Digitized ancient painting presentation method driven by Micro-LED micro-display chip

Abstract

The invention discloses an ancient painting digital presentation method driven by a Micro-LED micro-display chip, and relates to the technical field of digital image processing and display. Extracting a brightness uniformity coefficient, a size coefficient and a contrast ratio disqualification coefficient which are qualified about image adaptation processing in the target image; according to the brightness uniformity coefficient, the size coefficient and the contrast ratio disqualification coefficient, obtaining a processing qualification coefficient, and according to the processing qualification coefficient and a preset processing qualification coefficient threshold, determining whether the target image is qualified in the image adaptation processing process; when the target image is qualified in the image adaptation processing process, the target image is digitally presented on the AR device through the Micro-LED micro-display chip driving the ancient painting; in this way, the reasonability of image adaptation processing can be judged, whether the digital image of the ancient painting can be presented through the AR equipment or not is judged, and it is ensured that the presentation effect is optimal.

Description

Technical Field

[0001] The present invention relates to the field of digital image processing and display technology, and in particular to a method for digitally presenting ancient paintings driven by a Micro-LED microdisplay chip. Background Art

[0002] In terms of the digital display of ancient paintings and the application of augmented reality (AR) technology, the closest existing technologies currently rely mainly on traditional LCD or LED display technology. Although these technologies perform well in general applications, they have some obvious limitations in the display of specific artworks, especially the digital presentation of ancient paintings.

[0003] First, traditional display technologies often fail to meet the high standards required for artworks in terms of color reproduction. For example, LCD technology has inherent color deviation and limited color gamut coverage when displaying colors in the real world, which may result in loss of original details and distortion of colors for ancient paintings that require precise color matching. In addition, the performance of these technologies in terms of brightness and contrast is often affected by ambient light, especially in outdoor or bright light environments, where the display effect is greatly reduced. Second, the application of traditional display solutions in AR glasses is limited by size and weight. Conventional LCD and LED display components are large in size and heavy in weight, which not only limits the flexibility of AR glasses design, but also affects the comfort of users wearing them for a long time. In addition, the pixel density of these technologies often cannot meet the needs of high-resolution image display, which is particularly important in devices such as AR glasses that need to display high-definition images to enhance the user experience. Low pixel density limits the display of image details and affects users' appreciation of ancient paintings;

[0004] In order to solve this problem, Micro-LED technology is now introduced to overcome these limitations, achieve a more realistic and detailed digital presentation of ancient paintings, and optimize the wearing experience of AR glasses, so as to better meet the needs of professional display and personal learning, because Micro-LED technology, with its self-luminous characteristics and higher color accuracy, can provide a wider color gamut and more accurate color reproduction, solving the color deviation problem of traditional LCD and LED technology in the digital display of ancient paintings; its independent pixel design allows the brightness and contrast to be adjusted more flexibly, and even in strong light environments, it can maintain a clear display effect. In addition, the ultra-high pixel density of Micro-LED makes the image details richer, and can accurately present the subtle textures and tonal changes in ancient paintings, greatly improving the visual effects of AR glasses; at the same time, Micro-LED displays are usually thinner and lighter, which helps to reduce the weight of AR glasses and improve wearing comfort. Therefore, this technology not only has significant advantages in improving the quality of digital presentation of artworks, but also optimizes the design and user experience of AR devices, especially when used for a long time.

[0005] In order to achieve the best effect of the digitized image of ancient paintings presented on the Micro-LED display screen of the AR device, image adaptation processing is usually required, such as image size adjustment, brightness and contrast adjustment, so that it can be displayed on the Micro-LED display screen with the best effect; however, the existing technology often directly assumes that the image adaptation processing is reasonable and directly presents the digitized image of ancient paintings through the AR device, resulting in a suboptimal presentation effect. Summary of the invention

[0006] The purpose of the present invention is to solve the above-mentioned problems and provide a method for digitally presenting ancient paintings driven by Micro-LED microdisplay chips.

