CN113143521B - Color correction method for image acquired by three-dimensional scanning equipment - Google Patents

Color correction method for image acquired by three-dimensional scanning equipment Download PDF

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CN113143521B
CN113143521B CN202011414457.9A CN202011414457A CN113143521B CN 113143521 B CN113143521 B CN 113143521B CN 202011414457 A CN202011414457 A CN 202011414457A CN 113143521 B CN113143521 B CN 113143521B
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杨英保
周桢人
王瑞剑
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Shenzhen Up3d Tech Co ltd
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Abstract

The invention provides a color correction method for an image acquired by three-dimensional scanning equipment, which comprises the step of correcting the color of the image acquired by the three-dimensional scanning equipment according to standard light intensity L0Under the condition, the color is performed by collecting the gray values of three single channels of RGB of the gray image of the standard color blockColor calibration; establishing standard light intensity L by polynomial regression algorithm0Calculating the standard light intensity L of the linear regression equation I according to the linear regression equation I0Obtaining a mapping relation f1 between the gray value combination of the RGB channel gray image and the real color by using the lower coefficient matrix A; at a standard light intensity L0On the basis, is enhanced to L0+ L, establishing a standard light intensity L0Linear regression equation II under + L, and calculating the light intensity L0The gray value of the image is restored to the light intensity of L under the + L condition0Substituting the gray value of the time-lapse image into the mapping relation f 1; the true color of the image is obtained. The color correction method for the image acquired by the three-dimensional scanning equipment provided by the invention ensures that the restored color image is not influenced by the light intensity of incident light and the real color image is accurately restored in real time.

Description

Color correction method for image acquired by three-dimensional scanning equipment
Technical Field
The invention relates to the technical field of image processing, in particular to a color correction method for an image acquired by three-dimensional scanning equipment.
Background
At present, most tooth three-dimensional scanning equipment is not provided with a color camera module in order to save more cost and installation space, generally uses two single-channel industrial cameras to form a binocular measurement system, and when a gray scale image is collected, the gray scale image under red light (R), green light (G) and blue light (B) is obtained by changing the color of projection light, and then the color image is synthesized by three single-channel gray scale images. The binocular measurement system is easy to install and low in price, but the color of the image fused with three channels of gray scales is changed due to the change of the light intensity of the environment, so that the color image is not real, and when the intensity of projection light is improved, the color of the fused color image is distorted.
At present, a polynomial regression method, an artificial neural network method and an SVR method are mainly adopted for the color correction algorithm of the three-dimensional scanning device, and according to actual verification, comprehensive correction errors and calculation time show that the polynomial regression algorithm is more suitable for correcting the image colors of the scanning device, but the correction effect of the conventional polynomial regression method on the image colors is influenced by light intensity, so that the imaging effect of the color image is influenced. For the application scene of the tooth three-dimensional scanning device, because the light entering amount at the gap of the tooth is small, the light intensity of incident light needs to be enhanced, and a color image needs to be displayed in real time, the conventional method for correcting the color of the image by utilizing the polynomial regression method cannot meet the requirement of color correction in the application scene of the tooth three-dimensional scanning device.
There is a need for an image color correction method with fast calculation speed, which can accurately restore a color image in real time, and the restored color image is not affected by light intensity, so as to solve the above problems.
Disclosure of Invention
In view of the above problems, the present invention provides a color correction method for an image acquired by a three-dimensional scanning device to improve the above problems.
In a first aspect, the present invention provides a color correction method for an image acquired by a three-dimensional scanning device, comprising the following steps:
s1: at a standard light intensity L0Under the condition, color calibration is carried out by collecting gray values of three single channels of RGB of a gray image of a standard color block; establishing standard light intensity L by polynomial regression algorithm0Calculating the standard light intensity L of the linear regression equation I0Obtaining a mapping relation f1 between the gray value combination of the RGB channel gray image and the real color by using the lower coefficient matrix A;
s2: at a standard light intensity L0On the basis, is enhanced to L0+ L, establishing a standard light intensity L0Linear regression equation II under + L, and calculating the light intensity L0The gray value of the image under the + L condition is restored to the light intensity of L0The gray value of the time-lapse image is substituted into the mapping relation f 1;
s3: and correcting the color of the color image according to the mapping relation f1 to obtain the true color of the image.
