CN110602473A - White balance calibration method and device - Google Patents
White balance calibration method and device Download PDFInfo
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- H04N23/80—Camera processing pipelines; Components thereof
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Abstract
The invention provides a white balance calibration method and a white balance calibration device. The method comprises the following steps: acquiring a shot target image; generating a first white balance gain coefficient of the target image according to a preset white balance algorithm; determining the confidence coefficient of the first white balance gain coefficient according to the target image and/or the brightness information when the target image is shot; acquiring the color temperature of a shooting environment; determining a second white balance gain coefficient of the target image according to the color temperature; calibrating the first white balance gain coefficient according to the confidence coefficient and the second white balance gain coefficient to generate a target white balance gain coefficient of the target image; and performing white balance gain processing on the target image according to the target white balance gain coefficient. The invention can improve the accuracy and reliability of the white balance gain coefficient.
Description
Technical Field
The present invention relates to the field of image processing technologies, and in particular, to a white balance calibration method and apparatus.
Background
Currently, the white balance algorithm of mobile devices is mainly based on the grey world assumption, which assumes: for a picture with a large amount of color variation, the average value of three components of all pixels R, G and B tends to the same Gray value Gray, and based on the assumed white balance algorithm, the image containing enough Gray statistical information or the image with rich colors can be subjected to more accurate white balance processing. The white balance algorithm based on the gray world assumption may be, for example, a basic gray world algorithm (simple gray world algorithm) or an upgrade gray world algorithm (advance gray world algorithm).
However, any of the white balance algorithms based on the gray world assumption has a certain limitation, and the limitation is that when there is no gray statistical information in a picture or the gray statistical information is insufficient, or when the illumination of ambient light is low in a single color picture, the accuracy of the white balance gain data counted by the conventional white balance algorithm is low, and thus when the captured image is subjected to white balance processing by using inaccurate white balance gain data, the color of the processed image is distorted.
Therefore, in the white balance algorithm based on the gray world assumption in the related art, when the number of gray pixels of a shot picture is insufficient or a low-illuminance environment is encountered, the white balance processing result is inaccurate, and the problems of image color cast and unstable overall color expression are generally caused.
Disclosure of Invention
The embodiment of the invention provides a white balance calibration method and a white balance calibration device, which are used for solving the problems of inaccurate and unreliable white balance processing results of a white balance algorithm based on grey world assumption in the related technology.
In order to solve the technical problem, the invention is realized as follows:
in a first aspect, an embodiment of the present invention provides a white balance calibration method applied to an electronic device, where the method includes:
acquiring a shot target image;
generating a first white balance gain coefficient of the target image according to a preset white balance algorithm;
determining the confidence coefficient of the first white balance gain coefficient according to the target image and/or the brightness information when the target image is shot;
acquiring the color temperature of a shooting environment;
determining a second white balance gain coefficient of the target image according to the color temperature;
calibrating the first white balance gain coefficient according to the confidence coefficient and the second white balance gain coefficient to generate a target white balance gain coefficient of the target image;
and performing white balance gain processing on the target image according to the target white balance gain coefficient.
In a second aspect, an embodiment of the present invention further provides a white balance calibration apparatus, where the apparatus includes:
the first acquisition module is used for acquiring a shot target image;
the generating module is used for generating a first white balance gain coefficient of the target image according to a preset white balance algorithm;
the first determining module is used for determining the confidence coefficient of the first white balance gain coefficient according to the target image and/or the brightness information when the target image is shot;
the second acquisition module is used for acquiring the color temperature of the shooting environment;
the second determining module is used for determining a second white balance gain coefficient of the target image according to the color temperature;
the calibration module is used for calibrating the first white balance gain coefficient according to the confidence coefficient and the second white balance gain coefficient to generate a target white balance gain coefficient of the target image;
and the processing module is used for carrying out white balance gain processing on the target image according to the target white balance gain coefficient.
