Color painting image reconstruction system and reconstruction method based on brightness and saturation information matching

Abstract

The application provides a color painting image reconstruction system and method based on brightness and saturation information matching, and relates to the field of color painting image reconstruction.The application comprises HSI color model conversion, Origin software fitting and reconstructed RGB image;the HSI color model conversion is to convert the measured different color RGB color space into HSI color space;the Origin software fitting is to import the HSI color space data into Origin software for data fitting;the reconstructed RGB image is to reconstruct the obtained HSI color space after fitting to obtain the RGB color image.Through the color painting image reconstruction system, the object color information is efficiently reconstructed, the spectral reflectance characteristics are accurately presented, and a scientific and reliable solution is provided for subsequent 3D object color reconstruction and artistic product digital copying.

Description

Technical Field

[0001] This invention relates to the field of color painting image reconstruction, specifically to a color painting image reconstruction system and method based on matching brightness and saturation information. Background Technology

[0002] Cultural heritage faces a dilemma in its preservation. On the one hand, there is the irreversible damage caused by physical display: traditional paintings, exposed to changing environments for extended periods, are prone to irreversible color loss, and precious collections are often "sealed away" for preservation purposes, unable to be seen by the public. On the other hand, there is a technological gap in digital transmission: existing digital reconstruction technologies largely rely on high-end commercial equipment, which is difficult for small and medium-sized museums and universities to afford; moreover, most technologies do not consider the "impact of lighting angle on color reproduction," resulting in significant color discrepancies between digital images and the original artwork.

[0003] Therefore, it is necessary to find an effective method to process and calculate finite images acquired at specific angles, thereby reconstructing images of paintings at arbitrary lighting angles. This paper introduces a color painting image reconstruction method based on matching brightness and saturation information. The method involves actual measurement and theoretical analysis of physical quantities characterizing the properties of each region of the painting sample, and then combines this method with colorimetric theory to reconstruct the images of the corresponding regions, followed by analysis and evaluation. Summary of the Invention

[0004] (a) Technical problems to be solved To address the shortcomings of existing technologies, this invention provides a color painting image reconstruction system and method based on brightness and saturation information matching, which solves the problem that the influence of illumination angle on color reproduction causes a large color deviation between the digital image and the original artwork.

[0005] (II) Technical Solution To achieve the above objectives, the present invention provides the following technical solution: a color painting image reconstruction system based on brightness and saturation information matching, comprising HSI color model conversion, Origin software fitting, and RGB image reconstruction; the HSI color model conversion converts the measured RGB color spaces of different colors into the HSI color space; the Origin software fitting imports the HSI color space data into Origin software for data fitting; and the RGB image reconstruction reconstructs the RGB color image from the fitted HSI color space.

[0006] Preferably, the conversion relationship between the RGB color space and the HSI color space is as follows: ; I: Represents the brightness of the image (equivalent to light intensity I), S: Represents the saturation of the image, H: Represents the hue of the image, θ: Represents the base angle value for calculating the hue H.

[0007] Preferably, the Origin software fitting involves converting the RGB color space to the HSI color space, importing the experimental data into Origin, analyzing and fitting the saturation (S), brightness (I), and illumination angle, and then fitting the S and I values.

[0008] The proposed reconstruction method for color painting images based on brightness and saturation information matching includes the following steps: Step 1: First, calibrate, then measure the RGB color space values ​​under different lighting angles; Step 2: Convert the RGB color space values ​​to HSI color space values ​​using the RGB color space to HSI color space conversion formula; Step 3: Fit the data from the transformation in Step 1 using Origin; Step 4: Obtain the HSI color space value under any lighting angle by using the conversion formula between RGB color space and HSI color space; Step 5: Reconstruct the RGB image from the HSI color space values.

[0009] A system and method for reconstructing color paintings based on matching brightness and saturation information are proposed. The RGB color space is converted to the HSI color space, the experimental data is imported into Origin, and analysis and fitting are performed using light intensity I and illumination angle, and analysis and fitting are performed using saturation S and illumination angle, respectively.

[0010] (III) Beneficial Effects This invention provides a system and method for reconstructing color paintings based on brightness and saturation information matching. It offers the following advantages: The system efficiently reconstructs the color information of objects through the reconstruction of color painting images, accurately presenting spectral reflectance characteristics, and provides a scientific and reliable solution for subsequent 3D object color reconstruction and digital reproduction of artworks. Attached Figure Description

[0011] Figure 1 This is a graph showing the relationship between light intensity I and illumination angle obtained by fitting the color painting image reconstruction system and reconstruction method based on brightness and saturation information matching proposed in this invention. Figure 2 This is a graph showing the relationship between saturation S and illumination angle obtained from the fitting of the color painting image reconstruction system and method based on brightness and saturation information matching proposed in this invention. Figure 3The calculation results of the color difference of the six colors in the color chart of the color painting image reconstruction system and reconstruction method based on brightness and saturation information matching proposed in this invention; Figure 4 The calculation results of the color difference of five colors in a traditional Chinese painting are based on the color painting image reconstruction system and reconstruction method based on brightness and saturation information matching proposed in this invention. Figure 5 The results show the calculation of the color difference of five colors in an oil painting based on the color painting image reconstruction system and reconstruction method based on brightness and saturation information matching proposed in this invention. Detailed Implementation

[0012] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0013] Example 1: like Figure 1-2 As shown, this embodiment of the invention provides a color painting image reconstruction system based on brightness and saturation information matching, including HSI color model conversion, Origin software fitting, and RGB image reconstruction; the HSI color model conversion is to convert the measured RGB color spaces of different colors into the HSI color space; the Origin software fitting is to import the HSI color space data into the Origin software for data fitting; the RGB image reconstruction is to reconstruct the RGB color image from the fitted HSI color space.