[0007] The present invention proposes a method for digitally presenting ancient paintings driven by a Micro-LED microdisplay chip, the method comprising:

[0008] The image after image adaptation processing of the digitized image of the ancient painting is used as the target image, and the brightness uniformity coefficient, size coefficient and contrast unqualified coefficient of the target image with respect to the image adaptation processing are extracted;

[0009] Obtaining a processing qualified coefficient according to the brightness uniformity coefficient, the size coefficient and the contrast unqualified coefficient, and judging whether the target image is qualified in the image adaptation processing according to the processing qualified coefficient and a preset processing qualified coefficient threshold;

[0010] When the target image passes the image adaptation process, the target image will be digitally presented on the AR device through the Micro-LED micro-display chip driving the ancient painting.

[0011] Optionally, the brightness uniformity coefficient includes:

[0012] Convert the target image to a grayscale image and calculate the mean μY and standard deviation σY of the grayscale values ​​in the grayscale image. The calculation formula is:

[0013]

[0014] Where Q is the number of rows in the image, E is the number of columns in the image, and Y(n,m) is the grayscale value of the pixel at position (n,m) in the grayscale image.

[0015] Calculate the brightness uniformity coefficient, the calculation formula is:

[0016]

[0017] Where UK is the brightness uniformity index, and ∈ is a preset constant used to avoid division by zero when calculating the standard deviation.

[0018] Optionally, the size factor includes:

[0019] Obtain the width and length of the target image, marked as HJ and HG respectively, and divide the width HJ of the target image by the length HG of the target image to obtain the processed proportional coefficient;

[0020] The width and length of the digitized image of the ancient painting before image adaptation are marked as FG and RE respectively, and the width FG is divided by the length RE to obtain the scale coefficient before processing;

[0021] The absolute difference between the scale factor after processing and the scale factor before processing is calculated, and the absolute difference is used as the size coefficient of the target image.

[0022] Optionally, the contrast failure coefficient includes:

[0023] Grayscale the target image, convert the color image into a grayscale image, count the number of pixels at each grayscale level in the image, and obtain a grayscale histogram;

[0024] The grayscale histogram shows the distribution of pixels at each grayscale level in the image;

[0025] Normalize the grayscale histogram so that the sum of the histogram is 1, that is, the number of pixels at each grayscale level divided by the total number of pixels in the image;

[0026] The normalized histogram reflects the relative distribution of each gray level in the image.

[0027] The contrast of the image is calculated using the normalized grayscale histogram.

[0028] The formula for calculating contrast is:

[0029]

[0030] Where Qa is the contrast, p a is the normalized number of pixels at the ath gray level, is the mean of the normalized histogram, is the center value of the normalized histogram, and L is the number of gray levels;

[0031] The obtained contrast value is normalized to obtain the contrast failure coefficient of the image. The calculation formula of the contrast failure coefficient is:

[0032]

[0033] Where GL is the contrast failure factor and JK is the maximum possible contrast.

[0034] Optionally, obtaining a processing qualified coefficient according to a brightness uniformity coefficient, a size coefficient and a contrast unqualified coefficient includes:

[0035]

[0036] Wherein, ERT is the processing qualification coefficient, UK, HY, and GL are the brightness uniformity coefficient, size coefficient, and contrast unqualified coefficient, respectively, a1, a2, and a3 are the preset proportional coefficients of the brightness uniformity coefficient, size coefficient, and contrast unqualified coefficient, respectively, and a1, a2, and a3 are all greater than 0.

[0037] Optionally, judging whether the target image is qualified in the image adaptation process according to the processing qualification coefficient and a preset processing qualification coefficient threshold includes:

[0038] The processing qualification coefficient is compared with the preset processing qualification coefficient threshold. If the processing qualification coefficient is not less than the preset processing qualification coefficient threshold, it means that the target image has passed the image adaptation process, and the target image is digitally presented on the AR device through the Micro-LED micro-display chip to drive the ancient painting.

[0039] Optionally, judging whether the target image is qualified in the image adaptation process according to the processing qualification coefficient and a preset processing qualification coefficient threshold value further includes:

[0040] If the processing qualification coefficient is less than the preset processing qualification coefficient threshold, it means that the target image is unqualified in the image adaptation process, and the digitized image of the ancient painting is re-adapted until the processing qualification coefficient of the image after the image adaptation process is not less than the preset processing qualification coefficient threshold. The image after the image adaptation process is digitally presented on the AR device through the Micro-LED microdisplay chip to drive the ancient painting.

