, for each input color, n non-zero components are determined. Thus, the corresponding subspace is determined. Here, it is checked whether a table exists for this subspace, which applies if all relevant color combinations are considered. Next, the non-zero input values ​​are interpolated.

[0040] Interpolation can be performed using k-dimensional interpolation methods, such as multilinear interpolation or n-simplex interpolation.

[0041] If no matching table exists, the request is invalid. In other words, in this case, the input color data is outside the combination of the n color subsets provided by the project. Then, for example, to indicate that the input color data does not meet the requirements, the process can be aborted or a special signal color can be generated as the output color data. This makes it possible to combine and adopt any different subspaces in a way that perfectly aligns with the requirements of the application.

[0042] To apply the associated subspaces more quickly, it has been proposed to store all low-dimensional subspaces as separate duplicate copies of the stored subspace. Due to the exponential size relationship, these additional low-dimensional copies are small compared to the actual data.

[0043] According to the present invention, in the table structure, by eliminating redundancy in the saved file format, that is, by first saving a zero-dimensional subspace, then saving a one-dimensional subspace added without a zero level, and then saving a two-dimensional subspace added without a zero level, the same values ​​are guaranteed in redundant tables. When reading, an incomplete subspace is completed by adding a zero level from the low-dimensional table.

[0044] Furthermore, this invention proposes an efficient way to find and assign subspaces by representing subspaces with binary values ​​that assign bits to each of the n dimensions. If the color value is greater than 0, the bit is set to 1; otherwise, it is set to 0. Therefore, up to 2 n The allocation of the subspace table is 0-2 n This can be done directly via a list that has an entry of -1.

[0045] While using many subspace tables provides maximum flexibility, there may be cases where using a homogeneous and exhaustive subspace table is advantageous. For example, if convention dictates that only subspaces of the same dimension k can be used, and all combinations of k can be stored among n subspaces, then meaningless combinations (e.g., complementary colors or combinations of colors on the same color wheel) cannot be omitted. This eliminates the need for generation, visualization, or editing programs to distinguish between existing and non-existent table entries. However, since it is easy to determine the degree of homogeneity or exhaustion of a subspace structure when it is loaded, it is not necessary to specify it.

[0046] According to the present invention, in a homogeneous and exhaustive subspace table, in this simplified case, it is proposed to select the value k collectively so that all related (transformed) color combinations are covered. As mentioned above, a reasonable size possible in the field of graphics is k=4. Thus, a table is generated for all related combinations that can be formed from 4 colors. Next, a real subset including the empty set (i.e., direct printing onto the subset) is generated, and the subspace transformation table is determined.

[0047] The entries in the subspace transformation table are usefully mapped to a linear grid, that is, to the Cartesian product of all combinations of k desired tonal levels from the n input colors that occur in the subspace.

[0048] The present invention will be further described below with reference to examples. Further advantages and features of the present invention arise therefrom.

[0049] As a first example, consider a supplier color space with colors C, M, Y (n=3). For explanatory purposes, a 3D table is not stored; instead, all subspaces with simultaneously occurring colors k=2 are stored. Thus, three subspaces, CM, CY, and MY, are stored. If only these tables are available, queries with fewer than two colors, such as M only, must first be mapped to one of the matching subspaces, which is either CM or MY. Since table consistency is required, either table is acceptable. However, in either case, additional zeros must be correctly added to the 2D table interpolation (C=0 as the first value in CM, or Y=0 as the second value in MY). Thus, cumbersome assignment and addition are required.

[0050] However, if a one-dimensional subspace M already exists, it can be used directly, eliminating the need for additional subspaces. A further advantage is that multidimensional interpolation is faster due to the smaller table size. In the case of zero dimensions, only one data point needs to be read. Therefore, it is highly convenient as it has a table of additional overlapping low-dimensional subspaces that can be used for transformation.

[0051] If there is redundancy, it can be easily supplemented from the stored subspaces. See also Figure 3. Therefore, all low-dimensional subspaces are generated from CM, CY, and MY.

