CN112511717A - Mapping method and device of RGB image data, storage medium and electronic equipment - Google Patents
Mapping method and device of RGB image data, storage medium and electronic equipment Download PDFInfo
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Abstract
The embodiment of the disclosure provides a mapping method, a mapping device, a storage medium and electronic equipment of RGB image data, wherein the method comprises the steps of acquiring an image histogram based on the RGB data of a preset image; determining a CIELab data mapping relation based on the image histogram and the output parameter value; and acquiring the RGB data mapping relation of converting the preset image into an output image based on the CIELab data mapping relation. The embodiment of the disclosure is based on an automatic mapping framework to realize that RGB image data is converted into standard data of a printing image, and can promote the working process, automation and intellectualization of printing digitalization, wherein the intellectualization is embodied as follows: 1) one-click is finished, the system automatically provides recommended results, and the user selects a favorite result; 2) the guide type operation is carried out, the system prompts and guides an operator to gradually finish the effect preview of the expected printing, and the personalized adjustment is embodied; 3) the process integration level is high, the RGB image is input, and a result graph meeting the requirements of the pre-printing condition is output.
Description
Technical Field
The embodiment of the disclosure relates to the technical field of image conversion, and in particular, to a mapping method and device of RGB image data, a storage medium, and an electronic device.
Background
In computer interface devices, there are many products at the input and output ends of an image, such as scanners, digital cameras, displays, inkjet printers, color laser printers, digital printers, etc., and different output and input devices involve different color-rendering operation principles, such as some display modes of RGB data and some display modes of CMYK data.
Taking the example that the input end adopts the scanner and the output end adopts the display, because manufacturers for manufacturing the display and the lamp tube of the scanner are numerous, the displayed colors cannot be uniform due to different qualities and capabilities, and the colors do not have consistent color standards after self-adjustment by users; in addition, printing ink and color toner are available in many brands, so that different works can be produced by using different consumables for the same file, even if the same consumable is used, the different works can be different if the different works are printed on different devices, and perfect color management is necessary to reduce the difference of colors on different devices and systems. Even the same type of electronic equipment, such as a color inkjet printer, may have differences in the definition of the description of the color due to differences in the manufacturers of the designs. Therefore, when a user uses different devices for image input or output, distortion or errors may occur.
In the print image copy job ratio in which a digital photograph acquired by an electronic device such as a digital camera is used as an original, the digital photograph is merely represented as data, unlike a photograph or other actual original, and a client and a print technician can communicate with each other according to the actual object to adjust an image copy process, and can predict a print effect and complete image copy, compared with a print image copy job in which a film or film is used as an original. The digital photos can only show the effect through the display equipment, and because the scenes during shooting cannot be or are difficult to reproduce, the basis for judging the image reproduction effect of photographers and printing technicians is lost, and certain difficulty exists in achieving consensus on the printing and copying process. At present, for the copying work of images such as digital photos, professional technicians often use professional equipment and software to make a consensus with customers through repeated adjustment processes.
In the existing print image copying process based on the RGB color scheme, based on the ICC color management technique, the RGB image is displayed on a color-corrected display, and in a standard viewing environment, the image is adjusted in specialized image processing software by experienced printing technicians with reference to the relevant printing conditions. In the prior art, the main work of image copying in the RGB mode includes: 1) setting a working environment to meet the requirements of ISO 3664; 2) a professional display is used, the software and hardware of the display meet the requirements of ISO12646, the calibration and characterization of the display are completed, and the requirements of soft proofing specified by ISO 1486 are met; 3) displaying an image using image adjustment software supporting an ICC color management technique; 4) skilled prepress technicians adjust highlight and dark dots, gray balance, gradations, colors and the like of the image to achieve the expected printing reproduction effect; 5) performing soft sampling or digital sampling, and inviting clients to sign according to the requirements of ISO 12647-8 or ISO 12647-7; 6) If the client agrees, the printing is delivered; 7) if not agreed with the customer, the process of 4) through 6) is repeated. Currently, printing technologies based on RGB digital image data are used, and a skilled printing technician can reproduce the results to the satisfaction of customers according to the corresponding standards or technical specifications. The process technology is a classic printing copying technology based on ICC color management, in recent years, various industry associations develop process control specifications matched with corresponding process control specifications, such as PSO, G7, C9 and the like, which are suitable for lithographic printing to meet the process control specifications required by ISO 12747-2, the requirements of process correction, control and the like on specialization of operators are high, the process correction and control are often completed by industry experts, and image copying work is completed by printing operators before printing and according to established conditions.
The artificial intelligence technology is promoting the change of all industries, the change of the working process of the printing technology is always promoted in the automatic working process from image output to printing or printing, particularly short-version printing, the requirements are met by the requirements of mass consumers in a quick and personalized design, the prior art does not meet the requirements of mass consumers for standing and the like, a user uploads an image to a system or a platform through a simple platform or the system, the adjustment of the image effect is completed by self according to the automatic prompt of the platform, the preview of the printing effect is achieved, professional technicians are not needed to participate, the samples are signed at once, and the working mode of printing is handed over.
Disclosure of Invention
In order to improve the above problems, it is therefore an object of the embodiments of the present disclosure to provide a method, an apparatus, a storage medium, and an electronic device for mapping RGB image data, so as to solve the above problems in the prior art.