More preferably, in step S2, the light intensity is L0Carrying out secondary color calibration under the condition of + L, and obtaining the light intensity of the light source under the condition of L through a linear regression equation II0And a coefficient matrix B of + L, and obtaining a mapping relation f2 between the gray value under the light intensity of L0+ L and the gray value increasing value under the light intensity based on L0.
Preferably, the matrix equation IV corresponding to the linear regression equation II is such that the incident light intensity is L0Device acquisition at + L hoursThe difference value of the gray value of the three single-channel images and the gray value added value of the three single-channel images obtained by substituting the gray value into the matrix equation IV is obtained to obtain the light intensity L0+ L is reduced to a light intensity of L0The grey value of the image.
Preferably, the matrix form of the linear regression equation I is a matrix equation III, and the linear regression equation I is reduced to the light intensity L0And substituting the obtained gray values into a matrix equation III to calculate the gray values of the RGB single-channel images corresponding to the real colors of the images so as to obtain the real colors of the images.
More preferably, in step S1, (x, xy, x) with the number of terms of 10 is used21) calibrating the regression model, and setting the color combination of the ith standard color block as R under the condition of standard light intensity L00i、G0i、B0iThe gray value of the ith standard color block gray image collected by the equipment is Ri、Gi、BiThen the linear regression equation I is satisfied,
Figure GDA0003640131230000021
wherein, aijIs the conversion coefficient of the regression equation, vij(J ═ 1, 2, 3.., J) (J ═ 10) is a regression model;
the matrix form of the linear regression equation I is as follows:
X＝AT·V (Ⅲ)
wherein, X is a standard color block three-channel value matrix of 3 × I, A is a conversion coefficient matrix of J × 3, and V is a polynomial regression matrix of J × I, then, the matrix A is obtained by a least square method, and A is (V.V.V.T)-1·(V·XT) Then the standard light intensity L can be calculated0The coefficient matrix a of the lower linear regression equation i.
Preferably, the regression model vijSpecifically {1, Ri，Gi，Bi，RiGi，RiBi，GiBi，Ri 2，Gi 2，Bi 2}。
Preferably, during the secondary color calibration, the light intensity value of the incident light is L0+ L, the gray value R 'of the ith standard color block'0i、G′0i、B′0iThe gray value of the ith standard color lump gray image collected by the equipment is R'i、G′i、B′iThen the linear regression equation ii satisfies:
Figure GDA0003640131230000031
wherein, bijIs the conversion coefficient of the regression equation, wij(J ═ 1, 2, 3.., J) (J ═ 10) is a regression model; calculating the light intensity to be L by a linear regression equation II0+ L condition, conversion factor bijThe corresponding coefficient matrix B.
Preferably, the regression model wijIn particular to
Figure GDA0003640131230000032
Figure GDA0003640131230000033
More preferably, the standard color blocks are collected on a 24-color standard colorimetric plate.
The invention has the technical effects that: the color correction method for the image collected by the three-dimensional scanning equipment can still ensure the color restoration effect of the image under the condition of changing the incident light intensity, so that the restored color image is not influenced by the incident light intensity, and the real color image is accurately restored in real time through the obtained single-channel gray image.
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FIG. 1 is a flow chart of a color correction method for an image acquired by a three-dimensional scanning device according to the present invention;
FIG. 2 is a diagram illustrating the imaging effect of the corrected R-channel grayscale image according to the present invention;
FIG. 3 is an image of a corrected G-channel grayscale image according to the present invention;
FIG. 4 is a diagram illustrating the imaging effect of a corrected B-channel grayscale image according to the present invention;
fig. 5 is an imaging effect diagram of the corrected RGB three-channel fused gray scale image provided by the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the 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.