[0041] Beneficial effects of the present invention:

[0042] The present invention proposes a method for digitally presenting ancient paintings driven by a Micro-LED micro-display chip, in which the image after image adaptation processing of the digitized image of the ancient painting is taken as the target image, and the brightness uniformity coefficient, size coefficient and contrast unqualified coefficient of the target image that are qualified for the image adaptation processing are extracted; a processing qualified coefficient is obtained according to the brightness uniformity coefficient, size coefficient and contrast unqualified coefficient, and whether the target image is qualified in the image adaptation processing process is judged according to the processing qualified coefficient and a preset processing qualified coefficient threshold; when the target image is qualified in the image adaptation processing process, the target image is digitally presented on an AR device by driving the ancient painting with the Micro-LED micro-display chip; in this way, the rationality of the image adaptation processing can be judged, and it can be judged whether the image can be presented as a digital image of the ancient painting through the AR device, so as to ensure the best presentation effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The present invention will be further described below in conjunction with the accompanying drawings.

[0044] Figure 1 This is a flow chart of the method for digitally presenting ancient paintings driven by Micro-LED microdisplay chips. DETAILED DESCRIPTION

[0045] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0046] Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in the field without making any creative work shall fall within the scope of protection of the present invention.

[0047] The embodiment of the present invention provides a method for digitally presenting ancient paintings driven by a Micro-LED microdisplay chip. Figure 1 , Figure 1A flowchart of a method for digitally presenting ancient paintings driven by a Micro-LED microdisplay chip provided in an embodiment of the present invention. The method comprises the following steps:

[0048] The image after image adaptation processing of the digitized image of the ancient painting is used as the target image, and the brightness uniformity coefficient, size coefficient and contrast unqualified coefficient of the target image with respect to the image adaptation processing are extracted;

[0049] Obtaining a processing qualified coefficient according to the brightness uniformity coefficient, the size coefficient and the contrast unqualified coefficient, and judging whether the target image is qualified in the image adaptation processing according to the processing qualified coefficient and a preset processing qualified coefficient threshold;

[0050] When the target image passes the image adaptation process, the target image will be digitally presented on the AR device through the Micro-LED micro-display chip driving the ancient painting.

[0051] Based on the method for digital presentation of ancient paintings driven by the Micro-LED microdisplay chip provided in the embodiment of the present invention, the rationality of the image adaptation processing can be judged through the above method, and it can be judged whether the image can be presented as a digital image of the ancient painting through the AR device, thereby ensuring the optimal presentation effect.

[0052] It should be noted that there are several obvious deficiencies and limitations in the use of existing technologies for the digital presentation of ancient paintings and their display on AR glasses. First, traditional digital display technologies, such as LCD or traditional LED, are often unable to accurately reproduce the colors and details of ancient paintings. The limitations of these technologies in color depth and dynamic range have led to the loss of delicate colors and blurred details of ancient paintings during the digitization process, and it is impossible to truly reproduce the artistic value and visual effects of the original works. Secondly, when these traditional technologies are applied to AR glasses, they often face problems of volume and weight, which affects the portability of the device and the comfort of the user. More importantly, these display technologies have relatively high power consumption, which will greatly reduce the usage time of AR glasses that need to be worn for a long time. Finally, the limitations of existing technologies in pixel density also pose a challenge to high-quality image display. When used in AR glasses, this low pixel density makes it impossible to display image details in detail, thus affecting the overall quality of the digital presentation of ancient paintings and the user's viewing experience. In order to solve this problem, Micro-LED technology is now introduced to overcome these limitations, achieve a more realistic and detailed digital presentation of ancient paintings, and optimize the wearing experience of AR glasses, because the excellent performance of Micro-LED display chips in color reproduction, contrast and brightness can effectively solve the problem of color and detail loss in the digital presentation of ancient paintings by traditional technologies. In addition, the low power consumption and small size of Micro-LED also make it very suitable for AR glasses, which not only improves the display quality, but also improves the portability of the device and the comfort of the user. These improvements enable the digital presentation technology of ancient paintings based on Micro-LED to provide a more vivid, realistic and high-quality visual experience, whether in museum display or personal learning.