In order to solve the technical problem, the embodiment of the present disclosure adopts the following technical solutions: a mapping method of RGB image data, comprising the steps of: acquiring an image histogram based on RGB data of a predetermined image; determining a CIELab data mapping relation based on the image histogram and the output parameter value; and acquiring the RGB data mapping relation from the preset image to the output image based on the CIELab data mapping relation.
In some embodiments, the acquiring an image histogram based on RGB data of the predetermined image includes: acquiring a preset image; acquiring CIELab data based on the RGB data of the predetermined image; and drawing an image histogram based on the CIELab data.
In some embodiments, the obtaining CIELab data based on RGB data of the predetermined image is performed by a color profile embedded in the predetermined image.
In some embodiments, the determining a CIELab data mapping relationship based on the image histogram and the output parameter value includes: acquiring a first tone range of the predetermined image based on the image histogram; acquiring a second order range of the output image based on the output parameter value; and determining a CIELab data mapping relation based on the first tonal range and the second tonal range.
In some embodiments, the obtaining of the first tone range of the predetermined image based on the image histogram is implemented by: extracting CIELab values of the brightest and darkest pixel points from the image histogram; traversing the data of the preset image, and marking the areas of the brightest and darkest pixel points in the image histogram; respectively determining an image white field or an image black field based on the areas where the brightest and darkest pixel points are located, thereby calculating the average brightness value of each area; determining a first tonal range for the predetermined image based on the average luminance value.
In some embodiments, further comprising: and adjusting the RGB data mapping relation based on the color difference between the output image and the predetermined image.
In some embodiments, said adjusting said RGB data mapping based on a color difference of an output image and said predetermined image comprises: acquiring an output image based on the mapping relation between the predetermined image and the RGB data; determining sample CIELAB values for tone sample points in a predetermined color patch based on the output parameter values; determining a comparison sample point in the output image based on the sample CIELab value; obtaining a color difference based on the sample CIELab values and the comparison CIELab values of the comparison sample points; and adjusting the RGB data mapping relation based on the color difference.
The present disclosure also provides an apparatus for mapping RGB image data, which includes:
the device comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring an image histogram based on RGB data of a preset image; a determining module for determining a CIELab data mapping relation based on the image histogram and an output parameter value; and the second acquisition module is used for acquiring the RGB data mapping relation of the conversion from the preset image to the output image based on the CIELab data mapping relation.
The present disclosure also provides a storage medium storing a computer program, wherein the computer program is configured to implement the steps of any one of the above methods when executed by a processor.
The present disclosure also provides an electronic device comprising at least a memory and a processor, wherein the memory stores a computer program, and wherein the processor implements the steps of any one of the above methods when executing the computer program on the memory.
The impetus of the embodiment of the disclosure is placed at the conversion stage of 'converting RGB digital image data into printing standard reference data', which is different from the prior art that the technical scheme provides an intelligent mapping system, and three difficulties in the prior art are simplified: in the prior art, the adjustment of the RGB digital image data can be completed only by using a tool with high specialization degree by a professional; both, the cost of agreeing with the customer in the adjustment process is high; three, the modules of the prior art work are scattered, and multiple people are needed to cooperate to complete the work.
The beneficial effects of this disclosed embodiment lie in: the embodiment of the disclosure provides a mapping method for converting RGB image data into RGB image data of standard printing image data by adopting an automatic mapping frame, and according to the mapping frame, the working process, automation and intellectualization of printing digitization can be promoted. The requirement threshold to user operation of this disclosed embodiment is low, and operation flow is simple, and wherein, the intellectuality embodies: 1) one-click is finished, the system automatically provides recommended results, and the user selects a favorite result; 2) The guide type operation is carried out, the system prompts and guides an operator to gradually finish the effect preview of the expected printing, and the personalized adjustment is embodied; 3) the process integration level is high, the RGB image is input, and a result graph meeting the requirements of the pre-printing condition is output.
Drawings
In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the present disclosure, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a schematic flowchart of a mapping method of RGB image data according to an embodiment of the disclosure;
FIG. 2 is a schematic structural diagram of an apparatus for mapping RGB image data according to an embodiment of the present disclosure;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the disclosure.
Detailed Description
Various aspects and features of the disclosure are described herein with reference to the drawings.
It will be understood that various modifications may be made to the embodiments of the present application. Accordingly, the foregoing description should not be construed as limiting, but merely as exemplifications of embodiments. Those skilled in the art will envision other modifications within the scope and spirit of the disclosure.
The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments of the disclosure and, together with a general description of the disclosure given above, and the detailed description of the embodiments given below, serve to explain the principles of the disclosure.
These and other characteristics of the present disclosure will become apparent from the following description of preferred forms of embodiment, given as non-limiting examples, with reference to the attached drawings.
It should also be understood that, although the present disclosure has been described with reference to some specific examples, a person of skill in the art shall certainly be able to achieve many other equivalent forms of the disclosure, having the characteristics as set forth in the claims and hence all coming within the field of protection defined thereby.
The above and other aspects, features and advantages of the present disclosure will become more apparent in view of the following detailed description when taken in conjunction with the accompanying drawings.