The invention provides a color correction method for an image acquired by three-dimensional scanning equipment, which comprises a correction method when the light intensity is not enhanced and a correction method when the light intensity is enhanced, as shown in figure 1.
When the light intensity is not enhanced, collecting the gray image of the standard color block to establish the standard light intensity L0Setting a gray value matrix, calibrating colors, calculating a regression coefficient matrix under standard light intensity, and substituting the regression coefficient matrix into the standard light intensity L according to the gray image obtained by scanning0Under the condition, in a linear regression equation of the color calibration calculation coefficient matrix, calculating a gray value matrix of the real image to obtain an RGB pixel channel value combination, and further obtaining a corrected color image.
When the light intensity is increased, the light intensity is set from L0Enhancement to L0+ L, establishing L0Calculating an enhanced regression coefficient matrix by using the gray value matrix of the light intensity enhancement value under the condition of + L and performing secondary color calibration, calculating the gray value enhancement value of the image according to the enhanced regression coefficient matrix obtained by the secondary color calibration, scanning the obtained gray image, making a difference value with the gray value enhancement value to restore the gray value of the standard light intensity value, and substituting the gray value into the standard light intensity L0Further calculating a gray value matrix corresponding to the real color of the obtained image in a matrix equation corresponding to a linear regression equation established by the color mark at regular time under the condition, thereby obtaining the corrected real color of the imageAnd (4) color. The method specifically comprises the following steps:
s1: at a standard light intensity L0Under the condition, color calibration is carried out by collecting gray values of three single channels of RGB of a gray image of a standard color block; establishing standard light intensity L by polynomial regression algorithm0Calculating the standard light intensity L of the linear regression equation I according to the linear regression equation I0Obtaining a mapping relation f1 between the gray value combination and the real color of the RGB single-channel gray image by using the coefficient matrix A;
the specific calculation steps are as follows:
taking account of the calculation amount, the calculation speed, the regression accuracy and other factors, the (x, xy, x) with the number of terms of 10 is adopted2And 1) calibrating the regression model at the standard light intensity L0Under the condition of (1), the color combination of the ith standard color block of the 24-color standard colorimetric plate is set as R0i、G0i、B0iAnd the gray value of the ith standard color block gray image collected by the equipment is Ri、Gi、BiThen the linear regression equation I is satisfied,
Figure GDA0003640131230000041
wherein, aijIs the conversion coefficient of the regression equation, vij(J ═ 1, 2, 3.., J) (J ═ 10) is a regression model, regression model vijSpecifically {1, Ri，Gi，Bi，RiGi，RiBi，GiBi，Ri 2，Gi 2，Bi 2}；
The matrix form of the linear regression equation I is as follows:
X＝AT·V (Ⅲ)
wherein, X is a standard color block three-channel value matrix of 3 × I (I ═ 24), a is a conversion coefficient matrix of J × 3(J ═ 10), and V ═ J × I polynomial regression matrix, then, the matrix a, a ═ V · V ═ is obtained by the least square methodT)-1·(V·XT) Then the mark can be calculatedQuasi light intensity L0The coefficient matrix a of the lower linear regression equation i.
Since the incident light is divided into red light (R), green light (G), and blue light (B), when the illumination intensity of the incident light is enhanced by a certain channel, the imaging conditions of objects of different colors are non-linearly changed, so that color calibration is required for the imaging effects of different light intensities.