[0053] The use of Micro-LED technology brings the following benefits: High color accuracy and contrast Micro-LED provides a wider color gamut and higher contrast, so that every stroke of the ancient painting can be presented in a way closer to the original, thus greatly improving the visual effect of the artwork; High pixel density: High pixel density ensures that even on a smaller display screen, such as AR glasses, extremely fine image details can be displayed, optimizing the user's viewing experience; Miniaturization and lightweight: The miniaturization design of Micro-LED makes AR glasses lighter and improves the user's comfort for long-term wearing; Through these technical improvements, the digital display quality of ancient paintings is significantly optimized, and the user experience of AR glasses is improved; In addition, compared with the prior art, the present invention has functionally realized the transformation from simple image display to high-fidelity, highly interactive visual experience, so that the appreciation of ancient paintings is not limited to physical galleries, but can also be carried out at any time and any place through digital and augmented reality technology;

[0054] For example, to restore the painting "River and Sky Dusk Snow" by the Ming Dynasty painter Zhang Longzhang through Micro-LED technology, the original painting must first be scanned and digitized with high precision, and every detail of the painting must be accurately captured and converted into a digital image. In order to ensure that the colors, layers and details of the painting are perfectly restored, image adjustment technologies such as color calibration, resolution adjustment and brightness contrast optimization are used. Through Micro-LED display technology, these finely restored digital images are presented. With its high resolution, high brightness and precise color expression, the Micro-LED display can effectively present the delicate brushstrokes and rich colors of the work "River and Sky Dusk Snow". In order to further enhance the display effect, the painting is not only transformed from a static display to a dynamic display, but also the details can be enlarged or reduced on the display, allowing the audience to appreciate the Jiangtian snow scene painted by Zhang Longzhang more closely. In addition, through the combination of AR glasses, the painting can break through the limitations of the physical display space, and users do not need to view the exhibits at a fixed location or time. After wearing AR glasses, users can project paintings to any place in the real world through AR technology at any time. The painting presentation is seamlessly integrated with the real scene, as if traveling through time and space. AR glasses can dynamically adjust the presentation angle and view of the painting according to the user's perspective, movement and position, making it more in line with the real artistic perception, greatly enhancing interactivity and immersion.

[0055] The benefit of this combination of technologies is that it not only transforms traditional artworks from static displays into interactive and dynamic displays, allowing viewers to understand and appreciate artworks more deeply, but also Micro-LED and AR technologies solve the limitations of traditional display methods. Audiences can enjoy artworks anytime and anywhere without being restricted by space and time, gaining unprecedented convenience and immersive experience. In addition, through high-precision digital restoration, damage to the original work caused by long-term display can be avoided, providing an innovative way to protect cultural relics. Therefore, this display method combining Micro-LED and AR technology not only improves the accessibility and dissemination of artworks, but also provides a new perspective and form for the modern display of ancient artworks.

[0056] Among them, in order to achieve the best effect of the digitized image of ancient paintings presented on the Micro-LED display screen of the AR device, image adaptation processing is usually required, such as image size adjustment, brightness and contrast adjustment, etc., so that it can be displayed on the Micro-LED display screen with the best effect; however, the existing technology often directly assumes that the image adaptation processing is reasonable and directly presents the digitized image of ancient paintings through the AR device, resulting in a suboptimal presentation effect. Therefore, now the image of the digitized image of the ancient painting that has undergone image adaptation processing is analyzed to determine whether it is qualified and then the ancient painting is driven by the Micro-LED microdisplay chip on the AR device for digital presentation to achieve the best presentation effect.