Specific embodiments of the present disclosure are described hereinafter with reference to the accompanying drawings; however, it is to be understood that the disclosed embodiments are merely exemplary of the disclosure that may be embodied in various forms. Well-known and/or repeated functions and constructions are not described in detail to avoid obscuring the disclosure in unnecessary or unnecessary detail. Therefore, specific structural and functional details disclosed herein are not to be interpreted as limiting, but merely as a basis for the claims and as a representative basis for teaching one skilled in the art to variously employ the present disclosure in virtually any appropriately detailed structure.
The specification may use the phrases "in one embodiment," "in another embodiment," "in yet another embodiment," or "in other embodiments," which may each refer to one or more of the same or different embodiments in accordance with the disclosure.
A first embodiment of the present disclosure relates to a mapping method of RGB image data, by which it is possible to output an image for printing or printing meeting a predetermined condition or standard in a case where a predetermined image with RGB data is input, so as to ensure that a color difference of the output image is within a predetermined range, as shown in fig. 1, the mapping method specifically includes the following steps:
s101, acquiring an image histogram based on RGB data of a predetermined image.
In this step, RGB data of a predetermined image is acquired based on the input predetermined image, and an image histogram is acquired based on the RGB data of the predetermined image.
The RGB data of the predetermined image herein refers to color information of each element point in the predetermined image, the color information being represented in the form of RGB data. The Image Histogram (Image Histogram) is widely used in computer vision processing, and generally obtains color change information by marking significant edges and statistical changes of colors, and is simply a statistical graph representing the data distribution of the luminance distribution in a digital Image, counting the number of pixels of each luminance value in the Image, so that the Image Histogram herein is a way of counting color data, and assigning the statistical value to a series of well-defined bins, which are considered as "bars" or "pitches" in the Image Histogram, and the value of the bin is a feature statistic calculated from the data, such as gradient, direction, color or any other features. Further, the acquiring an image histogram based on the RGB data of the predetermined image includes the following steps:
s201, acquiring a preset image.
In this step, it is first necessary to acquire an input predetermined image, where the predetermined image is a predetermined image that needs to be subjected to subsequent processing such as printing, etc. by user input, and where the predetermined image may be an image that is acquired by an electronic device such as a mobile terminal, a digital camera, a scanner, etc. and stored and presented in the form of RGB data.
S202, acquiring CIELab data based on the RGB data of the preset image;
through the predetermined image obtained in step S201, RGB data in the predetermined image may be obtained based on the predetermined image analysis, and in this step, CIELab data may be obtained based on the RGB data of the predetermined image. It should be noted that CIELab is a color system of the international commission on illumination (CIE), belongs to the color system, the Lab mode or Lab color space is a color mode published by the international commission on illumination in 1976, is a color mode theoretically including all colors visible to the human eye determined by the international commission on illumination, and the Lab mode makes up for the deficiencies of the two color modes of RGB and CMYK. The Lab pattern consists of three channels, the first of which is the lightness, i.e., "L", and in addition, the color of the a-channel is from red to dark green and the color of the b-channel is from blue to yellow. In the existing color mode, the most comprehensive is Lab mode, the next is RGB mode, and the narrowest is CMYK mode in the expression color range. That is, the Lab mode defines the most colors, and is used as a transmission medium to keep the appearance of all colors consistent, and when transferring colors between different devices, the colors do not change and are independent of light and device, and the processing speed is as fast as the RGB mode, several times faster than the CMYK mode.
In this step, since manufacturers of different pre-press electronic devices have different definitions of RGB or CMYK colors, so that the same RGB or CMYK image data can be presented with different colors on different systems and electronic devices, the ICC file is used as a basis and standard for color conversion between different devices, so that colors can be consistently presented on different electronic devices. In one embodiment, the conversion of the predetermined image from RGB data to CIELab data may be achieved, for example, by a color profile ICC which maps all device-dependent color data (e.g., RGB and CMYK data) into a device-independent Lab color pattern.
Specifically, considering that a general electronic device is previously installed with a color profile ICC file, by reading input data of the predetermined image, it is possible to determine whether the predetermined image is embedded with the color profile ICC file by acquiring header file information of the predetermined image; if a color profile ICC file is embedded in the header file information of the predetermined image, conversion of "RGB-CIELAB" in the color profile ICC file may be performed to acquire data of the RGB data of the predetermined image in Lab mode, i.e., CIELAB data; if the ICC file is not embedded in the header file information of the predetermined image, conversion can be achieved in a form by installing a color characteristic ICC file.
S203, drawing an image histogram based on the CIELAB data
After the CIELab data of the predetermined image is acquired in the above step S202, in this step, an image histogram is drawn by the RGB data of the predetermined image and the CIELab data acquired in the above step S202. Here, the method for drawing the image histogram based on the CIELab data in the Lab mode may adopt any conventional method, and the details of the disclosure are not repeated herein.
S102, determining a CIELab data mapping relation based on the image histogram and the output parameter value.
After the image histogram is obtained based on the RGB data of the predetermined image in step S101, in this step, a mapping relationship of CIELab values is determined based on the image histogram and the output parameter values. In this step, the image histogram represents the CIELAB data of the input image, i.e., the predetermined image, the output parameter value represents the CIELAB value of the output image, and the CIELAB value mapping relationship between the input image and the output image is determined based on the two CIELAB values. The determining of the CIELAB mapping relation based on the image histogram and the output parameter values specifically comprises the following steps:
s301, acquiring a first tone range of the preset image based on the image histogram.