[0052] From CM, a one-dimensional table corresponding to C(M value 0) and M(C value 0) may be added.

[0053] From C, a 0-dimensional table of unprinted subsets (C value 0) may be added. The same applies to M, but it already exists.

[0054] Since C already exists, only the one-dimensional table Y (with a C value of 0) is added from CY.

[0055] Since M and Y already exist in MY, no further one-dimensional tables will be added.

[0056] Consider the size of the additional memory requirements for duplicate tables. If all colors have 10 levels, the stored tables CM, CY, MY will each have 10 levels. 2 = has 100 entries (total 300). Additional tables C, M, and Y each have 10 entries, and the 0-dimensional table of the subset has 1 entry (total of 31 additional generated entries). The number of additional entries needed is about 10% (331 entries instead of 300 entries), but this decreases further as n increases. On the other hand, in the case of an exhaustive CMY table that is not saved, 10 3 = Has 1,000 entries.

[0057] Furthermore, the above example clarifies the naming of tables using binary values. For the CMY colors, powers of 2 are assigned 4, 2, and 1. The three 2D subspaces have the binary values ​​CM: 4+2=6, CY: 4+1=5, MY: 2+1=3. The generated 1D table is C: 4, M: 2, Y: 1. The 0D table has substrait: 0. Therefore, all numbers from 0 to 6 are assigned to the subspace tables. Here, n = 2, which becomes a 3D full table. 3 The number -1=7 cannot exist in this example and is therefore excluded.

[0058] Referring to ensuring the same value in the redundant table by the non-redundant storage format, in the example of CM, an unprinted substrate (0 dimension) can be stored, and then C>0 with a 1-dimensional increment, M>0 with a 1-dimensional increment, and the 2-dimensional combination C>0+M>0 can be stored. Referring to Figure 4, upon reading, the unprinted substrate (zero entry) is read, and then the 1-dimensional gradation C>0 with 0 added to complete the C table is read, and then the 1-dimensional gradation M>0 with 0 added in the same way to complete M is read. Thereafter, the 2-dimensional combination C>0+M>0 with 0 added at the corners and 1-dimensional C and M added at the ends to complete CM is read. For example, other tables for CY, MY are the same.

[0059] In another example, consider 7 colors (CMYK + 3 other colors) with a 17-step resolution (a typical CMYK resolution). The comprehensive table has 17 7 , having approximately 410 million table entries. On the other hand, when only a 4-dimensional subspace of k = 4 is required, there are 35 ways to select 4 out of 7 colors at the initial stage. Each of the 35 tables has 17 4 , approximately 84,000 table entries, and all together, it amounts to 29 million table entries. Here, combinations such as pairs of irrelevant colors are not yet excluded (see Figure 5). However, even at this stage, the number is more than 100 times less. This affects not only the storage space but also, for example, the generation calculation time that requires a complex model, etc. It becomes possible to quickly and accurately interpolate all color combinations with a maximum of k components.

[0060] The additional redundant subspaces generated for the conversion with k < 4 are 35 subspaces corresponding to 3 out of 7 colors, 21 subspaces corresponding to 2 out of 7 colors, 7 subspaces corresponding to 1 out of 7 colors, and 1 subspace having no color. In total, 35×17 3 +21×17 2 +7×17 1 +1×17 0 =178,144 entries, that is, only 6% of the additional main memory requirement.

[0061] In another example, we consider 15 colors (upper limit in the ICC profile) with 10 levels of resolution (all at 11%). For a complete table, 10 15 = 1 trillion table entries, which is too large. If you choose 4 colors from 15 colors, there are only 1,365 possibilities, and each of the 1,365 tables is 10 4 =10,000 table entries, so even when combined, there are approximately 13.65 million entries. For tables with additional redundancy, if there are 3 out of 15 colors (455), 2 out of 15 colors (105), 1 out of 15 colors (15), and 0 out of 15 colors (1), then 455 × 10 3 +105×10 2 +15×10 1 +1 × 10 0 This amounts to 465,651 entries, or about 3% of the additional main memory requirement. Since the memory requirement is well below 1GB, even more will be available.