[0057] In one embodiment, an image of a digitized image of an ancient painting that has been subjected to image adaptation processing is obtained as a target image, and a brightness uniformity coefficient, a size coefficient, and a contrast unqualified coefficient of the target image that have been subjected to image adaptation processing are extracted;

[0058] Among them, the brightness uniformity coefficient includes:

[0059] Convert the target image to a grayscale image and calculate the mean μY and standard deviation σY of the grayscale values ​​in the grayscale image. The calculation formula is:

[0060]

[0061] Where Q is the number of rows in the image, E is the number of columns in the image, and Y(n,m) is the grayscale value of the pixel at position (n,m) in the grayscale image.

[0062] Calculate the brightness uniformity coefficient, the calculation formula is:

[0063]

[0064] Where UK is the brightness uniformity index, and ∈ is a preset constant used to avoid division by zero when calculating the standard deviation.

[0065] It should be noted that ∈ is a preset constant, which is usually used to avoid division by zero and ensure the stability of the calculation process. For the calculation of the image brightness uniformity index, the general value range of ∈ can be set according to different requirements. Common value ranges include:

[0066] 10 -5 : This value is usually small enough to effectively avoid division by zero without significantly affecting the calculation results;

[0067] 10 -6 : When higher precision is required, a smaller value can be selected to ensure the accuracy of the calculation in extreme cases;

[0068] 10-8 : For some high-precision applications, especially when numerical stability is very high, this value can be used;

[0069] The specific values ​​are determined by professionals based on actual conditions and are not limited or elaborated on.

[0070] It should be noted that the larger the brightness uniformity coefficient, the more qualified the image of the ancient painting digitized image for image adaptation processing, because the larger the brightness uniformity coefficient, the more uniform the brightness distribution in the image, the smaller the overall brightness fluctuation of the image, and the clearer and easier to identify details. In the presentation of digitized images of ancient paintings, especially when showing delicate details of artworks, uniform brightness can better show the layering and color depth of the work. If the brightness is too concentrated or uneven, it may cause some details to disappear or some areas to be too bright or too dark, affecting the audience's overall appreciation of the artwork. Therefore, a higher brightness uniformity coefficient means that the image avoids excessive brightness distortion or unevenness during processing, ensuring that the digitized image can faithfully reflect the visual effects and artistic style of the original, thereby improving the overall quality of the digital display of ancient paintings and the reproducibility of artistic value; for example, the painting "River Sky Dusk Snow" by Ming Dynasty painter Zhang Longzhang, the snow scene and distant mountains in his work have extremely delicate layering, and the changes in brightness and contrast are very subtle. If the brightness of the digitally processed image is uneven, the white part of the snow may be overexposed or the dark details of the mountains may be lost, which will affect the audience's perception of the artistic conception of the painting. By improving the brightness uniformity coefficient, image processing can effectively retain these details, so that the purity of the snow scene and the depth of the distant mountains can be presented, enhancing the visual effect and ensuring that the digital image can better convey the delicate brushstrokes and exquisite painting style in the original work, so that when the audience appreciates this work, they can feel the unique charm of the Jiangtian snow scene presented by Zhang Longzhang through the contrast of light and dark.

[0071] In one embodiment, the size factors include:

[0072] Obtain the width and length of the target image, marked as HJ and HG respectively, and divide the width HJ of the target image by the length HG of the target image to obtain the processed proportional coefficient;

[0073] The width and length of the digitized image of the ancient painting before image adaptation are marked as FG and RE respectively, and the width FG is divided by the length RE to obtain the scale coefficient before processing;

[0074] The absolute difference between the scale factor after processing and the scale factor before processing is calculated, and the absolute difference is used as the size coefficient of the target image.