After the image histogram is obtained based on the step S101, in this step, CIELab values of the brightest and darkest pixel points in the image histogram are extracted from the image histogram, and RGB values of the brightest pixel points and corresponding CIELab values are stored.
Further, according to the RGB data and CIELab values of the brightest and darkest pixel points, traversing the data of the predetermined image, marking the areas where the brightest and darkest pixel points are located in the image histogram, and determining, for example, a 3 × 3 or 5 × 5 continuous area as an image white field or an image black field by intelligently identifying an image black and white field, thereby calculating an average brightness value of each area, where the brightness value is recorded in a CIELab value format, thereby determining a first tone range of the predetermined image, wherein a tone in the tone range is an optical representation of an area with uniform brightness in image information restoration, and the tone value is a measure of a tone, and is generally expressed by a degree of transmission or reflection of light in a printing technology.
S302, acquiring a second tone range of the output image based on the output parameter value.
In the first tonal range of the predetermined image obtained by the above step S301, in this step, it is also necessary to obtain a second tonal range of the output image based on determining and setting output parameter values of the image data for printing or printing, where the output parameter values may be determined based on the user' S purpose for outputting the image, for example: for office printing/for network transmission or the like, output parameter values are determined and set by output purposes, where the output parameter values are recorded in, for example, a color profile ICC file. Based on the output parameter values of, for example, the color characteristic ICC profile, the second gradation range of the output image is extracted and acquired, and recorded in the format of CIELab values.
S303, determining a CIELab data mapping relation based on the first tonal range and the second tonal range.
After the first pitch range of the predetermined image and the second pitch range of the output image are obtained in step S301, in this step, a pitch compression ratio from the predetermined image to the output image is determined based on the first pitch range and the second pitch range, and a CIELab data mapping relationship is determined based on the pitch compression ratio.
S103, acquiring an RGB data mapping relation of converting the preset image into an output image based on the CIELAB data mapping relation.
After determining the CIELab data mapping relationship in step S102, in this step, the RGB data mapping relationship of converting the predetermined image into the output image is obtained based on the CIELab data mapping relationship, which may be implemented by, for example, a color profile ICC, and the inverse operation of the CIELab-to-RGB image data in the color profile ICC embedded in the predetermined image is called to complete the mapping of the CIELab data mapping relationship to the RGB data mapping relationship.
The embodiment of the disclosure can promote the printing digitization work flow, automation and intellectualization. The embodiment of the disclosure has low threshold for the requirement of user operation, simple operation process and intelligent implementation: 1) one-click is finished, the system automatically provides recommended results, and the user selects a favorite result; 2) guiding operation is performed, and the system prompts and guides an operator to gradually finish the effect preview of expected printing, so that personalized adjustment is embodied; 3) the process integration level is high, the RGB image is input, and a result graph meeting the requirements of the pre-printing condition is output.
A second embodiment of the present disclosure provides a mapping method of RGB image data, which includes the above steps S101 to S103 in the above first embodiment, and specifically, further includes the following steps:
and S104, adjusting the RGB data mapping relation based on the color difference between the output image and the preset image.
In this step, a comparison is further performed between the predetermined image and the output image to adjust the RGB data mapping relationship accordingly, so that the output image meets the requirements of the predetermined output parameter value and the conditions such as color difference. Specifically, the adjusting the RGB data mapping relationship based on the color difference of the output image and the predetermined image includes the steps of:
s401, acquiring an output image based on the predetermined image and the RGB mapping relation.
In this step, firstly, the output image is obtained based on the mapping relation between the predetermined image and the RGB data, and the output image is an image conforming to an output parameter value; preferably, after the output image is acquired, the input image and the mapping result of the input image, i.e. the output image, may be displayed in parallel in the system user interface, so as to facilitate comparison by the user, and simultaneously output the image-converted contrast ratio.
S402, sample CIELAB values of the tone sample points are determined in the predetermined color patches based on the output parameter values.
After the output image is acquired by the above-described step S301, in this step, the sample CIELAB values of the gradation sample points are determined in the predetermined patches based on the output parameter values, specifically,
predetermined patches need to be determined first, and RGB patches of all combinations 0/255, 52/255, 94/255, 143/255, 197/255, 255/255 may be extracted as predetermined patches from the color profile ICC embedded in the predetermined image, for example, according to ISO 16760. Further, for example, CIELab values of highlight sample points, halftone sample points, and light and dark sample points may be extracted from the output image according to the color profile ICC, where the highlight sample points may be sample points with CMYK values of (5%, 3%, 3%, 0), the halftone sample points may be sample points with CMYK values of (50%, 41%, 39%, 0), and the light and dark sample points may be sample points with CMYK values of (65%, 53%, 51%, 95%).
S403, determining comparative sample points in the output image based on the sample CIELab values.
After the sample CIELab values of the gradation sample points are determined through the above steps, in this step, the neutral gray curve of the output image is extracted with the sample CIELab values of the gradation sample points as target values, and points on the neutral gray curve that are closest to the three target values are marked as comparison sample points.
S404, obtaining a color difference based on the sample CIELab value and the comparison CIELab value of the comparison sample point.