In a third aspect, an embodiment of the present invention further provides an electronic device, including: a memory, a processor and a computer program stored on the memory and executable on the processor, the computer program, when executed by the processor, implementing the steps of the white balance calibration method.
In a fourth aspect, the embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps of the white balance calibration method.
In the embodiment of the invention, the confidence coefficient of the first white balance gain coefficient is determined by utilizing the brightness information when the target image is shot and/or the shot target image, the confidence coefficient can express the reliability of the first white balance gain coefficient of the target image generated according to the preset white balance algorithm, the higher the confidence coefficient is, the higher the reliability of the first white balance gain coefficient is, the second white balance gain coefficient of the target image is determined according to the color temperature of the shooting environment, the first white balance gain coefficient is calibrated according to the confidence coefficient of the first white balance gain coefficient and the second white balance gain coefficient, so that the obtained target white balance gain coefficient is matched with the brightness condition of the shooting environment and/or the actual image parameter of the target image, and the accuracy and the reliability of the finally determined target white balance gain coefficient aiming at the target image are improved, then, the target white balance gain coefficient is used to perform white balance gain processing on the target image, so that the overall color expression of the processed image is stable.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments of the present invention will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without inventive labor.
FIG. 1 is a flow chart of a white balance calibration method of one embodiment of the present invention;
FIG. 2 is a schematic diagram of a chromaticity diagram coordinate system according to one embodiment of the invention;
FIG. 3 is a block diagram of a white balance calibration apparatus according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a hardware structure of an electronic device according to an embodiment of 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 some, not all, embodiments of the present invention. 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.
Referring to fig. 1, a flowchart of a white balance calibration method according to an embodiment of the present invention is shown, and is applied to an electronic device, where the method specifically includes the following steps:
step 101, acquiring a shot target image;
optionally, a camera of the electronic device may perform image shooting, and may generate a shot target image, in this step, the electronic device may acquire the target image shot by the camera; in addition, a target image captured by other electronic devices may also be acquired, which is not specifically limited in the embodiment of the present invention.
102, generating a first white balance gain coefficient of the target image according to a preset white balance algorithm;
the preset white balance algorithm may be a white balance algorithm based on a gray world assumption in the conventional technology, and after the current electronic device shoots a shooting object, the current electronic device may automatically calculate a white balance gain value for the shot target image based on the white balance algorithm based on the gray world assumption. The white balance algorithm is specifically used, and the embodiment of the present invention is not limited in this respect. In this step, a first white balance gain coefficient for the target image corresponding to the automatic white balance processing may be obtained.
The white balance gain coefficients (including the first white balance gain coefficient, the second white balance gain coefficient, and the target white balance gain coefficient) in the present invention may include white balance three-channel gain data, such as a red primary gain value rgain, a green primary gain value ggain, and a blue primary gain value bgain.
For example, the first white balance gain coefficients include r1gain, g1gain, and b1 gain.
The electronic device may include an automatic white balance calculation module, and the target image acquired in step 101 may be sent to the automatic white balance calculation module to obtain r1gain, g1gain, and b1 gain.
103, determining the confidence coefficient of the first white balance gain coefficient according to the target image and/or the brightness information when the target image is shot;
the brightness information is brightness information of a shooting environment when the target image is shot.
The brightness information of the shooting environment may be directly obtained by a camera of the electronic device, or may be sent to the electronic device by another electronic device, or may be input by a user, and the like.
The present invention does not limit the execution sequence between the step of acquiring the luminance information and the step 101.
The confidence T of the present invention is used to represent the reliability of the first white balance gain coefficient obtained in step 102, where the higher the value of the confidence T is, the higher the reliability of the first white balance gain coefficient is, and the lower the value of the confidence T is, the lower the reliability of the first white balance gain coefficient is, and T is greater than or equal to 0 and less than or equal to 1.