[0062] This invention describes a novel method for preparing and providing a conversion table. This provides a novel device for performing the corresponding conversion, comprising a computer system with corresponding input / output devices and a processor and memory unit on which the conversion table according to the present invention is managed. A method for performing color space conversion is realized through a combination of hardware, data, and corresponding software.

[0063] This invention describes a practical and feasible solution for those skilled in the art that enables sufficiently fast and high-quality color space conversion to a color space, even with very high-resolution layouts and a large number of source colors, in a reliable printing system.

[0064] Further advantages and features will be explained below with reference to the drawings. The drawings are as follows: [Brief explanation of the drawing]

[0065] [Figure 1] FIG. 1 is a flowchart for explaining a process step. [Figure 2] FIG. 2 is a flowchart for explaining the conversion. [Figure 3] FIG. 3 shows the complement of the low-dimensional subspace table. [Figure 4] FIG. 4 constructs a subspace table from a storage without redundancy. [Figure 5] FIG. 5 is an exhaustive and highly relevant subspace table in the case of seven colors.

MODE FOR CARRYING OUT THE INVENTION

[0066] In FIG. 1, a displayed project 11 is shown. In step 12, all the color data of each layout object becomes available in the color space of a source having n colors.

[0067] In step 13, partial combinations are generated from k < n colors. In step 14, a subspace conversion table is generated for each partial combination. The actual subset is not shown here. In step 15, the color data of the n colors of each layout object is converted into the color data of m colors in the destination color space using the subspace conversion table in step 14. Thereby, in step 16, the print data is accumulated for result 17. The result is generated by an output device having m device colors.

[0068] Figure 2 shows the details of conversion 15. Input 21 is the color data of a layout object in a source color space having n colors for the object. In step 22, the corresponding subcombinations, including non-zero parts, are determined. In step 23, previously generated subspace tables and their true subsets are searched to check if a table exists that contains this subcombination 22. In step 24, the results are checked. If a subspace table 23 is generated that is suitable for input 21, it will be at least one suitable table in which the color data of m colors in the destination color space is determined as result 25. If no table is found, in step 26, an error is indicated, for example, by a signal color consisting of special m color values ​​in the destination color space for m colors.

[0069] As an example in the specification, Figure 3 shows three two-dimensional subspace tables 31, 32, and 33 corresponding to CM, CY, and MY. Overlapping one-dimensional subspace tables 34, 35, and 36 corresponding to C, M, and Y can be extracted from 31 to 33. Thus, C can be obtained from CM or CY, M from CM or MY, and Y from CY or MY. The overlapping zero-dimensional subspace table 37 contains only a subset of the unprinted subnetwork and can be obtained from any higher-dimensional table.

[0070] Figure 4 assumes a storage format without redundancy. All subspace tables are stored in abbreviated form, meaning they do not contain one or more null elements of any color. Therefore, there is no duplication between stored tables. The only exception is the zero element 41, which is a zero-dimensional table containing entries for unprinted substraits. The one-dimensional abbreviated tables 42, 43, and 44 corresponding to C, M, and Y are associated with the zero element 48 (corresponding to 41), thus becoming exhaustive one-dimensional subspace tables 49, 50, and 51, from which interpolation can be performed as usual. Similarly, the two-dimensional truncation tables 45, 46, and 47 are interpolated by the lower-dimensional tables and yield tables 52, 53, and 54. The same process continues for all stored truncation tables.

