CN114046880A - Color difference correction method for LED spliced display screen - Google Patents
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Abstract
The invention discloses a color difference correction method for an LED spliced display screen, and particularly relates to the technical field of display screen splicing. According to the scheme, the color difference of the spliced screen is detected and calculated by adopting a CIELAB color difference formula, data acquisition is simultaneously carried out on a plurality of spliced positions of the spliced screen, and the data acquisition is simultaneously shielded by adopting a light shield, so that the accuracy and consistency of the data acquisition process are ensured to a certain extent, the condition that the data acquisition environment is obviously different among data due to the acquisition environment is avoided, the efficiency and the effect of the integral color difference inspection process are obviously improved, the manpower and time cost required by the scheme are ideal, and the scheme has good economic applicability.
Description
Technical Field
The invention relates to the technical field of display screen assembly, in particular to a color difference correction method for an LED spliced display screen.
Background
When white light is used for imaging, not only five monochromatic aberrations are generated for each monochromatic light, but also different propagation paths are provided for different colored lights due to dispersion caused by different refractive indexes of the different colored lights, so that aberration caused by the difference of the light paths of the different colored lights is presented, which is called chromatic aberration (chromatic aberration for short). Chromatic aberration is classified into two types, namely, positional chromatic aberration and chromatic aberration of magnification, due to different properties.
An led (light emitting diode) display screen is a modern information publishing platform formed by LD dot matrix modules or pixel units, and has the characteristics of high luminous efficiency, long service life, flexible configuration, rich colors, strong indoor and outdoor environment adaptability and the like. In particular, full-color LFD displays have been developed rapidly, and have been widely used in the fields of finance, traffic, sports, advertising, etc.
Unlike other flat display products, which are essentially a one-piece flat panel, the LED display screen is modular in composition, i.e., is formed by combining a large number of individual LEDs. Since the numerous LEDs are more or less different, when they are assembled into a whole display screen, the inconsistency of brightness and chromaticity can cause mosaic, screen blooming, etc.
Modern colorimetry employs a set of color measurement principles, data and calculations specified by the CIE (international commission on illumination), known as the CIE standard colorimetry system. Wherein the standard wavelengths of the three primary colors of RB are respectively specified as R (700nm), G (546.1nm) and B (435.8 nm). It is well known that wavelength determines color (i.e., hue). On a standard CE chromaticity diagram, the colors are distributed in areas according to hue and saturation, i.e. if a point representing different chromaticity wavelengths is connected to a central white light point, the chromaticity diagram can be divided into a plurality of different color areas.
The splicing screen is classified according to the backlight sources as follows: the LED liquid crystal splicing screen, the OLED self-luminous liquid crystal splicing screen and the DLP rear projection type splicing. Wherein the different backlight sources give the tiled screen different product types, such as: the spliced screen of the OLED backlight source can be bent in a certain curvature direction, and the DLP projection type splicing is thick due to the fact that backlight is from a projector. Progress and development in each field appear in each type of spliced screen product along with the updating and upgrading of technology, wherein the products of transparent splicing of the LED spliced screen and the OLED spliced screen are slowly accepted by the market.
The spliced screen is a complete display unit, a combined large picture can be displayed after the spliced screen is freely combined and installed, and the spliced screen is installed like building blocks. The frame (the part of the physical frame which can not display the content) after the spliced screen display unit and the spliced screen display unit are combined is only 0.88mm wide, and the main flow size of the spliced screen is as follows: 46 inches/49 inches/55 inches/65 inches/75 inches, etc. However, with the progress of the technology, products are diversified, the whole customized spliced screen is in point-to-point display, and the spliced screen without chromatic aberration, a seamless spliced screen, a curved surface spliced screen, transparent splicing and the like are adopted. The DID originally refers to the abbreviation of panel technology, and the English abbreviation of the split screen technology can be represented in 2021 by the following abbreviations: LED, OLED, LCD, BSR, DID and the like all refer to liquid crystal in the splicing screen category. DLP stands for rear projection tiled screens.