Since the accuracy and reliability of the first white balance gain coefficient generated based on the preset white balance algorithm are affected by the number of gray pixels of the captured image and the ambient illuminance, in this step, the confidence of the first white balance gain coefficient may be determined according to the brightness information of the capturing environment where the target image is captured and/or the target image.
The target image can reflect the number of gray pixels of the shot picture, whether the picture color is rich or not and other characteristics, so that the confidence coefficient of the first white balance gain coefficient can be flexibly and accurately determined according to the brightness condition of the actual shooting environment and the pixel information of the shot target image.
Optionally, the electronic device may include a confidence calculation module for performing step 103.
Step 104, acquiring the color temperature of the shooting environment;
wherein step 104 is performed after step 101.
The color temperature is a color temperature of a shooting environment in which the target image is shot.
Optionally, the electronic device has a color temperature sensor, and color temperature data of the shooting environment can be acquired by using the color temperature sensor. Of course, the electronic device may also obtain the color temperature by other methods, for example, the color temperature is detected by other electronic devices and then sent to the electronic device, or input by a user, and the embodiment of the present invention is not limited in this respect.
Alternatively, in one embodiment, a color temperature sensor of the electronic device may be utilized to directly read a color temperature value of light of an environment (i.e., a shooting environment) in which the primary electronic device is located.
Alternatively, in another embodiment, in order to ensure the accuracy and stability of the obtained color temperature values, the color temperature sensor may be used to continuously read the color temperature values of the light of the shooting environment for a plurality of times within a certain time period, and perform an average processing on the plurality of color temperature values, and the average color temperature value is used as the color temperature data of the shooting environment.
Optionally, the unit of the color temperature data read in this step is K.
Optionally, before step 101, the method according to the embodiment of the present invention further includes: and generating a mapping table of color temperature values and white balance gain coefficients by pre-calibrating the color temperature sensor.
The mapping table is a one-to-one mapping table.
Therefore, the color temperature read by the color temperature sensor can be converted into the corresponding white balance gain coefficient in real time through the mapping table. That is, it is possible to determine how much white balance compensation should be performed on the target image at a certain color temperature using the mapping table.
The execution sequence among step 102, step 103, and step 104 is not limited in the present invention.
Step 105, determining a second white balance gain coefficient of the target image according to the color temperature;
the second white balance gain coefficient is determined according to the color temperature of the shooting environment.
For example, the second white balance gain factors include r2gain, g2gain, b2 gain.
Alternatively, in performing step 105, this may be accomplished by the method of the following embodiment or other known or future developed methods for determining white balance compensation using color temperature.
Optionally, in an embodiment, when step 105 is executed, a second white balance gain coefficient corresponding to the color temperature in step 104 may be obtained according to a preset mapping table of color temperature values and white balance gain coefficients (for example, the mapping table generated by pre-calibrating the color temperature sensor); wherein the mapping table is generated by pre-calibrating the color temperature sensor.
In the embodiment of the invention, the color temperature of the light of the shooting environment is referred to, and a white balance compensation value corresponding to the color temperature, namely the second white balance gain coefficient, is calculated for the shot target image, so that the first white balance gain coefficient can be favorably calibrated.
Step 106, calibrating the first white balance gain coefficient according to the confidence coefficient and the second white balance gain coefficient to generate a target white balance gain coefficient of the target image;
optionally, two confidence thresholds are preset, namely a first confidence threshold T1 and a second confidence threshold T2, wherein T1> T2.
Optionally, the electronic device may include a white balance calibration module, configured to perform step 106, where the white balance calibration module may include three sub-modules, namely, a white balance calibration module 1, a white balance calibration module 2, and a white balance calibration module 3, according to the difference in the reliability of the first white balance gain coefficient.
