CN107705266B - Panoramic camera lens classification method - Google Patents
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Abstract
The invention provides a panoramic camera lens classification method, and belongs to the technical field of image processing. The method comprises the following steps: shooting images to be judged under different light sources by using each lens of the panoramic camera to be judged; calculating the chromatic aberration offset of images shot by all the lenses under the same light source; calculating the color cast of the light source of each lens under different light sources; constructing a color consistency evaluation function according to the color difference deviation degree and the light source color deviation degree, and calculating the color consistency value of each lens; and sorting according to the color consistency indexes, and assembling the N lenses with the similar color consistency indexes. The method is simple and effective, can greatly reduce the difficulty of the chromatic aberration correction algorithm, can simultaneously reduce the model complexity of the chromatic aberration correction algorithm, and improves the image correction effect.
Description
Technical Field
The invention belongs to the technical field of image processing, and particularly relates to a panoramic camera lens classification method.
Background
Due to the defects of the manufacturing process of the lens in the panoramic camera, the color difference of the image shot by the same lens is obvious at different positions, and in addition, due to the difference of the optical characteristics of different lenses, the problem of color inconsistency also exists between different lenses, so that the image colors presented by the panoramic video output by the panoramic camera are inconsistent, and the image quality of the image is seriously influenced.
For the problem of color inconsistency of an output video of a panoramic camera, color difference correction algorithm is mostly used for improvement. Because the images shot by the same lens have different colors at different positions and different optical characteristics among different lenses, the difficulty of a chromatic aberration correction algorithm is increased, and the corrected effect is poor.
Disclosure of Invention
In order to reduce the difficulty of a chromatic aberration correction algorithm and improve the chromatic aberration correction effect, the invention provides a panoramic camera lens classification method, which classifies and assembles lenses with similar chromatic aberration.
The invention provides a panoramic camera lens classification method, which comprises the following steps:
shooting images to be judged under different light sources by using each lens of the panoramic camera to be judged;
calculating the chromatic aberration offset of images shot by all the lenses under the same light source;
specifically, according to the collected images to be evaluated, the color average value and the color gain value of the image formed by each lens in different light source environments at different ring positions are counted, two-dimensional color gain discrete points are drawn according to the value from the ring position to the image center pixel point and the corresponding color gain value, and a polynomial fitting function is obtained; fitting the color gain discrete points into a straight line according to a polynomial fitting function; calculating the chromatic aberration offset of each lens under each light source according to the color gain discrete points;
calculating the color cast of the light source of each lens under different light sources;
constructing a color consistency evaluation function according to the chromatic aberration deviation degree and the light source chromatic deviation degree, and calculating the color consistency value of each lens, wherein the color consistency evaluation function specifically comprises the following steps:
constructing a color consistency evaluation function according to the color difference deviation degree and the light source color deviation degree as follows:
val＝δ*(α1*fc(r)+β1*fc(b))+ε*(α2*fl(r)+β2*fl(b))
in the formula, fc(r)、fc(b)Respectively representing the color difference offset of the red and blue components, fl(r)、fl(b)Light source color cast representing red and blue components, respectively, α1、β1、α2、β2Delta and epsilon are weight factors;
substituting the color deviation degree and the light source color deviation degree of each lens into the formula to calculate to obtain a color consistency value val of each lens;
and sorting according to the color consistency indexes, and assembling the N lenses with similar color consistency values.
Furthermore, the shooting environment of each lens of the panoramic camera is the same as the standard reference object;
the standard reference object is white paper, or 18% gray card, or standard white card, and the standard reference object fills the whole visual field of the lens;
the shooting environment is a standard color temperature box with the same light source;
the types of the standard light sources in the color temperature box are M, and the number of the images to be evaluated shot by each lens is M.