In this step, after the sample CIELab value and the comparison sample point are obtained, a color difference is calculated based on the sample CIELab value and the comparison CIELab value of the comparison sample point to determine an effect of gray balance adjustment of the output image. Here, the so-called color difference is evaluated for the effect before and after image conversion by using the maximum color difference, the average color difference, or the like as an evaluation index.
S405, adjusting the RGB data mapping relation based on the color difference.
After the color difference is obtained in step S304, the color difference is judged and evaluated in this step to determine whether the RGB data mapping relationship is appropriate, for example, when the average color difference satisfies Δ E00 ≦ 4 or the maximum color difference satisfies Δ Eab ≦ 6, it is determined that the RGB data mapping relationship does not need to be adjusted if a satisfactory effect is considered to be achieved, and of course, when the average color difference or the maximum color difference does not satisfy the above-mentioned condition, it is determined that the RGB data mapping relationship needs to be adjusted.
The embodiment of the disclosure can promote the printing digitization work flow, automation and intellectualization. The embodiment of the disclosure has low threshold for the requirement of user operation, simple operation process and intelligent implementation: 1) one-click is finished, the system automatically provides recommended results, and the user selects a favorite result; 2) guiding operation is performed, and the system prompts and guides an operator to gradually finish the effect preview of expected printing, so that personalized adjustment is embodied; 3) the process integration level is high, the RGB image is input, and a result graph meeting the requirements of the pre-printing condition is output.
A third embodiment of the present disclosure provides a mapping apparatus of RGB image data, by which it is possible to output an image for printing or printing meeting a predetermined condition or standard in a case where a predetermined image with RGB data is input, so as to ensure that a color difference of the output image is within a predetermined range, as shown in fig. 2, the mapping apparatus includes a first obtaining module 10, a determining module 20, and a second obtaining module 30, which are coupled to each other, specifically:
the first obtaining module 10 is configured to obtain an image histogram based on RGB data of a predetermined image.
By the first acquiring module 10, RGB data of a predetermined image is acquired based on the input predetermined image, and an image histogram is acquired based on the RGB data of the predetermined image.
The RGB data of the predetermined image herein refers to color information of each element point in the predetermined image, the color information being represented in the form of RGB data. The Image Histogram (Image Histogram) is widely used in computer vision processing, and generally obtains color change information by marking significant edges and statistical changes of colors, and is simply a statistical graph representing the data distribution of the luminance distribution in a digital Image, counting the number of pixels of each luminance value in the Image, so that the Image Histogram herein is a way of counting color data, and assigning the statistical value to a series of well-defined bins, which are considered as "bars" or "pitches" in the Image Histogram, and the value of the bin is a feature statistic calculated from the data, such as gradient, direction, color or any other features. Further, the image histogram is acquired based on the RGB data of the predetermined image, and the first acquiring module 10 includes the following parts:
a first acquisition unit for acquiring a predetermined image.
By the first acquiring unit, it is first necessary to acquire an input predetermined image, where the predetermined image is a predetermined image that needs to be subjected to subsequent processing such as printing, etc. by user input, and here, the predetermined image may be an image that is acquired by an electronic device such as a mobile terminal, a digital camera, a scanner, etc. and stored and presented in the form of RGB data.
A second acquisition unit configured to acquire CIELab data based on RGB data of the predetermined image;
through the predetermined image acquired by the first acquisition unit, the RGB data in the predetermined image may be analytically acquired based on the predetermined image, and through the second acquisition unit, the CIELab data may be acquired based on the RGB data of the predetermined image. It should be noted that CIELab is a color system of the international commission on illumination (CIE), belongs to the color system, the Lab mode or Lab color space is a color mode published by the international commission on illumination in 1976, is a color mode theoretically including all colors visible to the human eye determined by the international commission on illumination, and the Lab mode makes up for the deficiencies of the two color modes of RGB and CMYK. The Lab pattern consists of three channels, the first of which is the lightness, i.e., "L", and in addition, the color of the a-channel is from red to dark green and the color of the b-channel is from blue to yellow. In the existing color mode, the most comprehensive is Lab mode, the next is RGB mode, and the narrowest is CMYK mode in the expression color range. That is, the Lab mode defines the most colors, and is used as a transmission medium to keep the appearance of all colors consistent, and when transferring colors between different devices, the colors do not change and are independent of light and device, and the processing speed is as fast as the RGB mode, several times faster than the CMYK mode.
With the second acquisition unit, since manufacturers of different pre-press electronic devices have different definitions of RGB or CMYK colors, so that the same RGB or CMYK image data can be presented with different colors on different systems and electronic devices, using an ICC file as a basis and standard for color conversion between different devices enables colors to be consistently presented on different electronic devices. In one embodiment, the conversion of the predetermined image from RGB data to CIELab data may be achieved, for example, by a color profile ICC which maps all device-dependent color data (e.g., RGB and CMYK data) into a device-independent Lab color pattern.
Specifically, considering that a general electronic device is previously installed with a color profile ICC file, by reading input data of the predetermined image, it is possible to determine whether the predetermined image is embedded with the color profile ICC file by acquiring header file information of the predetermined image; if a color profile ICC file is embedded in the header file information of the predetermined image, conversion of "RGB-CIELAB" in the color profile ICC file may be performed to acquire data of the RGB data of the predetermined image in Lab mode, i.e., CIELAB data; if the ICC file is not embedded in the header file information of the predetermined image, conversion can be achieved in a form by installing a color characteristic ICC file.