Alternatively, when step 106 is executed, this may be achieved by:
when the confidence coefficient is larger than a first confidence coefficient threshold value, determining the first white balance gain coefficient as a target white balance gain coefficient of the target image;
e.g., T > T1, indicating that the white balance gain automatically calculated using a white balance algorithm based on the gray world assumption is sufficiently reliable and reliable, the white balance calibration module 1 is executed for determining the first white balance gain coefficient as the target white balance gain coefficient (including Rgainfinal, Ggainfinal, Bgainfinal) of the target image.
Wherein, Rgainfinal ═ r1gain, Ggainfinal ═ g1gain, and Bgainfinal ═ b1 gain.
That is, the brightness of the shooting environment is sufficiently high, or the number of gray pixels of the target image is sufficiently large, so that the first white balance gain coefficient automatically calculated by the white balance algorithm based on the gray world assumption is accurate and reliable.
When the confidence coefficient is greater than or equal to a second confidence coefficient threshold and less than or equal to the first confidence coefficient threshold, performing weighted calculation on the first white balance gain coefficient and the second white balance gain coefficient to generate a target white balance gain coefficient of the target image;
for example, T2 ≦ T1, which indicates that there is a certain deviation in the first white balance gain coefficient automatically calculated by the white balance algorithm based on the gray world assumption, and a more accurate target white balance gain coefficient needs to be obtained in combination with the color temperature, and therefore, the white balance calibration module 2 is executed for performing weighted calculation on the first white balance gain coefficient and the second white balance gain coefficient to generate the target white balance gain coefficients (including Rgainfinal, Ggainfinal, and Bgainfinal) of the target image.
The values of the weight w1 of the first white balance gain coefficient and the weight w2 of the second white balance gain coefficient may be manually configured in advance, or the values of w1 and w2 may be automatically set by the electronic device according to the position of T in the [ T2, T1] interval.
Wherein, Rgainfinal ═ r1gain ═ w1+ r2gain × w2, Ggainfinal ═ g1gain × w1+ g2gain × w2, and Bgainfinal ═ b1gain × w1+ b2gain × w 2.
And when the confidence coefficient is smaller than the second confidence coefficient threshold value, determining the second white balance gain coefficient as a target white balance gain coefficient of the target image.
E.g., T < T2, indicating that the white balance gain automatically calculated using a white balance algorithm based on the gray world assumption is not reliable, the white balance calibration module 3 is executed for determining the second white balance gain factor as the target white balance gain factor (including Rgainfinal, Ggainfinal, Bgainfinal) of the target image.
Wherein, Rgainfinal ═ r2gain, Ggainfinal ═ g2gain, and Bgainfinal ═ b2 gain.
That is, it is considered that the first white balance gain coefficient automatically calculated by the white balance algorithm based on the gray world assumption is inaccurate and unreliable because the luminance of the shooting environment is low or the number of gray pixels of the target image is small. The target white balance gain coefficient for white balance compensation of the target image is entirely dependent on the second white balance gain coefficient obtained based on the color temperature.
In the embodiment of the present invention, it may be determined whether the first white balance gain coefficient automatically calculated by the white balance algorithm based on the gray world assumption is accurate and reliable according to the confidence level of the first white balance gain coefficient, and if the first white balance gain coefficient is not reliable and inaccurate, the second white balance gain coefficient obtained by directly adopting the color temperature is used as the white balance compensation for the target image; when the image is reliable and accurate, a first white balance gain coefficient automatically calculated by a white balance algorithm based on gray world assumption is directly adopted as white balance compensation for the target image; when a certain deviation exists, the first white balance gain coefficient and the second white balance gain coefficient are subjected to weighted summation to obtain white balance compensation for the target image, so that the target white balance gain coefficient generated by the embodiment of the invention is a reliable, accurate and stable white balance gain coefficient for the target image.
And 107, performing white balance gain processing on the target image according to the target white balance gain coefficient.
Then, after the white balance gain processing is performed on the shot target image by using the target white balance gain coefficient, the color difference between the processed image and the actual shot object can be ensured to be low, and the situations of color cast of the image shot by the camera and unstable overall color expression are avoided.