[0075] It should be noted that the smaller the size coefficient is, the more qualified the image of the digitized image of the ancient painting is after image adaptation, because the smaller the size coefficient is, the smaller the change in the aspect ratio of the image after the adaptation process is, which means that the image shape is closer to the original image. For the digitized image of ancient paintings, it is very important to maintain the aspect ratio of the original, because any excessive stretching or compression will cause visual distortion of the artwork and destroy the composition and details of the artwork. For example, the characters, scenery or structures in ancient paintings may rely on a specific proportional relationship to show their artistic effect. If the aspect ratio changes significantly during the digitization process, the audience's visual experience will be affected, and the original style and intention of the work may not be truly perceived. Therefore, a smaller size coefficient can not only ensure that the digitized image of the ancient painting is more visually restored to the original, but also improve the accuracy of the image display, so that the audience can better experience every detail and level in the artwork; for example, the painting "River and Sky Dusk Snow" by the Ming Dynasty painter Zhang Longzhang, in which the vast scene of snow and river and sky is expressed through fine composition and just the right proportion. If the aspect ratio changes significantly during the digitization process, it may distort the relationship between near and far in the painting, affecting the audience's overall perception of the painting. Especially in a painting such as "River and Sky Dusk Snow" that depicts the river, snow and distant mountains, the broad sense of space and profound artistic conception originally displayed through the proportional relationship will lose the charm and depth of the painting if the picture is deformed due to improper size adaptation. Therefore, ensuring that the smaller the size coefficient is, the closer the proportion of the image in the digital display is to the original, allowing the audience to more accurately perceive how Zhang Longzhang uses delicate proportion control and spatial layout to show the ethereal snow scene and the vastness of the river, and enhance the deep understanding and appreciation of the artistic value of the work.

[0076] In one embodiment, the contrast failure coefficient includes:

[0077] Grayscale the target image, convert the color image into a grayscale image, count the number of pixels at each grayscale level in the image, and obtain a grayscale histogram;

[0078] The grayscale histogram shows the distribution of pixels at each grayscale level in the image;

[0079] Normalize the grayscale histogram so that the sum of the histogram is 1, that is, the number of pixels at each grayscale level divided by the total number of pixels in the image;

[0080] The normalized histogram reflects the relative distribution of each gray level in the image.

[0081] The contrast of the image is calculated using the normalized grayscale histogram.

[0082] The formula for calculating contrast is:

[0083]

[0084] Where Qa is the contrast, p a is the normalized number of pixels at the ath gray level, is the mean of the normalized histogram, is the center value of the normalized histogram, and L is the number of gray levels;

[0085] The obtained contrast value is normalized to obtain the contrast failure coefficient of the image. The calculation formula of the contrast failure coefficient is:

[0086]

[0087] Where GL is the contrast failure factor and JK is the maximum possible contrast.

[0088] It should be noted that the maximum possible contrast depends on the number of gray levels in the image. This is because the contrast of an image is determined by the difference between different gray levels in the image. When the number of gray levels is limited, the maximum possible contrast of the image is limited, because it is impossible to produce infinitely high contrast within the limited gray level range. For example, in an 8-bit grayscale image, the gray level range is 0 to 255, which means that the darkest pixel is black (0) and the brightest pixel is white (255). Therefore, within this range, the maximum possible contrast is 255. When the number of gray levels in the image increases, the range of grayscale changes that can be represented will also increase, so the maximum possible contrast will also increase. For example, for a 16-bit grayscale image, its gray level range is 0 to 65535, so the maximum possible contrast is even higher.

[0089] It should be noted that the smaller the contrast failure coefficient is, the more qualified the image of the digitized image of the ancient painting is for image adaptation processing, because the smaller the contrast failure coefficient is, the higher the contrast of the image is retained during the adaptation process, making the difference between the brightness and dark parts of the image more distinct. Contrast is one of the key indicators of image quality, especially in the digitization of ancient paintings, which can highlight the details and layering of the works. For example, the delicate brushstrokes, light and dark changes, and light and shadow effects on the faces of characters in many ancient paintings rely on appropriate contrast to present. If the contrast of the image is too low, the details in the painting may become blurred, making some artistic elements difficult to identify, and even affecting the overall visual experience. An image with a smaller contrast failure coefficient means that its brightness range and layer changes are effectively retained, allowing the audience to feel richer details and three-dimensionality in the digital display. This is crucial for the true presentation of works of art, because it ensures that the effect seen by the audience on the screen is consistent with the delicate texture of the original work, and enhances the visual impact and appreciation value of the work of art; for example, "River and Sky Dusk Snow" by Zhang Longzhang, a painter of the Ming Dynasty, is famous for its delicate brushstrokes and well-defined snow scenes. The changes in light and shadow and the details of falling snowflakes in the painting show a very high level of art. If the contrast of the image is not properly adapted during the digitization process, the layering and depth of the snow scene in the painting and the river surface in the distance cannot be clearly presented, which may cause the subtle changes in the painting to be lost, thus affecting its original visual effect. Especially for works such as "River and Sky Dusk Snow" with interlaced light and shadow and delicate gray and white layers, if the contrast is not up to standard, it will be difficult for the audience to experience the beauty of the snowflakes gradually disappearing in the twilight and the profound sense of space in the picture. Therefore, ensuring that the contrast of the image is properly adapted can not only enhance the visual impact of the work, but also help the audience better perceive Zhang Longzhang's ingenious expression of the interweaving of snow scenes and river water when creating, so that the ancient paintings can shine with stronger artistic charm in digital display.