A rendering unit for rendering an image histogram based on the CIELAB data
After CIELab data of the predetermined image is acquired by the second acquisition unit, an image histogram is drawn by the drawing unit through RGB data of the predetermined image and the CIELAB data acquired by the second acquisition unit. Here, the manner of drawing the image histogram based on the CIELab data in the Lab mode may be any manner known in the art, and the details of the disclosure are not repeated herein.
A determining module 20, configured to determine a CIELab data mapping relationship based on the image histogram and the output parameter value.
After the first obtaining module 10 obtains the image histogram based on the RGB data of the predetermined image, the determining module 20 determines the mapping relationship of CIELab values based on the image histogram and the output parameter values. By means of the determination module 20, the image histogram represents the case of CIELAB data of the input image, i.e. the predetermined image, and the output parameter value represents the CIELAB value of the output image, and the CIELAB value mapping relationship between the input image and the output image is determined based on these two CIELAB values. The determining module 20 specifically includes the following parts:
a third acquisition unit for acquiring a first tone range of the predetermined image based on the image histogram.
After the image histogram is acquired based on the first acquiring module 10, a third acquiring unit extracts CIELab values of the brightest and darkest pixel points in the image histogram from the image histogram, and simultaneously stores RGB values of the brightest pixel points and corresponding CIELab values.
Further, according to the RGB data and CIELab values of the brightest and darkest pixel points, traversing the data of the predetermined image, marking the areas where the brightest and darkest pixel points are located in the image histogram, and determining, for example, a 3 × 3 or 5 × 5 continuous area as an image white field or an image black field by intelligently identifying an image black and white field, thereby calculating an average brightness value of each area, where the brightness value is recorded in a CIELab value format, thereby determining a first tone range of the predetermined image, wherein a tone in the tone range is an optical representation of an area with uniform brightness in image information restoration, and the tone value is a measure of a tone, and is generally expressed by a degree of transmission or reflection of light in a printing technology.
A fourth acquiring unit for acquiring a second gradation range of the output image based on the output parameter value.
In the first gradation range in which the predetermined image is acquired by the third acquisition unit, the second gradation range in which the image is output is acquired by the fourth acquisition unit based on the determination and setting of the output parameter value of the image data for printing or printing, which may be determined based on the purpose of the user for outputting the image, for example: for office printing/for network transmission, etc., output parameter values are determined and set by the purpose of output, where the output parameter values are recorded in, for example, a color profile ICC file. Based on the output parameter values of, for example, the color characteristic ICC profile, the second gradation range of the output image is extracted and acquired, and recorded in the format of CIELab values.
A first determining unit, configured to determine a CIELab data mapping relationship based on the first and second tonal ranges.
After the third obtaining unit obtains the first tone range of the preset image and the fourth obtaining unit obtains the second tone range of the output image, the first determining unit determines the tone compression ratio from the preset image to the output image based on the first tone range and the second tone range, and the CIELab data mapping relation is determined based on the tone compression ratio.
A second obtaining module 30, configured to obtain an RGB data mapping relationship of the predetermined image to an output image based on the CIELAB data mapping relationship.
After the determining module 20 determines the CIELab data mapping relationship, the second obtaining module 30 obtains the RGB data mapping relationship from the predetermined image to the output image based on the CIELab data mapping relationship, for example, the RGB data mapping relationship may be realized by using a color profile ICC, and the inverse operation of the CIELab-to-RGB image data in the color profile ICC embedded in the predetermined image is called to complete the mapping from the CIELab data mapping relationship to the RGB data mapping relationship.
The embodiment of the disclosure can promote the printing digitization work flow, automation and intellectualization. The embodiment of the disclosure has low threshold for the requirement of user operation, simple operation process and intelligent implementation: 1) one-click is finished, the system automatically provides recommended results, and the user selects a favorite result; 2) guiding operation is performed, and the system prompts and guides an operator to gradually finish the effect preview of expected printing, so that personalized adjustment is embodied; 3) the process integration level is high, the RGB image is input, and a result graph meeting the requirements of the pre-printing condition is output.
A fourth embodiment of the present disclosure provides an apparatus for mapping RGB image data, which includes the first acquiring module 10, the determining module 20, and the second acquiring module 30 in the third embodiment, and specifically includes the following parts:
an adjusting module, configured to adjust the RGB data mapping relationship based on a color difference between an output image and the predetermined image.
On the basis of the predetermined image, an output image can be obtained through the RGB data mapping relationship obtained by the second obtaining module 30, and an adjusting module may further perform a comparison between the predetermined image and the output image to adjust the RGB data mapping relationship accordingly, so that the output image meets the requirements of predetermined output parameter values and conditions such as color difference. Specifically, the adjusting module includes the following parts based on the color difference between the output image and the predetermined image:
a fifth acquiring unit for acquiring an output image based on the predetermined image and the RGB mapping relation.
Acquiring, by the fifth acquisition unit, the output image, which is an image conforming to an output parameter value, first based on the predetermined image and the RGB data mapping relationship; preferably, after the output image is acquired, the input image and the mapping result of the input image, i.e. the output image, may be displayed in parallel in the system user interface, so as to facilitate comparison by the user, and simultaneously output the image-converted contrast ratio.