The LED display screen has bright color and strong stereoscopic impression, is widely applied to industries such as sports, advertisements, education and the like, and along with the development of science and technology and industry, people also put forward higher requirements on the quality of the display picture of the LED display screen. The brightness uniformity is an important index for measuring the color quality of the display screen, but the LED display screen is easy to cause the unevenness of the chromaticity and the brightness of the displayed image due to the objective reasons of limited manufacturing process level, inconsistent aging degree of devices and the like. In addition, human eyes as a receiving terminal of the picture is a very fine and complex nonlinear system, and the perception capability of different colors is different, so that the nonuniformity of the brightness and the chroma of the perceived picture is aggravated on the basis of objective factors. Therefore, the evaluation characteristics of the image by the human eyes are particularly important.
The spliced display unit can be used as a display independently and can be spliced into an ultra-large screen for use. According to different use requirements, the functions of changing the size of the picture can be realized through the graphics processor: the method comprises the following steps of single-screen multi-picture display, single-screen single-picture display, arbitrary splicing screen combined display, image splicing and full-screen splicing, optional compensation or covering of an image frame, roaming, zooming and stretching of digital signals, cross-screen display, setting and running of various display plans and real-time processing of full-high-definition signals.
The installation is as simple as building blocks, and the use and installation of single or spliced blocks are very simple. SLCD is a super narrow-edge liquid crystal splicing screen, the periphery of the SLCD is only 3mm wide, and the SLCD is also provided with a toughened glass protective layer, a built-in intelligent temperature control alarm circuit and a special 'fast-dispersion' heat dissipation system on the surface. The splicing special interface is very abundant: analog AV, component, S terminal, VGA interface, digital DVI, HDMI and the like are available, not only are the digital signal input suitable, but also the support for analog signals is unique. The SLCD series products adopt unique and world forefront digital processing technology, so that users really experience the effect of full-high-definition large screens.
In most digital image systems, an input image is processed and converted into a one-dimensional electric signal by adopting a mode of firstly freezing and then scanning, and then the one-dimensional electric signal is processed, stored, transmitted and the like. Finally, multi-dimensional image signals are often formed, and image noise is subjected to decomposition and synthesis. In these processes the electrical system and external influences will complicate the accurate analysis of image noise. On the other hand, the image is only a medium for transmitting visual information, and the understanding and understanding of the image information are determined by the human visual system. Different image noise has different human perception degrees, which is the subject of the so-called human noise visual characteristics.
Image noise refers to unnecessary or unnecessary interference information present in the image data. The presence of noise seriously affects the quality of the remotely sensed image and must therefore be corrected before image enhancement and classification processes. Various factors in an image that hinder one's acceptance of its information may be referred to as image noise. Noise can be theoretically defined as "random error that is unpredictable and can only be recognized by probabilistic statistical methods". It is therefore appropriate to consider the image noise as a multi-dimensional random process, and the method of describing the noise can therefore fully borrow the description of the random process, i.e. its probability distribution function and probability density distribution function.
The colorimeter is an instrument for measuring colors and color differences reflected by an object (paper, etc.), measuring ISO brightness (blue whiteness R457) and the degree of fluorescent whitening of a fluorescent whitened material, measuring CIE whiteness (ganz whiteness W10 and color cast value TW10), measuring ceramic whiteness, measuring whiteness of a building material and a non-metallic mineral product, measuring hunter system Lab and hunter (Lab) whiteness, measuring yellowness, measuring opacity, transparency, light scattering coefficient and light absorption coefficient of a test sample, measuring an ink absorption value. The method is widely applied to industries such as papermaking, printing, ceramics, chemical industry, textile printing and dyeing, building materials, grain, salt manufacturing and the like.