S2: at a standard light intensity L0On the basis, is enhanced to L0+ L, establishing a standard light intensity L0Solving L by using a linear regression equation II under + L0The gray value under + L light intensity and the gray value based on L0The mapping relationship f2 between the gray scale value increases under the light intensity, and the light intensity L0The gray value of the image is restored to the light intensity of L under the + L condition0Substituting the gray value of the time image into the mapping relation f 1;
the specific calculation steps are as follows:
in the process of secondary color calibration, the light intensity value of incident light is L0+ L, the gray value R 'of the ith standard color block'0i、G′0i、B′0iThe gray value of the ith standard color block gray image collected by the equipment is R'i、G′i、B′iThen the linear regression equation ii satisfies:
Figure GDA0003640131230000051
wherein, bijIs the conversion coefficient of the regression equation, wij(J ═ 1, 2, 3.., J) (J ═ 10) is a regression model, with regression model w being the regression modelijIn particular to
Figure GDA0003640131230000052
Calculating the light intensity to be L by a linear regression equation II0+ L condition, conversion factor bijCorresponding coefficient matrix B, finding L0The gray value under + L light intensity and the gray value based on L0The mapping relationship f2 between the gray scale value increases under the light intensity, and the secondary color calibration process is ended.
The matrix form of the linear regression equation I is a matrix equation III, and the matrix form of the linear regression equation II is as follows:
X′＝BT·W (Ⅳ)
incident light intensity of L0The difference value of the gray value of the three single-channel images acquired by the equipment at + L time and the gray value added value of the three single-channel images obtained by substituting the gray value added value into the matrix equation IV is the light intensity L0+ L is reduced to a light intensity of L0The grey value of the image. For the color image to be reduced, the actual color is reduced to light intensity L0And substituting the obtained gray values into a mapping relation f1 between the gray value combination and the real color of the RGB three single-channel gray image, calculating the gray values of the three single channels corresponding to the real color of the image, and further synthesizing the real color of the image.
In particular, including at an incident light intensity of L0When + L, defining the gray values of three single channels collected by the equipment as RL、GL、BLAccording to the coefficient matrix B obtained during the secondary color calibration and the matrix equation IV corresponding to the linear regression equation II, the gray value increase values of the three single channels are respectively R0、G0、B0Then the light intensity is set to L0The gray value obtained by + L is reduced to light intensity L0The gray value of the time image is RL-R0、GL-G0、BL-B0Substituting the gray values into a regression model in a matrix equation III, wherein the matrix equation III can reflect the mapping relation f1 between the gray value combination of the collected RGB channel gray images and the gray values of the three single-channel images corresponding to the real color, so that the gray values of the three single-channel images corresponding to the real color of the image can be calculated, and the real color of the image can be synthesized;
s3: and correcting the color of the color image according to the mapping relation f1 to obtain the true color of the image.
The method provided by the invention is used for correcting the color of the image of the three-dimensional scanner, can quickly restore the color image, and can avoid the influence of the light intensity of incident light on the imaging effect. Fig. 2-5 are images of corrected RGB single-channel gray scale images and fused gray scale images of a dental three-dimensional scanning device by using the method provided by the invention.
In summary, the present invention provides a color correction method for an image collected by a three-dimensional scanning device, which calibrates a standard color through a standard color palette, calculates a gray value combination by using a polynomial regression algorithm, performs secondary color calibration, calibrates a regression coefficient matrix when a light intensity is enhanced, establishes a linear regression equation between a light intensity enhanced value and a gray value transformation value, thereby reducing a gray value of the image under the standard light intensity, substitutes a mapping relation f1 between the gray value combination of an RGB three-channel gray image and a real color, calculates a gray value of an RGB three-channel corresponding to the real color, further synthesizes the real color of the image, and realizes color correction. The color correction method provided by the invention can still ensure the color reduction effect of the image under the condition of changing the incident light intensity, so that the reduced color image is not influenced by the incident light intensity, and the real color image is accurately reduced in real time through the obtained single-channel gray image.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art will understand that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not necessarily depart from the spirit and scope of the corresponding technical solutions.