Further, the specific steps of calculating the color average value and the color gain value of the image formed by each lens in different light source environments at different ring positions according to the collected image to be evaluated are as follows:
taking rings at equal intervals by taking a central pixel point as a circle center on an image to be evaluated, dividing the image into K different annular regions, and then counting the number of red pixel points, the number of green pixel points, the number of blue pixel points, the sum of red components, the sum of green components and the sum of blue components of each annular region i to be calculated, wherein i is more than or equal to 1 and less than or equal to K;
calculating the average value of each color component in the annular region i according to the red component sum, the green component sum, the blue component sum, the red pixel number, the green pixel number and the blue pixel number in the annular region i, wherein the calculation formula is as follows:
Ai(r)＝Si(r)/x
Ai(g)＝Si(g)/y
Ai(b)＝Si(b)/z
Si(r) denotes the sum of the red components, S, in the annular region ii(g) Representing the sum of the green components, S, in the annular region ii(b) Representing the sum of the blue components, A, in the annular region ii(r) represents the average of the red components in the annular region i, Ai(g) Denotes the average value of the green component, A, in the annular region ii(b) The average value of blue components in the annular area i is represented, and x, y and z respectively represent the number of red, green and blue color components in the annular area i;
the gain values of the red and blue components relative to the green component are calculated from the average value of the components in the annular region i, and the calculation formula is as follows:
Gi(r)＝Ai(g)/Ai(r)
Gi(b)＝Ai(g)/Ai(b)
Gi(r)、Gi(b) respectively representing the gain value of the red component and the gain value of the blue component in the annular region i.
Further, the calculating of the chromatic aberration offset of each lens under each light source according to the color gain discrete points is specifically as follows;
and respectively calculating the difference between the maximum value and the minimum value of the gain values of the red component and the blue component according to the gain discrete points of the red component and the blue component of each lens, and taking the ratio of the difference value and the minimum value of the gain values of the red component and the blue component as the chromatic aberration offset of each lens under the corresponding standard light source.
Further, the calculating the color cast of the light source of each lens under different light sources specifically includes:
according to the red gain value and the blue gain value of the single lens in different annular areas, the overall red component gain value and the blue component gain value of the single lens are obtained, and the calculation formula is as follows:
Gi(r)、Gi(b) respectively representing the gain value of a red component and the gain value of a blue component in the annular area i, G (r), G (b) respectively representing the gain values of the whole red component and the blue component of a single lens, and K is the total number of the annular areas;
calculating a red component gain fitting value and a blue component gain fitting value by taking the distance of every 1 pixel as a sampling radius according to the polynomial fitting function; then, the gain ratio is obtained by dividing the gain fitting value by the overall gain value, and the calculation formula is as follows:
coei(r)＝fit_Gi(r)/G(r)
coei(b)＝fit_Gi(b)/G(b)
in the formula, fit _ Gi(r)、fit_Gi(b) Respectively representing red and blue component gain fit values of different radii i, G (r), G (b) respectively representing overall red and blue component gain values for a single lens, coei(r)、coei(b) Respectively representing the gain ratio of red components and the gain ratio of blue components with different radii i, and drawing a gain ratio straight line graph;
according to the gain ratios, the maximum value and the minimum value of the gain ratio of the red component and the blue component at the same radius of the image shot by the M light sources of the same lens are respectively calculated, the difference between the maximum value and the minimum value is divided by the minimum value to obtain the color deviation degrees of the light sources at different radii, and then the average value of the color deviation degrees of the light sources at different radii is calculated to be used as the color deviation degree of the light source of the lens.
The invention provides a panoramic camera lens classification method, which is used for classifying and assembling lenses with similar color consistency values by calculating the color consistency values of all the lenses. The method is simple and effective, can greatly reduce the difficulty of the chromatic aberration correction algorithm, can reduce the model complexity of the chromatic aberration correction algorithm, and improves the image correction effect.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a flowchart of a method for classifying lenses of a panoramic camera according to an embodiment of the present invention;
FIG. 2 is a schematic view of a color gain line provided by an embodiment of the present invention;
fig. 3 is a schematic diagram of a color gain ratio straight line provided by an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail with reference to the accompanying drawings in conjunction with the following detailed description. It should be understood that the description is intended to be exemplary only, and is not intended to limit the scope of the present invention. Moreover, in the following description, descriptions of well-known structures and techniques are omitted so as to not unnecessarily obscure the concepts of the present invention.
The invention provides a panoramic camera lens classification method aiming at the problem of color inconsistency among all lens image areas and among all lenses of a panoramic camera.
As shown in fig. 1, the method comprises the steps of:
s1: shooting images to be judged under different light sources by using each lens of the panoramic camera to be judged;
in the embodiment of the invention, the shooting environment of each lens is the same as the standard reference object of shooting, the shooting environment is a standard color temperature box with multiple light sources, the standard reference object is white paper, or 18% gray card, or standard white card, and the size of the standard reference object needs to fill the whole visual field of the lens. Any equivalent reference may also be used in a particular application.