Lack of synchronization between the luminance and chrominance of the tiled screen can cause the screen to differ in luminance and chrominance and typically cause the screens to be out of sync and cause the luminance of the tiled screen to be out of sync. When the brightness is not synchronized, one side will become dark and the other side will become bright. Or partial color deviations, which is a common mosaic phenomenon. Since the LED is a self-luminous body, the luminous intensity in this range is proportional to the current supplied thereto, and the brightness between the tiled screens, the debugging process, and the discrimination of program errors can be reduced by reasonably controlling the current in the circuit design, production, installation, and installation processes. At this point, the image on the screen shows several ribbon loops (self-test) or a black screen or ghost. The program size of the mosaic frame does not match the screen clicked. At this time, you can change the program or select the corresponding screen. The application is as follows. Improper insertion or poor contact of the screen cable or incomplete signal cable: shaking the screen cable at this time causes the screen to shake and takes a corresponding countermeasure according to the response of the screen. The signal lines are poor, the resistance of the signal lines is large or the error is large, the error of the signal ends of the signal distributor or the matrix machine is large, and the distribution can be caused by the connection line error of the upper signal I/O port and the lower signal I/O port due to the 1/O principle of the signal equipment. A difference in brightness occurs between the upper and lower ports of the display.
The splicing screen color difference detection process part adopts manual operation to respectively detect a plurality of splicing parts of the splicing screen, and respectively adjusts the splicing parts according to detected values, so that the consistency of integral acquired data is difficult to achieve, and the acquired image data has obvious deviation due to different noise influences in the data acquisition and transmission process, so that the effect of color difference detection is not ideal enough, and therefore, the problem is solved by the LED splicing display screen color difference correction method.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention provides a color difference correction method for an LED spliced display screen, and the technical problems to be solved by the invention are as follows: the splicing screen color difference detection process part adopts manual operation to detect a plurality of splicing parts of the splicing screen respectively, and adjusts the splicing parts respectively according to the detected numerical values, so that the consistency of the whole collected data is difficult to achieve, and the collected image data has obvious deviation probably because the noise influence in the data collection and transmission process is different, thereby causing the problem that the effect of color difference detection is not ideal enough.
In order to achieve the purpose, the invention provides the following technical scheme: a color difference correction method for an LED spliced display screen comprises the following steps:
firstly, adjusting a screen to be white and outputting, acquiring L, a and b values of the spliced screen by using a color difference meter, dividing the screen into a plurality of regions, and sharpening the edges of the image of each divided region to identify the position of a splicing seam of the spliced screen;
carrying out noise reduction processing on the acquired image, wherein the noise reduction process adopts a median filtering algorithm to carry out processing;
and carrying out color difference detection analysis on the obtained image data by using a detection algorithm to obtain a color difference detection result.
As a further scheme of the invention: the image dividing process comprises the steps of firstly converting an image into a gray image, then simply accumulating gray values of the image to obtain gray values of the image in a row direction, finding out peak-valley positions of the image in a changing process after the gray values are accumulated, after the image is divided, carrying out threshold processing on divided sub-images by adopting a threshold dividing algorithm, transversely dividing the image into a plurality of rectangular areas with the same size, respectively carrying out global threshold dividing on the rectangular areas, carrying out accumulation calculation on each row of gray values of the threshold divided image, processing the row accumulated gray values by using a first-order difference to obtain boundaries at two ends of the corresponding area, dividing the target area, matching the corresponding target area with an actual splicing part of a splicing screen, and simultaneously numbering the target areas.
As a further scheme of the invention: when the color difference meter is used for collecting images, the color difference meter is placed at a corresponding position of the spliced screen, the outer parts of the spliced screen and the color difference meter are shielded by using a light shield, and then the spliced screen is controlled to be adjusted to be white and output, and the images are collected.