Claims (8)

1. A color correction method for an image acquired by a three-dimensional scanning device is characterized by comprising the following steps:
s1: under the condition of standard light intensity L0, color calibration is carried out by collecting the gray values of three single channels of RGB of the gray image of the standard color block; establishing a linear regression equation I under the standard light intensity L0 by using a polynomial regression algorithm, calculating a coefficient matrix A of the linear regression equation I under the standard light intensity L0, and obtaining a mapping relation f1 between the gray value combination of the RGB channel gray level image and the real color;
s2: on the basis of the standard light intensity L0, the gray value of the image is enhanced to L0+ L, a linear regression equation II under the standard light intensity L0+ L is established, the gray value of the image under the condition of the light intensity L0+ L is restored to the gray value of the image when the light intensity is L0, and the gray value is substituted into the mapping relation f 1;
s3: correcting the color of the color image according to the mapping relation f1 to obtain the real color of the image;
in step S2, the light intensity is L0Carrying out secondary color calibration under the condition of + L, and obtaining the light intensity of the light source as L through a linear regression equation II0+ L coefficient matrix B, finding L0The gray value under + L light intensity and the gray value based on L0The mapping relationship f2 between the gray scale value increases under light intensity.
2. The method of claim 1, wherein the linear regression equation II corresponds to a matrix equation IV with incident light intensity L0The difference value of the gray value of the three single-channel images acquired by the equipment at + L time and the gray value added value of the three single-channel images obtained by substituting the gray value added value into the matrix equation IV is the light intensity L0+ L is reduced to a light intensity of L0The grey value of the image.
3. The method of claim 2, wherein the linear regression equation I is in the form of matrix III, and the linear regression equation I is reduced to the light intensity L0And substituting the obtained gray values into a matrix equation III to calculate the gray values of the RGB single-channel images corresponding to the real colors of the images so as to obtain the real colors of the images.
4. The method for correcting color of an image captured by a three-dimensional scanning device according to claim 1, wherein in step S1, (x, xy, x) with the term number of 10 is used21) calibrating the regression model, and setting the color group of the ith standard color block under the condition of standard light intensity L0With the synthesis being R0i、G0i、B0iAnd the gray value of the ith standard color block gray image collected by the equipment is Ri、Gi、BiThen the linear regression equation I is satisfied,
Figure FDA0003631014330000021
wherein, aijIs the conversion coefficient of the regression equation, vij(J ═ 1, 2, 3.., J) (J ═ 10) is a regression model;
the matrix equation III corresponding to the linear regression equation I is as follows:
X＝AT·V (Ⅲ)
wherein, X is a standard color block three-channel value matrix of 3 × I, A is a conversion coefficient matrix of J × 3, and V is a polynomial regression matrix of J × I, then, the matrix A is obtained by a least square method, and A is (V.V.V.T)-1·(V·XT) Then the standard light intensity L can be calculated0The coefficient matrix a of the lower linear regression equation i.
5. Method for correcting the color of an image acquired by a three-dimensional scanning device according to claim 4, characterized in that the regression model vijSpecifically {1, Ri，Gi，Bi，RiGi，RiBi，GiBi，Ri 2，Gi 2，Bi 2}。
6. The method of claim 4, wherein during the secondary color calibration, the incident light intensity value is L0+ L, the gray value R 'of the ith standard color block'0i、G′0i、B′0iThe gray value of the ith standard color lump gray image collected by the equipment is R'i、G′i、B′iThen the linear regression equation ii satisfies:
Figure FDA0003631014330000022
wherein, bijIs the conversion coefficient of the regression equation, wij(J ═ 1, 2, 3.., J) (J ═ 10) is a regression model; calculating the light intensity to be L by a linear regression equation II0+ L condition, conversion coefficient bijThe corresponding coefficient matrix B.
7. The method of claim 6, wherein the regression model w is a color correction modelijSpecifically { L, R'i，G′i，B′i，R′iG′i，R′iB′i，G′iB′i，R′i 2，G′i 2，B′i 2}。
8. The method of claim 6, wherein the standard color blocks are obtained from a 24-color standard color palette.
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