For example, in the related art, when a white balance algorithm based on a gray world assumption is used alone to calculate and generate a white balance gain value for a shot target image, if the illuminance of a shooting environment is normal and not very dark, or the number of gray pixels of a shot picture is sufficient, or the color of the shot picture is rich, the white balance gain value is relatively accurate, the color reduction degree of the target image processed by using the white balance gain is high, and the color difference between the color of the image and the actual color of the object is small. However, if the illuminance of the shooting environment is low, or the number of gray pixels of the shot picture is small, or the color of the shot picture is single, the white balance gain value is not accurate enough, and the color reduction degree of the target image processed by the white balance gain is low, so that the color difference between the color of the image and the actual color of the object is large. Then, the white balance gain value calculated and generated by using the white balance algorithm based on the gray world assumption alone in the related art is sometimes accurate and sometimes not accurate enough for the shot target image, so that the overall color representation of the target image processed by using the white balance gain is not stable enough, sometimes the color is true, and sometimes the color is distorted.
However, the above technical solution of the embodiment of the present invention may flexibly determine whether the first white balance gain coefficient obtained each time is accurate according to the confidence of the first white balance gain coefficient, and flexibly adopt different calibration schemes to calibrate the white balance gain, so that the overall color representation of the image processed by the target white balance gain coefficient obtained by the method of the embodiment of the present invention is relatively stable.
In the embodiment of the invention, the confidence coefficient of the first white balance gain coefficient is determined by utilizing the brightness information when the target image is shot and/or the shot target image, the confidence coefficient can express the reliability of the first white balance gain coefficient of the target image generated according to the preset white balance algorithm, the higher the confidence coefficient is, the higher the reliability of the first white balance gain coefficient is, the second white balance gain coefficient of the target image is determined according to the color temperature of the shooting environment, the first white balance gain coefficient is calibrated according to the confidence coefficient of the first white balance gain coefficient and the second white balance gain coefficient, so that the obtained target white balance gain coefficient is matched with the brightness condition of the shooting environment and/or the actual image parameter of the target image, and the accuracy and the reliability of the finally determined target white balance gain coefficient aiming at the target image are improved, then, the target white balance gain coefficient is used to perform white balance gain processing on the target image, so that the overall color expression of the processed image is stable.
Optionally, in an embodiment, when performing step 103, specifically when determining the confidence of the first white balance gain coefficient according to the target image, the following may be implemented:
s201, determining gray pixels meeting preset conditions in the target image;
in order to solve the above problem, in the embodiment of the present invention, a gray pixel that meets a preset condition in the target image may be identified.
The gray pixels meeting the preset condition are available gray pixels for calculating the confidence degree, and can be used as a basis for calculating the value of the confidence degree.
Alternatively, the preset condition may include a chromaticity condition, or, further include a luminance condition.
Optionally, in an embodiment, for example, the preset condition includes a chromaticity condition, when S201 is executed, a pixel point of the target image whose color coordinate is in a preset gray area in the chromaticity diagram may be determined as a gray pixel that satisfies the preset condition.
The color coordinate (chromaticity coordinate) is a coordinate of a color, and is also called a color system.
Each pixel point has a color coordinate (Cr, Cb), and the color coordinate accurately represents the color of the pixel point. Because each pixel point in the target image has a unique color, each pixel point has a unique color coordinate.
In addition, the color coordinates are coordinates in a chromaticity diagram, the chromaticity diagram corresponds to a coordinate system including a plurality of colors, and each coordinate point corresponds to one color, for example, in the coordinate system of the chromaticity diagram shown in fig. 2, the horizontal axis is cr, and the vertical axis is cb.