A second determination unit for determining sample CIELAB values of the tone sample points in the predetermined color patches based on the output parameter values.
After the output image is acquired by the fifth acquisition unit, sample CIELAB values of the gradation sample points are determined in predetermined patches based on the output parameter values by the second determination unit, specifically,
predetermined patches need to be determined first, and RGB patches of all combinations 0/255, 52/255, 94/255, 143/255, 197/255, 255/255 may be extracted as predetermined patches from the color profile ICC embedded in the predetermined image, for example, according to ISO 16760. Further, for example, CIELab values of highlight sample points, halftone sample points, and light and dark sample points may be extracted from the output image according to the color profile ICC, where the highlight sample points may be sample points with CMYK values of (5%, 3%, 3%, 0), the halftone sample points may be sample points with CMYK values of (50%, 41%, 39%, 0), and the light and dark sample points may be sample points with CMYK values of (65%, 53%, 51%, 95%).
A third determination unit for determining comparison sample points in the output image based on the sample CIELab values.
After the sample CIELab values of the gradation sample points are determined by the second determining unit, a neutral gray curve of the output image is extracted by a third determining unit with the sample CIELab values of the gradation sample points as target values, and points on the neutral gray curve closest to the three target values are marked as comparison sample points.
A sixth obtaining unit for obtaining a color difference based on the sample CIELab value and a comparison CIELab value of the comparison sample point.
And calculating a color difference based on the sample CIELab value and the comparison CIELab value of the comparison sample point after the sample CIELab value and the comparison sample point are acquired by a sixth acquisition unit so as to judge the gray balance adjustment effect of the output image. Here, the so-called color difference is evaluated for the effect before and after image conversion by using the maximum color difference, the average color difference, or the like as an evaluation index.
An adjusting unit for adjusting the RGB data mapping relation based on the color difference.
After the color difference is obtained by the sixth obtaining unit, the adjusting unit judges whether the RGB data mapping relationship is appropriate or not by judging and evaluating the color difference, for example, when the average color difference satisfies Δ E00 ≦ 4 or the maximum color difference satisfies Δ Eab ≦ 6, it is determined that the RGB data mapping relationship does not need to be adjusted if a satisfactory effect is achieved, and of course, when the average color difference or the maximum color difference does not satisfy the above-mentioned condition, it is determined that the RGB data mapping relationship needs to be adjusted.
The embodiment of the disclosure can promote the printing digitization work flow, automation and intellectualization. The embodiment of the disclosure has low threshold for the requirement of user operation, simple operation process and intelligent implementation: 1) one-click is finished, the system automatically provides recommended results, and the user selects a favorite result; 2) guiding operation is performed, and the system prompts and guides an operator to gradually finish the effect preview of expected printing, so that personalized adjustment is embodied; 3) the process integration level is high, the RGB image is input, and a result graph meeting the requirements of the pre-printing condition is output.
A fifth embodiment of the present disclosure provides a storage medium, which is a computer-readable medium storing a computer program that, when executed by a processor, implements the methods provided by the first and third embodiments of the present disclosure, including the following steps S11 to S13:
s11, acquiring an image histogram based on RGB data of a predetermined image;
s12, determining a CIELab data mapping relation based on the image histogram and the output parameter value;
and S13, acquiring the RGB data mapping relation of the conversion from the preset image to the output image based on the CIELab data mapping relation.
Further, the computer program realizes the other methods provided by the first and third embodiments of the present disclosure when executed by the processor
The embodiment of the disclosure can promote the printing digitization work flow, automation and intellectualization. The embodiment of the disclosure has low threshold for the requirement of user operation, simple operation process and intelligent implementation: 1) one-click is finished, the system automatically provides recommended results, and the user selects a favorite result; 2) guiding operation is performed, and the system prompts and guides an operator to gradually finish the effect preview of expected printing, so that personalized adjustment is embodied; 3) the process integration level is high, the RGB image is input, and a result graph meeting the requirements of the pre-printing condition is output.
A sixth embodiment of the present disclosure provides an electronic device, a schematic structural diagram of which may be as shown in fig. 3, and the electronic device at least includes a memory 901 and a processor 902, where the memory 901 stores a computer program, and the processor 902 implements the method provided by any embodiment of the present disclosure when executing the computer program on the memory 901. Illustratively, the electronic device computer program steps are as follows S21-S23:
s21, acquiring an image histogram based on RGB data of a predetermined image;
s22, determining a CIELab data mapping relation based on the image histogram and the output parameter value;
and S23, acquiring the RGB data mapping relation of the conversion from the preset image to the output image based on the CIELab data mapping relation.
Further, the processor 902 also executes the computer programs in the first and second embodiments described above
The embodiment of the disclosure can promote the printing digitization work flow, automation and intellectualization. The embodiment of the disclosure has low threshold for the requirement of user operation, simple operation process and intelligent implementation: 1) one-click is finished, the system automatically provides recommended results, and the user selects a favorite result; 2) guiding operation is performed, and the system prompts and guides an operator to gradually finish the effect preview of expected printing, so that personalized adjustment is embodied; 3) the process integration level is high, the RGB image is input, and a result graph meeting the requirements of the pre-printing condition is output.