When the image is collected, except the standard light source of the color temperature box, no other light source influence exists, and each camera is placed in the color temperature box and is shot by aiming at the light source. And switching the light sources of the standard color temperature box, and acquiring one image under different light sources respectively. When color consistency evaluation is performed, preferably, M standard light sources are adopted, and M images to be evaluated are shot by each lens; wherein M is an integer greater than 1, the more light source types are selected, the more accurate the color consistency calculation is.
S2: calculating the chromatic aberration offset of images shot by all the lenses under the same light source;
according to the collected images to be evaluated, the color average value and the color gain value of the image formed by each lens at different ring positions are counted, two-dimensional color gain discrete points are drawn according to the value from the ring position to the image center pixel point and the corresponding color gain value, and a polynomial fitting function is obtained; and fitting the color gain discrete points into a straight line according to a polynomial fitting function. And calculating the chromatic aberration offset of each lens under each light source according to the color gain discrete points, and quantitatively evaluating the color consistency of the lenses.
In the embodiment of the invention, the specific implementation steps are as follows:
because the color deviation problem of the lens presents a radial symmetry characteristic, the color deviation of the center of the image is very small, and the color deviation is larger towards the periphery. Preferably, the method comprises the steps of taking rings at equal intervals by taking a central pixel point as a circle center on an image to be evaluated, dividing the image into K different annular regions, and then counting the number of red pixels, the number of green pixels, the number of blue pixels, the sum of red components, the sum of green components and the sum of blue components of each annular region i to be calculated, wherein i is more than or equal to 1 and less than or equal to K.
Calculating the average value of each color component in the annular region i according to the red component sum, the green component sum, the blue component sum, the red pixel number, the green pixel number and the blue pixel number in the annular region i, wherein the calculation formula is as follows:
Ai(r)＝Si(r)/x
Ai(g)＝Si(g)/y
Ai(b)＝Si(b)/z
Si(r) denotes the sum of the red components, S, in the annular region ii(g) Representing the sum of the green components, S, in the annular region ii(b) Representing the sum of the blue components, A, in the annular region ii(r) represents the average of the red components in the annular region i, Ai(g) Denotes the average value of the green component, A, in the annular region ii(b) The average value of blue components in the annular area i is represented, and x, y and z respectively represent the number of red, green and blue color components in the annular area i;
the gain values of the red and blue components relative to the green component are calculated from the average value of the components in the annular region i, and the calculation formula is as follows:
Gi(r)＝Ai(g)/Ai(r)
Gi(b)＝Ai(g)/Ai(b)
Gi(r)、Gi(b) respectively representing the gain value of the red component and the gain value of the blue component in the annular region i.
The method is utilized to calculate the gain value of the red and blue components in each annular area respectively to obtain the gain discrete points of the red and blue components of the lens, and then polynomial functions are utilized to fit two straight lines for the gain discrete points of the blue component and the red component respectively, as shown in fig. 2, a straight line r represents a straight line fitted by the discrete points of the red component, and a straight line b represents a straight line fitted by the blue component. Under the same light source, when the two fitted straight lines are more parallel, the color consistency of the lens is better, and under an ideal condition, the two fitted straight lines are horizontal straight lines; under the same light source, when the straight lines of the same color component fitted by the two lenses are closer, the closer the color consistency of the two lenses is.
In order to quantitatively evaluate the color consistency of the lens, the chromatic aberration offset degree of the lens under each light source is calculated. And respectively calculating the difference between the maximum value and the minimum value of the gain values of the red component and the blue component according to the gain discrete points of the red component and the blue component of each lens, taking the ratio of the difference value to the minimum value of the gain values of the red component and the blue component as the chromatic aberration offset of each lens under the corresponding standard light source, and taking the chromatic aberration offset as the judgment index of color consistency. Under the same light source, the smaller the chromatic aberration offset of each lens is, the better the color consistency of the lens is, and ideally, the chromatic aberration offset of each light source should be zero.
S3: calculating the color cast of the light source of each lens under different light sources;
in order to evaluate the color consistency of the lenses more fully, the invention calculates the light source color cast of each lens under different light sources, and further quantitatively evaluates the color consistency of the lenses.
In the embodiment of the invention, the specific implementation steps are as follows:
and according to the red and blue gain values of the single lens in different annular areas calculated in the step of S2, obtaining the gain value of the whole red and blue component of the single lens, wherein the calculation formula is as follows:
Gi(r)、Gi(b) the gain values of the red component and the blue component in the annular region i are respectively shown, G (r) and G (b) respectively show the gain values of the whole red component and the blue component of a single lens, and K is the total number of the annular regions.