The embodiment of the present invention may identify, in advance, the coordinate points corresponding to the gray color or the color close to the gray color in the coordinate system shown in fig. 2, so as to determine the 4 function curves shown in fig. 2, wherein values of 8 coefficients (m1, m2, m3, m4, c1, c2, c3, and c4) in the four function curves are determined in advance through multiple times of debugging.
Wherein, 4 function curves are respectively:
Cb＝m1Cr+c1；
Cb＝m3Cr+c3；
Cr＝m2Cb+c2；
Cr＝m4Cb+c4。
as shown in fig. 2, the color coordinates in the rectangular region formed by the four function curves in the coordinate system are all gray or color coordinates close to gray, and then the pixel points in the target image having the color coordinates in the rectangular region are all gray pixel points that satisfy the preset condition in this embodiment.
In specific implementation, the pixel point with the color coordinate meeting the chromaticity condition can be determined as the gray pixel point meeting the preset condition by judging which pixel points in the target image have the color coordinates (cb, cr) meeting the following chromaticity condition.
The chromaticity condition is as follows: m3Cr + c3 Cb is not less than m1Cr + c1, and m2Cb + c2 Cr is not less than m4Cb + c4
Therefore, in this step, the pixel point of the gray pixel area (gray pixel area) whose color coordinate is in the chromaticity diagram coordinate system of fig. 2 in the target image may be determined as the gray pixel that satisfies the preset condition.
In the embodiment of the invention, the gray pixel points with the color coordinates meeting the gray condition in the target image are found out, and the ratio of the number of the gray pixel points to the total number of the pixel points of the target image is used as the value of the confidence coefficient, so that the confidence coefficient refers to the pixel proportion of the gray pixel points in the shot target image in the target image, when the number of the gray pixel points of the target image is less and the proportion is lower, the confidence coefficient is lower, when the confidence coefficient is used for correcting the first white balance gain coefficient, the reliability of the first white balance gain coefficient can be known based on the value of the confidence coefficient, and a reasonable correction scheme is selected.
Optionally, in another embodiment, the preset condition may include a luminance condition and a chrominance condition, and then when S201 is executed, the first pixel point set of the target image whose color coordinates are in a preset gray area in a chrominance map may be identified (for a specific method, refer to the above embodiment, which is not described herein again); identifying a second pixel point set of which the brightness value is within a preset brightness interval in the target image (wherein each pixel point in the target image has a brightness value, and then the white balance gain calculated by a white balance algorithm based on the gray world assumption on too dark or too bright pixel points is not accurate enough, so that the brightness value Y of each pixel point in the target image needs to be referred to when calculating the value of confidence, wherein Y meets the brightness condition that when Y is less than or equal to Ymin and less than or equal to Ymax, the pixel point is identified into the second pixel set); and determining the pixel points in the intersection of the first pixel point set and the second pixel point set as gray pixels meeting preset conditions.
That is to say, the gray pixels determined in this embodiment for calculating the confidence are a set of pixels that satisfy both the luminance condition and the chrominance condition. Then, when the confidence is calculated by using the gray pixels determined by the embodiment of the present invention, the accuracy of the determined confidence can be improved.
The first pixel set and the second pixel set respectively comprise a plurality of pixel points.
The execution sequence of identifying the first pixel point set and the second pixel point set is not limited.
S202, acquiring the number of the gray pixels;
s203, determining the ratio of the number of the gray pixels to the total number of the pixels of the target image as the confidence of the first white balance gain coefficient.
In the embodiment of the present invention, gray pixels available for calculating the confidence are determined by referring to the chromaticity of a pixel point in a target image or further referring to the luminance of the pixel point, and the ratio of the number of the gray pixels to the total number of pixels of the target image is determined as the confidence of the first white balance gain coefficient. Then when the number of gray pixels of the target image is small and the ratio is low, the confidence is low, and when the first white balance gain coefficient is corrected by using the confidence, the reliability of the first white balance gain coefficient can be known based on the degree of the confidence, and a reasonable correction scheme can be selected.