The storage medium may be included in the electronic device; or may exist separately and not be incorporated into the electronic device.
The storage medium carries one or more programs that, when executed by the electronic device, cause the electronic device to: acquiring at least two internet protocol addresses; sending a node evaluation request comprising at least two internet protocol addresses to node evaluation equipment, wherein the node evaluation equipment selects the internet protocol addresses from the at least two internet protocol addresses and returns the internet protocol addresses; receiving an internet protocol address returned by the node evaluation equipment; wherein the obtained internet protocol address indicates an edge node in the content distribution network.
Alternatively, the storage medium carries one or more programs that, when executed by the electronic device, cause the electronic device to: receiving a node evaluation request comprising at least two internet protocol addresses; selecting an internet protocol address from at least two internet protocol addresses; returning the selected internet protocol address; wherein the received internet protocol address indicates an edge node in the content distribution network.
Computer program code for carrying out operations for the present disclosure may be written in any combination of one or more programming languages, including but not limited to an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the passenger computer, partly on the passenger computer, as a stand-alone software package, partly on the passenger computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the passenger computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
It should be noted that the storage media described above in this disclosure can be either computer-readable signal media or computer-readable storage media or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In contrast, in the present disclosure, a computer readable signal medium may include a data signal propagating in a baseband or as part of a carrier wave, in which computer readable program code is carried. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any storage medium that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a storage medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in the embodiments of the present disclosure may be implemented by software or hardware. Where the name of an element does not in some cases constitute a limitation on the element itself.
The functions described herein above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), systems on a chip (SOCs), Complex Programmable Logic Devices (CPLDs), and the like.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be understood by those skilled in the art that the scope of the disclosure herein is not limited to the particular combination of features described above, but also encompasses other embodiments in which any combination of the features described above or their equivalents does not depart from the spirit of the disclosure. For example, the above features may be replaced with (but not limited to) technical features disclosed in the present disclosure having similar functions.
Further, while operations are depicted in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order. Under certain circumstances, multitasking and parallel processing may be advantageous. Likewise, while several specific implementation details are included in the above discussion, these should not be construed as limitations on the scope of the disclosure. Certain features that are described in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable subcombination.
Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.
While the present disclosure has been described in detail with reference to the embodiments, the present disclosure is not limited to the specific embodiments, and those skilled in the art can make various modifications and alterations based on the concept of the present disclosure, and the modifications and alterations should fall within the scope of the present disclosure as claimed.
Claims (10)
1. A mapping method of RGB image data is characterized by comprising the following steps:
acquiring an image histogram based on RGB data of a predetermined image;
determining a CIELab data mapping relation based on the image histogram and the output parameter value;
and acquiring the RGB data mapping relation of converting the preset image into an output image based on the CIELab data mapping relation.
2. The mapping method according to claim 1, wherein the obtaining of the image histogram based on the RGB data of the predetermined image comprises the steps of:
acquiring a preset image;
acquiring CIELab data based on the RGB data of the predetermined image;
and drawing an image histogram based on the CIELab data.
3. The mapping method according to claim 2, wherein the obtaining of CIELab data based on RGB data of the predetermined image is performed by a color profile embedded in the predetermined image.
4. The mapping method according to claim 1, wherein the determining a CIELab data mapping relation based on the image histogram and the output parameter value comprises the following steps:
acquiring a first tone range of the predetermined image based on the image histogram;
acquiring a second order range of the output image based on the output parameter value;
and determining a CIELab data mapping relation based on the first tonal range and the second tonal range.
5. The mapping method according to claim 1, wherein the obtaining of the first pitch range of the predetermined image based on the image histogram is performed by:
extracting the CIELab values of the brightest and darkest pixel points from the image histogram;
traversing the data of the preset image, and marking the areas of the brightest and darkest pixel points in the image histogram;
respectively determining an image white field or an image black field based on the areas where the brightest and darkest pixel points are located, thereby calculating the average brightness value of each area;
determining a first tonal range for the predetermined image based on the average luminance value.
6. The mapping method according to claim 1, further comprising:
and adjusting the RGB data mapping relation based on the color difference between the output image and the predetermined image.
7. The mapping method according to claim 6, wherein the adjusting the RGB data mapping relation based on the color difference between the output image and the predetermined image comprises:
acquiring an output image based on the mapping relation between the predetermined image and the RGB data;
determining sample CIELAB values for tone sample points in a predetermined color patch based on the output parameter values;
determining a comparison sample point in the output image based on the sample CIELab value;
obtaining a color difference based on the sample CIELab values and the comparison CIELab values of the comparison sample points;
and adjusting the RGB data mapping relation based on the color difference.
8. An apparatus for mapping RGB image data, comprising:
the device comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring an image histogram based on RGB data of a preset image;
a determining module, configured to determine a CIELab data mapping relationship based on the image histogram and an output parameter value;
and the second acquisition module is used for acquiring the RGB data mapping relation of the conversion from the preset image to the output image based on the CIELab data mapping relation.
9. A storage medium storing a computer program, characterized in that the computer program realizes the steps of the method of any one of claims 1 to 7 when executed by a processor.
10. An electronic device comprising at least a memory, a processor, the memory having a computer program stored thereon, wherein the processor, when executing the computer program on the memory, is adapted to carry out the steps of the method of any of claims 1 to 7.
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