Calculating a red and blue component gain fitting value by taking the distance of every 1 pixel as a sampling radius according to the polynomial fitting function calculated in the step S2; then, the gain ratio is obtained by dividing the gain fitting value by the overall gain value, and the calculation formula is as follows:
coei(r)＝fit_Gi(r)/G(r)
coei(b)＝fit_Gi(b)/G(b)
in the formula, fit _ Gi(r)、fit_Gi(b) The gain fit values for the red and blue components representing different radii i, respectively, G (r), G (b) the overall red and blue component gain values for a single lens, respectively, coei(r)、coei(b) Respectively representing the gain ratio of the red component and the gain ratio of the blue component at different radii i.
A gain ratio straight line graph is drawn, and as shown in fig. 3, a straight line r represents a red component gain ratio straight line, a straight line b represents a blue component gain ratio straight line, and the two gain ratio straight lines fluctuate up and down on a straight line of coe-1, and ideally, the straight line r and the straight line b should coincide with a straight line of coe-1. The closer the gain ratio line is to the line coe of 1, the better the color consistency of the lens.
The method is adopted to obtain a gain ratio line graph of each lens under M light sources, the maximum value and the minimum value of the gain ratio of the red component and the blue component at the same radius of the M light sources are respectively calculated according to the gain ratio, the difference between the maximum value and the minimum value is divided by the minimum value to obtain the light source color cast degrees at different radii, and then the light source color cast degrees at different radii are averaged to be used as the light source color cast degree of the lens. The smaller the color cast of the light source is, the better the color consistency of the lens is, and ideally, the color cast of the light source of each lens should be zero.
S4: constructing a color consistency evaluation function according to the color difference deviation degree and the light source color deviation degree, and calculating color consistency indexes of all the lenses;
constructing a color consistency evaluation function according to the color difference deviation degree and the light source color deviation degree as follows:
val＝δ*(α1*fc(r)+β1*fc(b))+ε*(α2*fl(r)+β2*fl(b))
in the formula, fc(r)、fc(b)Respectively representing the color difference offset of the red and blue components, fl(r)、fl(b)Light source color cast representing red and blue components, respectively, α1、β1、α2、β2δ, ε are weighting factors.
And substituting the color deviation degree of each lens and the color deviation degree of the light source into the formula to calculate to obtain a color consistency value val of each lens.
S5: and sorting according to the color consistency indexes, and assembling the N lenses with the similar color consistency indexes.
Assuming that the panoramic camera has N (N is more than or equal to 2) shots, the color consistency val values of all the shots are arranged in a descending order, then every N shots are taken as a group based on the sorted shots, and the sorted shots are assembled together during production.
In summary, the invention provides a panoramic camera lens classification method, which classifies and assembles lenses with similar color consistency values by calculating the color consistency values of the lenses. The method is simple and effective, can greatly reduce the difficulty of the chromatic aberration correction algorithm, and can reduce the model complexity of the chromatic aberration correction algorithm.
It is to be understood that the above-described embodiments of the present invention are merely illustrative of or explaining the principles of the invention and are not to be construed as limiting the invention. Therefore, any modification, equivalent replacement, improvement and the like made without departing from the spirit and scope of the present invention should be included in the protection scope of the present invention. Further, it is intended that the appended claims cover all such variations and modifications as fall within the scope and boundaries of the appended claims or the equivalents of such scope and boundaries.