[0071] Figure 5 shows an exhaustive list 62 of all four-dimensional subspaces in the case of the source color space 61, which has seven colors: C, M, Y, K, O, G, and V. There are 35 combinations of selecting four of the seven colors. If a printing project does not use color combinations that include complementary colors, the required list is reduced to eight subspaces, as shown in 63. If each of the additional colors O, G, and V is used only in its own hue sector, i.e., not simultaneously, then only four subspaces remain, as shown in List 64. [Explanation of symbols]

[0072] 11 Project in a supplier color space with n colors Layout object with 12 color data 13k <n個の色となる部分的な組み合わせのリスト14. Generation of subspace tables 15-color data conversion 16. Print data in the supplier's color space Z 17 Printing using an output device 21 Input of color data from a supplier's color space with n colors 22. Determination of subcombinations 23 Searching subspace tables 24. Checking the results 25. Application of the table and output of color data in the destination color space. 26 Error Notification 31, 32, 33 Saving subspace tables 34, 35, 36, 37 Extracted low-dimensional tables 41 0-dimensional table 42, 43, 44 One-dimensional table without zero values 45, 46, 47 Two-dimensional table without zero values 48 0 elements 49, 50, 51 One-dimensional table with 0 elements 52, 53, 54 One-dimensional table with 0 elements 61 7-color color space of the supplier 62 List of 4-dimensional subspaces 63 Reduction by abandoning complementary colors 64 Reduction through additional color separation

Claims

1. A method for performing computer-assisted conversion of color data from a source color space to a destination color space in a printing project, which is a series of processes for printing color printed products, using a conversion table based on conversion rules, wherein each of the multiple input color data in the source color space is assigned a unique output value in the destination color space, the source color space contains n colors, the destination color space contains m values, the values ​​in the destination color space are generated for all the input color data in the printing project using the conversion table, and the output values ​​corresponding to the input color data are obtained from the conversion table and provided in a dataset. Step a) Determine all color combinations for n colors in the color space of the supplier, where the color components are not zero. Step b) For each of these color combinations, generate and store a subspace transformation table. Step c) From each of the aforementioned subspace transformation tables, generate all lower-dimensional subspace transformation tables that include an empty set where all color component values ​​are zero, by progressively reducing the number of dimensions, and store them as separate redundant subspace transformation tables. A method characterized in that, for each input having n color components, the subspace transformation table stored in the corresponding step b) or step c) is used for color transformation by assigning the subspace transformation table stored in step b) or step c) based on the non-zero color components, in step d).

2. The aforementioned step b) is, Step b1) Determine and save the already generated subspace transformation table for the color combination determined in step a), Step b2) For each color combination for which the subspace transformation table already generated in step b1) has not been determined, generate and store a subspace transformation table. The method according to claim 1, characterized in that it can be divided into two parts.

3. The method according to claim 1 or 2, characterized in that for each of the n input colors of the supplier, a stepwise gradation from 0% to 100% is determined according to a predetermined accuracy for the project, and these gradations are used to generate the subspace transformation table stored in step c).

4. The method according to claim 3, characterized in that the output value is interpolated when applying the redundant subspace transformation table stored in step c).

5. The color space values ​​of the aforementioned supplier are device-dependent values. The method according to claim 4, characterized in that

6. The method according to claim 5, characterized in that the printing project is a printing project in which the total number of colors that can be processed by the printing technology is limited by the number of colors n in the supplier's color space, and only subspace conversion tables that do not exceed the total input color data that can be processed in the printing project are stored and used.

7. The method according to claim 4, characterized in that the color space values ​​of the recipient are device-independent values.

8. The subspace transformation table is for the i-th color that occurs within a subset of the total n colors numbered from 0 to n-1, at position 2 ｉ The method according to claim 7, characterized in that each input color data is indexed by a binary value having set bits, and similarly, each input color data is further specified by a binary value having n non-zero component set bits, thereby allowing the corresponding subspace transformation table to be directly selected via the binary value of the input color data.

9. The method according to claim 8, characterized in that the method is performed on a computer unit by control software, the computer unit comprises an input unit that provides digital color data of the project, an output unit that outputs converted color data, and a memory that stores the conversion table, and the values ​​of the destination color space are generated by the control software for inputting the color data of the project using the conversion table and provided as a dataset.

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