[0090] In one embodiment, obtaining the processing qualified coefficient according to the brightness uniformity coefficient, the size coefficient and the contrast unqualified coefficient includes:

[0091]

[0092] Wherein, ERT is the processing qualification coefficient, UK, HY, and GL are the brightness uniformity coefficient, size coefficient, and contrast unqualified coefficient, respectively, a1, a2, and a3 are the preset proportional coefficients of the brightness uniformity coefficient, size coefficient, and contrast unqualified coefficient, respectively, and a1, a2, and a3 are all greater than 0.

[0093] It should be noted that a1, a2, and a3 are set by professionals according to actual conditions. Generally, the sum of a1, a2, and a3 is 1. For example, a1, a2, and a3 can be 0.3, 0.3, and 0.4, respectively, or other numbers, without specific limitation.

[0094] In one embodiment, judging whether the target image is qualified in the image adaptation process according to the processing qualification coefficient and the preset processing qualification coefficient threshold includes:

[0095] The processing qualification coefficient is compared with the preset processing qualification coefficient threshold. If the processing qualification coefficient is not less than the preset processing qualification coefficient threshold, it means that the target image is qualified in the image adaptation process, and the target image is digitally presented on the AR device through the Micro-LED micro-display chip driving the ancient painting;

[0096] If the processing qualification coefficient is less than the preset processing qualification coefficient threshold, it means that the target image is unqualified in the image adaptation process, and the digitized image of the ancient painting is re-adapted until the processing qualification coefficient of the image after the image adaptation process is not less than the preset processing qualification coefficient threshold. The image after the image adaptation process is digitally presented on the AR device through the Micro-LED microdisplay chip to drive the ancient painting.

[0097] It should be noted that the preset processing qualification coefficient threshold is set by professionals based on actual conditions and is not limited or elaborated on in detail.

[0098] It should be noted that the calculated processing qualification coefficient is compared with the preset processing qualification coefficient threshold. If the processing qualification coefficient of the target image is not less than the preset threshold, it means that the adaptation processing of the image has reached the qualified standard, and it can be directly driven and displayed on the AR device through the Micro-LED micro-display chip to show the digitization effect of the ancient painting; if the processing qualification coefficient is lower than the preset threshold, it means that the target image fails to meet the quality requirements and needs to be re-adapted. After reprocessing, it is necessary to calculate the new processing qualification coefficient again and compare it with the preset threshold until the processing qualification coefficient of the image reaches or exceeds the preset standard; when the image adaptation processing meets the standard, the image is driven and displayed on the AR device through Micro-LED technology to ensure that the digitization effect of the ancient painting is truly restored and achieve the best viewing experience. This evaluation method based on the processing qualification coefficient effectively avoids human intervention and subjective judgment, and ensures the quality control and consistency of ancient paintings in the digital display process.

[0099] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be used to artificially limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. The method for digitally presenting ancient paintings driven by Micro-LED microdisplay chips is characterized in that: The following steps are involved: The image after image adaptation processing of the digitized image of the ancient painting is used as the target image, and the brightness uniformity coefficient, size coefficient and contrast unqualified coefficient of the target image with respect to the image adaptation processing are extracted; Obtaining a processing qualified coefficient according to the brightness uniformity coefficient, the size coefficient and the contrast unqualified coefficient, and judging whether the target image is qualified in the image adaptation processing according to the processing qualified coefficient and a preset processing qualified coefficient threshold; When the target image passes the image adaptation process, the target image will be digitally presented on the AR device through the Micro-LED micro-display chip driving the ancient painting.