Optionally, in an embodiment, when step 103 is executed, specifically when determining the confidence of the first white balance gain coefficient according to the brightness information when the target image is captured, the following may be implemented:
s301, acquiring a maximum brightness value which can be identified by a camera of the electronic equipment;
s302, determining the confidence coefficient of the first white balance gain coefficient according to the maximum brightness value and the brightness information of the shooting environment when the target image is shot.
The method of the embodiment of the invention can determine the confidence coefficient of the first white balance gain coefficient by using the maximum brightness value and the brightness information, so that the confidence coefficient calculated by the embodiment of the invention refers to the light brightness condition of the shooting scene, the confidence coefficient can be positively correlated with the reliability of the first white balance gain coefficient, and the accuracy of the confidence coefficient is improved.
Optionally, in an embodiment, in executing S302, the first luminance threshold Ea may be determined according to the maximum luminance value Emax (for example, a result of a preset proportion of Emax is Ea., for example, the preset proportion is 50%, Emax ═ 500, Ea ═ 250); when the brightness information m of the shooting environment is smaller than or equal to the first brightness threshold Ea, the confidence coefficient is 1; when the luminance information m of the shooting environment is greater than the first luminance threshold Ea, the confidence is (Emax-m)/(Emax-Ea), for example, m is 300, and T is (500-.
Alternatively, in another embodiment, when S302 is executed, the ratio of the luminance information m of the shooting environment to the maximum luminance value Emax may be determined as the confidence, for example, T ═ m/Emax.
Optionally, in an embodiment, when step 103 is executed, specifically when the confidence of the first white balance gain coefficient is determined according to the target image and the brightness information when the target image is captured, a first confidence Ta determined according to the brightness information when the target image is captured (for example, the confidence obtained through the above S301 to S302) may be obtained; acquiring a second confidence Tb (for example, the confidence obtained through S201 to S203) determined according to the target image; and performing weighted calculation on the first confidence coefficient and the second confidence coefficient to generate a confidence coefficient T of the first white balance gain coefficient.
If the confidence weight corresponding to the luminance information of the shooting environment is w3 and the confidence weight corresponding to the target image is w4, then T ═ Ta × w3+ Tb × w 4.
The invention does not limit the execution sequence between the two steps of obtaining the first confidence coefficient and obtaining the second confidence coefficient.
In the embodiment of the invention, the confidence coefficient of the first white balance gain coefficient can be calculated by comprehensively referring to the brightness information of the shooting environment and the shot target image, so that the accuracy of the confidence coefficient is improved, the accuracy of the calculated target white balance gain coefficient is further ensured, and the calibration accuracy of the first white balance gain coefficient calculated by adopting a white balance algorithm based on the gray world assumption is improved.
Referring to fig. 3, a block diagram of a white balance calibration apparatus according to an embodiment of the present invention is shown. The white balance calibration device of the embodiment of the invention can realize the details of the white balance calibration method realized by the electronic equipment in the embodiment and achieve the same effect. The white balance calibration apparatus shown in fig. 3 includes:
a first acquisition module 31 for acquiring a photographed target image;
a generating module 32, configured to generate a first white balance gain coefficient of the target image according to a preset white balance algorithm;
a first determining module 33, configured to determine a confidence of the first white balance gain coefficient according to the target image and/or luminance information obtained when the target image is captured;
a second obtaining module 34, configured to obtain a color temperature of the shooting environment;
a second determining module 35, configured to determine a second white balance gain coefficient of the target image according to the color temperature;
a calibration module 36, configured to calibrate the first white balance gain coefficient according to the confidence and the second white balance gain coefficient, and generate a target white balance gain coefficient of the target image;
and the processing module 37 is configured to perform white balance gain processing on the target image according to the target white balance gain coefficient.