Claims (4)
1. A panoramic camera lens classification method is characterized by comprising the following steps:
shooting images to be judged under different light sources by using each lens of the panoramic camera to be judged;
calculating the chromatic aberration offset of images shot by all the lenses under the same light source;
specifically, according to the collected images to be evaluated, the color average value and the color gain value of the image formed by each lens in different light source environments at different ring positions are counted, two-dimensional color gain discrete points are drawn according to the value from the ring position to the image center pixel point and the corresponding color gain value, and a polynomial fitting function is obtained; fitting the color gain discrete points into a straight line according to a polynomial fitting function; calculating the chromatic aberration offset of each lens under each light source according to the color gain discrete points;
calculating the color cast of the light source of each lens under different light sources; the method specifically comprises the following steps:
according to the red gain value and the blue gain value of the single lens in different annular areas, the overall red component gain value and the blue component gain value of the single lens are obtained, and the calculation formula is as follows:
Gi(r)、Gi(b) respectively representing the gain value of a red component and the gain value of a blue component in the annular area i, G (r), G (b) respectively representing the gain values of the whole red component and the blue component of a single lens, and K is the total number of the annular areas;
calculating a red component gain fitting value and a blue component gain fitting value by taking the distance of every 1 pixel as a sampling radius according to the polynomial fitting function; then, the gain ratio is obtained by dividing the gain fitting value by the overall gain value, and the calculation formula is as follows:
coei(r)＝fit_Gi(r)/G(r)
coei(b)＝fit_Gi(b)/G(b)
in the formula, fit _ Gi(r)、fit_Gi(b) Respectively representing red and blue component gain fit values of different radii i, G (r), G (b) respectively representing overall red and blue component gain values for a single lens, coei(r)、coei(b) Respectively representing the gain ratio of red components and the gain ratio of blue components with different radii i, and drawing a gain ratio straight line graph;
respectively calculating the maximum value and the minimum value of the gain ratio of the red component and the blue component at the same radius of the image shot by the M light sources of the same lens according to the gain ratio, dividing the difference between the maximum value and the minimum value by the minimum value to obtain the color deviation degrees of the light sources at different radii, and then averaging the color deviation degrees of the light sources at different radii to obtain the color deviation degree of the light source of the lens;
constructing a color consistency evaluation function according to the chromatic aberration deviation degree and the light source chromatic deviation degree, and calculating the color consistency value of each lens, wherein the color consistency evaluation function specifically comprises the following steps:
constructing a color consistency evaluation function according to the color difference deviation degree and the light source color deviation degree as follows:
val＝δ*(α1*fc(r)+β1*fc(b))+ε*(α2*fl(r)+β2*fl(b))
in the formula, fc(r)、fx(b)Respectively representing the color difference offset of the red and blue components, fl(r)、fl(b)Light source color cast representing red and blue components, respectively, α1、β1、α2、β2Delta and epsilon are weight factors;
substituting the color deviation degree and the light source color deviation degree of each lens into the formula to calculate to obtain a color consistency value val of each lens;
and sorting according to the color consistency indexes, and assembling the N lenses with similar color consistency values.
2. The method according to claim 1, wherein the lens of the panoramic camera is located in the same shooting environment and the same standard reference object;
the standard reference object is white paper, or 18% gray card, or standard white card, and the standard reference object fills the whole visual field of the lens;
the shooting environment is a standard color temperature box with the same light source;
the types of the standard light sources in the color temperature box are M, and the number of the images to be evaluated shot by each lens is M.
3. The method according to claim 1, wherein the step of calculating the color average value and the color gain value of the image formed by each lens in different light source environments at different ring positions according to the collected image to be evaluated specifically comprises:
taking rings at equal intervals by taking a central pixel point as a circle center on an image to be evaluated, dividing the image into K different annular regions, and then counting the number of red pixel points, the number of green pixel points, the number of blue pixel points, the sum of red components, the sum of green components and the sum of blue components of each annular region i to be calculated, wherein i is more than or equal to 1 and less than or equal to K;
calculating the average value of each color component in the annular region i according to the red component sum, the green component sum, the blue component sum, the red pixel number, the green pixel number and the blue pixel number in the annular region i, wherein the calculation formula is as follows:
Ai(r)＝Si(r)/x
Ai(g)＝Si(g)/y
Ai(b)＝Si(b)/z
Si(r) denotes the sum of the red components, S, in the annular region ii(g) Representing the sum of the green components, S, in the annular region ii(r) represents the sum of the blue components in the annular region i, Ai(r) represents the average of the red components in the annular region i, Ai(g) Denotes the average value of the green component, A, in the annular region ii(b) The average value of blue components in the annular area i is represented, and x, y and z respectively represent the number of red, green and blue color components in the annular area i;
the gain values of the red and blue components relative to the green component are calculated from the average value of the components in the annular region i, and the calculation formula is as follows:
Gi(r)＝Ai(g)/Ai(r)
Gi(b)＝Ai(g)/Ai(b)
Gi(r)、Gi(b) respectively representing the gain value of the red component and the gain value of the blue component in the annular region i.
4. The method according to claim 3, wherein the calculating the chromatic aberration offset of each lens under each light source according to the color gain discrete points comprises:
and respectively calculating the difference between the maximum value and the minimum value of the gain values of the red component and the blue component according to the gain discrete points of the red component and the blue component of each lens, and taking the ratio of the difference value and the minimum value of the gain values of the red component and the blue component as the chromatic aberration offset of each lens under the corresponding standard light source.
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