As a further scheme of the invention: the detection algorithm adopted by the image data comprises the following steps:
the total color difference formula based on the CIELAB color space is:
each univocal chromatic aberration formula:
lightness difference,. DELTA.L ═ L1-L0，
Difference in chroma, Δ a ═ a1-a0,Δb＝b1-b0，
The color intensity is poor, and the color intensity is poor,
the color difference is generated between the two colors,
wherein L is1，a1，b1For detecting coordinate values of data in CIELAB color space, L0，a0，b0The coordinate value of the standard color of the spliced screen in the CIELAB color space is obtained;
the CIELAB200 formula developed on the basis of the total color difference formula of the CIELAB color space is:
2) calculating Ci′hi′
2) Calculate Δ L ' Δ C ' Δ H '
3) Calculating a color difference weight function SL，SC，SHAnd a rotation function RT，RC
4) Calculating the color difference Δ E00
Wherein K in CIELAB200 color difference formulaL，KC，KHSelecting K from the formula as the weight coefficientL＝1.4，KC＝1，KH＝1。
As a further scheme of the invention: the median filtering algorithm comprises the following steps, the relevant variables being defined as follows: f (I, j) is a pixel point on the image coordinate, WNIs taken as a filter window, NmaxIs the maximum value of the adaptive window size, IminIs the smallest pixel value of the current window, ImaxIs the largest pixel value of the current window, ImedFor the pixel median of the current window, the median algorithm is calculated as follows:
step I, Z1＝Imed-Imin，Z2＝Imed-Imax
In the first noise detection of the image area, a 3-by-3 window template is adopted for traversal, and when Z is used1＞0，Z2In the following, the method jumps to the second step to execute judgment, otherwise, the window W is enlargedNThe size of (D) is continuously judged until N is more than NmaxThe pixel value of the center point of the window is set to be Ii,jAs an output value;
step two, Z3＝Ii,j-Imin，Z4＝Ii,j-Imax
If Z is3＞0，Z4Less than 0, judging that no noise point exists in the window, and converting the original gray value Ii,jAs the output value, otherwise, the median I of the pixel points in the window is usedmedAs the corresponding output value of the filtering.
The invention has the beneficial effects that:
1. according to the invention, the color difference of the spliced screen is detected and calculated by adopting the CIELAB color difference formula, the CIELAB color space is closer to the color perceived by human vision, the CIELAB color difference formula can quantitatively analyze the detected numerical value, meanwhile, the scheme is used for simultaneously carrying out data acquisition on a plurality of spliced positions of the spliced screen, and the data acquisition is shielded by adopting a light shield, so that the accuracy and consistency of the data acquisition process are ensured to a certain extent, and the condition that the data acquisition environment is obviously different among the data due to the occurrence of the acquisition environment is avoided, so that the efficiency and the effect of the integral color difference inspection process are obviously improved, and the scheme has ideal manpower and time cost and good economic applicability;
2. the invention adopts the image segmentation and median filtering algorithm, adopts the median filtering algorithm to process the noise of the image caused by the interference of the sensor performance in the acquisition process, adopts the gray value accumulation method to realize the segmentation processing of the image, eliminates the redundant information of the image, removes the noise in the acquired data, further realizes the accuracy of the acquired data and avoids the condition that the splicing parts of each spliced screen have obvious difference.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1:
a color difference correction method for an LED spliced display screen comprises the following steps:
firstly, adjusting a screen to be white and outputting, acquiring L, a and b values of the spliced screen by using a color difference meter, dividing the screen into a plurality of regions, and sharpening the edges of the image of each divided region to identify the position of a splicing seam of the spliced screen;
carrying out noise reduction processing on the acquired image, wherein the noise reduction process adopts a median filtering algorithm to carry out processing;
and carrying out color difference detection analysis on the obtained image data by using a detection algorithm to obtain a color difference detection result.
The image dividing process comprises the steps of firstly converting an image into a gray image, then simply accumulating gray values of the image to obtain gray values of the image in a row direction, finding out peak-valley positions of the image in a changing process after the gray values are accumulated, after the image is divided, carrying out threshold processing on divided sub-images by adopting a threshold dividing algorithm, transversely dividing the image into a plurality of rectangular areas with the same size, respectively carrying out global threshold dividing on the rectangular areas, carrying out accumulation calculation on each row of gray values of the threshold divided image, processing the row accumulated gray values by using a first-order difference to obtain boundaries at two ends of the corresponding area, dividing the target area, matching the corresponding target area with an actual splicing part of a splicing screen, and simultaneously numbering the target areas.