2. The method for digitally presenting ancient paintings driven by a Micro-LED microdisplay chip according to claim 1, characterized in that: The brightness uniformity coefficient includes: Convert the target image to a grayscale image and calculate the mean μY and standard deviation σY of the grayscale values ​​in the grayscale image. The calculation formula is: Where Q is the number of rows in the image, E is the number of columns in the image, and Y(n,m) is the grayscale value of the pixel at position (n,m) in the grayscale image. Calculate the brightness uniformity coefficient, the calculation formula is: Where UK is the brightness uniformity index, and ∈ is a preset constant used to avoid division by zero when calculating the standard deviation.

3. The method for digitally presenting ancient paintings driven by a Micro-LED microdisplay chip according to claim 1, characterized in that: The size factors include: Obtain the width and length of the target image, marked as HJ and HG respectively, and divide the width HJ of the target image by the length HG of the target image to obtain the processed proportional coefficient; The width and length of the digitized image of the ancient painting before image adaptation are marked as FG and RE respectively, and the width FG is divided by the length RE to obtain the scale coefficient before processing; The absolute difference between the scale factor after processing and the scale factor before processing is calculated, and the absolute difference is used as the size coefficient of the target image.

4. The method for digitally presenting ancient paintings driven by a Micro-LED microdisplay chip according to claim 1, characterized in that: The contrast failure coefficients include: Grayscale the target image, convert the color image into a grayscale image, count the number of pixels at each grayscale level in the image, and obtain a grayscale histogram; The grayscale histogram shows the distribution of pixels at each grayscale level in the image; Normalize the grayscale histogram so that the sum of the histogram is 1, that is, the number of pixels at each grayscale level divided by the total number of pixels in the image; The normalized histogram reflects the relative distribution of each gray level in the image. The contrast of the image is calculated using the normalized grayscale histogram. The formula for calculating contrast is: Where Qa is the contrast, p a is the normalized number of pixels at the ath gray level, is the mean of the normalized histogram, is the center value of the normalized histogram, and L is the number of gray levels; The obtained contrast value is normalized to obtain the contrast failure coefficient of the image. The calculation formula of the contrast failure coefficient is: Where GL is the contrast failure factor and JK is the maximum possible contrast.

5. The method for digitally presenting ancient paintings driven by a Micro-LED microdisplay chip according to claim 1, characterized in that: The qualified coefficients obtained based on the brightness uniformity coefficient, size coefficient and contrast unqualified coefficient include: Wherein, ERT is the processing qualification coefficient, UK, HY, and GL are the brightness uniformity coefficient, size coefficient, and contrast unqualified coefficient, respectively, a1, a2, and a3 are the preset proportional coefficients of the brightness uniformity coefficient, size coefficient, and contrast unqualified coefficient, respectively, and a1, a2, and a3 are all greater than 0.

6. The method for digitally presenting ancient paintings driven by a Micro-LED microdisplay chip according to claim 1, characterized in that: Judging whether the target image is qualified in the image adaptation process according to the processing qualification coefficient and the preset processing qualification coefficient threshold includes: The processing qualification coefficient is compared with the preset processing qualification coefficient threshold. If the processing qualification coefficient is not less than the preset processing qualification coefficient threshold, it means that the target image has passed the image adaptation process, and the target image is digitally presented on the AR device through the Micro-LED micro-display chip to drive the ancient painting.

7. The method for digitally presenting ancient paintings driven by a Micro-LED microdisplay chip according to claim 1, characterized in that: Judging whether the target image is qualified in the image adaptation process according to the processing qualification coefficient and the preset processing qualification coefficient threshold also includes: If the processing qualification coefficient is less than the preset processing qualification coefficient threshold, it means that the target image is unqualified in the image adaptation process, and the digitized image of the ancient painting is re-adapted until the processing qualification coefficient of the image after the image adaptation process is not less than the preset processing qualification coefficient threshold. The image after the image adaptation process is digitally presented on the AR device through the Micro-LED microdisplay chip to drive the ancient painting.

Images