[0014] The conversion relationship between the RGB color space and the HSI color space is as follows: ; I: Represents the brightness of the image (equivalent to light intensity I), S: Represents the saturation of the image, H: Represents the hue of the image, θ: Represents the base angle value for calculating the hue H.

[0015] The Origin software fitting process involves converting the RGB color space to the HSI color space, importing the experimental data into Origin, and then analyzing and fitting the saturation (S), brightness (I), and illumination angle.

[0016] The proposed reconstruction method for a color painting image reconstruction system based on brightness and saturation information matching includes the following steps: Step 1: First, calibrate, then measure the RGB color space values ​​under different lighting angles; Step 2: Convert the RGB color space values ​​to HSI color space values ​​using the RGB color space to HSI color space conversion formula; Step 3: Fit the data from the transformation in Step 1 using Origin; Step 4: Obtain the HSI color space value under any lighting angle by using the conversion formula between RGB color space and HSI color space; Step 5: Reconstruct the RGB image from the HSI color space values.

[0017] The RGB color space was converted to the HSI color space, and the experimental data was imported into Origin. The data was then analyzed and fitted using light intensity I and illumination angle, as well as using saturation S and illumination angle.

[0018] CIEDE2000 color difference formula CIE DE2000 is a color difference evaluation standard used to quantify the perceptual difference between two colors by the human eye. Compared to previous formulas (such as CIE76 and CIE94), it significantly improves the uniformity of the color space by introducing hue interaction terms, chroma and luminance correction factors, especially performing better in scenes such as skin tones and blue areas. Its formula is as follows: Experimental verification: Reflectance Measurement and Application: Reflectance of paintings across the entire 200-1000 nm wavelength range is collected using a fiber optic spectrometer. Combined with computer-fitted "brightness I - angle" and "saturation S - angle" functions, this provides data support for accurate color reproduction. Figure 1-2 ) For objects with a large proportion of diffuse energy, the hue value H remains basically unchanged when the lighting angle is changed, while the saturation value S and the brightness value I change to some extent.

[0019] The coefficient of determination (R-square) of the function obtained by fitting the data using Origin software is close to 1 (Table 1), indicating that the variables in the fitted function have a strong explanatory power for the dependent variable. The small SSE of the fitted function indicates that the measured values ​​and the fitted values ​​are very close, thus demonstrating that the Gaussian function can fit the saturation and brightness data well. Figure 3 This is the calculated result of the color difference between the six colors in the color chart.

[0020] Table 1 Table 2 clearly shows that the method proposed in this experiment can reconstruct the color information of the artwork quite well. Considering the small error in the relationship between the fitted function and the actual change function during the measurement and fitting process, which leads to differences between the reconstructed colors and the actual camera shots, the differences remain within a small range.

[0021] The coefficient of determination (R-square) of the function obtained by fitting the data using Origin software is close to 1 (Table 2), indicating that the variables in the fitted function have a strong explanatory power for the dependent variable. The small SSE of the fitted function indicates that the measured values ​​and the fitted values ​​are very close, thus demonstrating that the Gaussian function can fit the saturation and brightness data well. Figure 4 This represents the calculated color difference of the five colors in a traditional Chinese painting.

[0022] Table 2 The coefficient of determination (R-square) of the function obtained by fitting the data using Origin software is close to 1 (Table 3), indicating that the variables in the fitted function have a strong explanatory power for the dependent variable. The small SSE of the fitted function indicates that the measured values ​​and the fitted values ​​are very close, thus demonstrating that the Gaussian function can fit the saturation and brightness data well. Figure 5 For oil painting Table 3 The calculation results of the color difference of the five colors.

[0023] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A color painting image reconstruction system based on brightness and saturation information matching, characterized in that: The process includes HSI color model conversion, Origin software fitting, and RGB image reconstruction. The HSI color model conversion converts the measured RGB color spaces into the HSI color space. The Origin software fitting imports the HSI color space data into Origin software for data fitting. The RGB image reconstruction obtains an RGB color image by reconstructing the fitted HSI color space.

2. The luminance and saturation information matching based color painting image reconstruction system according to claim 1, characterized in that: The conversion relationship between the RGB color space and the HSI color space is as follows: I: Represents the brightness of the image (equivalent to light intensity I), S: Represents the saturation of the image, H: Represents the hue of the image, θ: Represents the base angle value for calculating the hue H.

3. The luminance and saturation information matching based color painting image reconstruction system according to claim 1, characterized in that: The Origin software fitting process involves converting the RGB color space to the HSI color space, importing the experimental data into Origin, and then analyzing and fitting the saturation (S), brightness (I), and illumination angle.

4. The reconstruction method based on the color painting image reconstruction system matching the luminance and saturation information according to claim 1, characterized in that: Includes the following steps: Step 1: First, calibrate, then measure the RGB color space values ​​under different lighting angles; Step 2: Convert the RGB color space values ​​to HSI color space values ​​using the RGB color space to HSI color space conversion formula; Step 3: Fit the data from the transformation in Step 1 using Origin; Step 4: Obtain the HSI color space value under any lighting angle by using the conversion formula between RGB color space and HSI color space; Step 5: Reconstruct the RGB image from the HSI color space values.

5. The luminance and saturation information matching-based color painting image reconstruction system and method of claim 4, wherein: The RGB color space was converted to the HSI color space, and the experimental data was imported into Origin. The data was then analyzed and fitted using light intensity I and illumination angle, as well as using saturation S and illumination angle.

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