When the color difference meter is used for collecting images, the color difference meter is placed at a corresponding position of the spliced screen, the outer parts of the spliced screen and the color difference meter are shielded by using a light shield, and then the spliced screen is controlled to be adjusted to be white and output, and the images are collected.
The detection algorithm adopted by the image data comprises the following steps:
the total color difference formula based on the CIELAB color space is:
each univocal chromatic aberration formula:
lightness difference,. DELTA.L ═ L1-L0，
Difference in chroma, Δ a ═ a1-a0,Δb＝b1-b0，
The color intensity is poor, and the color intensity is poor,
the color difference is generated between the two colors,
wherein L is1，a1，b1For detecting coordinate values of data in CIELAB color space, L0，a0，b0The coordinate value of the standard color of the spliced screen in the CIELAB color space is obtained;
the CIELAB200 formula developed on the basis of the total color difference formula of the CIELAB color space is:
3) calculating Ci′hi′
2) Calculate Δ L ' Δ C ' Δ H '
3) Calculating a color difference weight function SL，SC，SHAnd a rotation function RT，RC
4) Calculating the color difference Δ E00
Wherein K in CIELAB200 color difference formulaL，KC，KHSelecting K from the formula as the weight coefficientL＝1.4，KC＝1，KH＝1。
The median filtering algorithm comprises the following steps, the relevant variables being defined as follows: f (I, j) is a pixel point on the image coordinate, WNIs taken as a filter window, NmaxIs the maximum value of the adaptive window size, IminFor the current windowMinimum pixel value, ImaxIs the largest pixel value of the current window, ImedFor the pixel median of the current window, the median algorithm is calculated as follows:
step I, Z1＝Imed-Imin，Z2＝Imed-Imax
In the first noise detection of the image area, a 3-by-3 window template is adopted for traversal, and when Z is used1＞0，Z2In the following, the method jumps to the second step to execute judgment, otherwise, the window W is enlargedNThe size of (D) is continuously judged until N is more than NmaxThe pixel value of the center point of the window is set to be Ii,jAs an output value;
step two, Z3＝Ii,j-Imin，Z4＝Ii,j-Imax
If Z is3＞0，Z4Less than 0, judging that no noise point exists in the window, and converting the original gray value Ii,jAs the output value, otherwise, the median I of the pixel points in the window is usedmedAs the corresponding output value of the filtering.
In conclusion, the present invention:
according to the invention, the CIELAB chromatic aberration formula is adopted to detect and calculate the chromatic aberration of the spliced screen, the CIELAB color space is closer to the color perceived by human vision, the CIELAB chromatic aberration formula can quantitatively analyze the detected numerical value, meanwhile, the scheme is used for simultaneously carrying out data acquisition on a plurality of spliced positions of the spliced screen, and the data acquisition is shielded by a light shield, so that the accuracy and consistency of the data acquisition process are ensured to a certain extent, the condition that the data acquisition environment is obviously different among the data due to the occurrence of the acquisition environment is avoided, the efficiency and the effect of the integral chromatic aberration inspection process are obviously improved, and the scheme has ideal manpower and time cost and good economic applicability.
The invention adopts the image segmentation and median filtering algorithm, adopts the median filtering algorithm to process the noise of the image caused by the interference of the sensor performance in the acquisition process, adopts the gray value accumulation method to realize the segmentation processing of the image, eliminates the redundant information of the image, removes the noise in the acquired data, further realizes the accuracy of the acquired data and avoids the condition that the splicing parts of each spliced screen have obvious difference.
The points to be finally explained are: although the present invention has been described in detail with reference to the general description and the specific embodiments, on the basis of the present invention, the above embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (5)
1. A color difference correction method for an LED spliced display screen is characterized by comprising the following steps:
firstly, adjusting a screen to be white and outputting, acquiring L, a and b values of the spliced screen by using a color difference meter, dividing the screen into a plurality of regions, and sharpening the edges of the image of each divided region to identify the position of a splicing seam of the spliced screen;
carrying out noise reduction processing on the acquired image, wherein the noise reduction process adopts a median filtering algorithm to carry out processing;
and carrying out color difference detection analysis on the obtained image data by using a detection algorithm to obtain a color difference detection result.
2. The method for correcting the chromatic aberration of the LED tiled display screen according to claim 1, wherein: the image dividing process comprises the steps of firstly converting an image into a gray image, then simply accumulating gray values of the image to obtain gray values of the image in a row direction, finding out peak-valley positions of the image in a changing process after the gray values are accumulated, after the image is divided, carrying out threshold processing on divided sub-images by adopting a threshold dividing algorithm, transversely dividing the image into a plurality of rectangular areas with the same size, respectively carrying out global threshold dividing on the rectangular areas, carrying out accumulation calculation on each row of gray values of the threshold divided image, processing the row accumulated gray values by using a first-order difference to obtain boundaries at two ends of the corresponding area, dividing the target area, matching the corresponding target area with an actual splicing part of a splicing screen, and simultaneously numbering the target areas.
3. The method for correcting the chromatic aberration of the LED tiled display screen according to claim 1, wherein: when the color difference meter is used for collecting images, the color difference meter is placed at a corresponding position of the spliced screen, the outer parts of the spliced screen and the color difference meter are shielded by using a light shield, and then the spliced screen is controlled to be adjusted to be white and output, and the images are collected.
4. The method for correcting the chromatic aberration of the LED tiled display screen according to claim 1, wherein: the detection algorithm adopted by the image data comprises the following steps:
the total color difference formula based on the CIELAB color space is:
each univocal chromatic aberration formula:
lightness difference,. DELTA.L ═ L1-L0，
Difference in chroma, Δ a ═ a1-a0,Δb＝b1-b0，
The color intensity is poor, and the color intensity is poor,
the color difference is generated between the two colors,
wherein L is1，a1，b1Color at CIELAB for data detectionCoordinate value in space, L0，a0，b0The coordinate value of the standard color of the spliced screen in the CIELAB color space is obtained;
the CIELAB200 formula developed on the basis of the total color difference formula of the CIELAB color space:
1) calculating Ci′hi′
2) Calculate Δ L ' Δ C ' Δ H '
3) Calculating a color difference weight function SL，SC，SHAnd a rotation function RT，RC
4) Calculating the color difference Δ E00
Wherein K in CIELAB200 color difference formulaL，KC，KHSelecting K from the formula as the weight coefficientL＝1.4，KC＝1，KH＝1。
5. The method for correcting the chromatic aberration of the LED tiled display screen according to claim 1, wherein: the median filtering algorithm comprises the following steps, the relevant variables being defined as follows: f (I, j) is a pixel point on the image coordinate, WNIs taken as a filter window, NmaxIs the maximum value of the adaptive window size, IminIs the smallest pixel value of the current window, ImaxIs the largest pixel value of the current window, ImedFor the pixel median of the current window, the median algorithm is calculated as follows:
step I, Z1＝Imed-Imin，Z2＝Imed-Imax
In the first noise detection of the image area, a 3-by-3 window template is adopted for traversal, and when Z is used1＞0，Z2In the following, the method jumps to the second step to execute judgment, otherwise, the window W is enlargedNThe size of (D) is continuously judged until N is more than NmaxThe pixel value of the center point of the window is set to be Ii,jAs an output value;
step two, Z3＝Ii,j-Imin，Z4＝Ii,j-Imax
If Z is3＞0，Z4Less than 0, judging that no noise point exists in the window, and converting the original gray value Ii,jAs the output value, otherwise, the median I of the pixel points in the window is usedmedAs the corresponding output value of the filtering.
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