Optionally, the first determining module 33 includes:
the first determining submodule is used for determining gray pixels meeting preset conditions in the target image;
the first obtaining submodule is used for obtaining the number of the gray pixels;
and the second determining submodule is used for determining the ratio of the number of the gray pixels to the total number of the pixels of the target image as the confidence coefficient of the first white balance gain coefficient.
Optionally, the first determining sub-module includes:
and the first determining unit is used for determining the pixel points of the color coordinates in the target image in a preset gray area in the chromaticity diagram as gray pixels meeting preset conditions.
Optionally, the first determining sub-module includes:
the first identification unit is used for identifying a first pixel point set of which the color coordinates are located in a preset gray area in a chromaticity diagram in the target image;
the second identification unit is used for identifying a second pixel point set of which the brightness value is within a preset brightness interval in the target image;
and the second determining unit is used for determining the pixel points in the intersection of the first pixel point set and the second pixel point set as the gray pixels meeting the preset conditions.
Optionally, the first determining module 33 includes:
the second obtaining submodule is used for obtaining the maximum brightness value which can be identified by a camera of the electronic equipment;
and the third determining submodule is used for determining the confidence coefficient of the first white balance gain coefficient according to the maximum brightness value and the brightness information of the shooting environment when the target image is shot.
Optionally, the first determining module 33 includes:
the third obtaining submodule is used for obtaining a first confidence coefficient determined according to the brightness information when the target image is shot;
the fourth obtaining submodule is used for obtaining a second confidence coefficient determined according to the target image;
and the calculation submodule is used for performing weighted calculation on the first confidence coefficient and the second confidence coefficient to generate the confidence coefficient of the first white balance gain coefficient.
Optionally, the electronic device has a color temperature sensor, and the second determination module 35 includes:
the fifth obtaining submodule is used for obtaining a second white balance gain coefficient corresponding to the color temperature data according to a preset mapping table of the color temperature value and the white balance gain coefficient; the mapping table is generated by pre-calibrating the color temperature sensor.
Optionally, the calibration module 36 includes:
a fourth determining submodule, configured to determine the first white balance gain coefficient as a target white balance gain coefficient of the target image when the confidence is greater than a first confidence threshold;
the generation submodule is used for performing weighted calculation on the first white balance gain coefficient and the second white balance gain coefficient when the confidence coefficient is greater than or equal to a second confidence coefficient threshold and is less than or equal to the first confidence coefficient threshold so as to generate a target white balance gain coefficient of the target image;
a fifth determining sub-module, configured to determine the second white balance gain coefficient as a target white balance gain coefficient of the target image when the confidence is smaller than the second confidence threshold;
wherein the second confidence threshold is less than the first confidence threshold.
The white balance calibration device provided by the embodiment of the invention can realize each process realized by the electronic equipment in the method embodiment, and is not described again in order to avoid repetition.
In the embodiment of the invention, the confidence coefficient of the first white balance gain coefficient is determined by utilizing the brightness information when the target image is shot and/or the shot target image, the confidence coefficient can express the reliability of the first white balance gain coefficient of the target image generated according to the preset white balance algorithm, the higher the confidence coefficient is, the higher the reliability of the first white balance gain coefficient is, the second white balance gain coefficient of the target image is determined according to the color temperature of the shooting environment, the first white balance gain coefficient is calibrated according to the confidence coefficient of the first white balance gain coefficient and the second white balance gain coefficient, so that the obtained target white balance gain coefficient is matched with the brightness condition of the shooting environment and/or the actual image parameter of the target image, and the accuracy and the reliability of the finally determined target white balance gain coefficient aiming at the target image are improved, then, the target white balance gain coefficient is used to perform white balance gain processing on the target image, so that the overall color expression of the processed image is stable.
Figure 4 is a schematic diagram of a hardware configuration of an electronic device implementing various embodiments of the invention,
the electronic device 400 includes, but is not limited to: radio frequency unit 401, network module 402, audio output unit 403, input unit 404, sensor 405, display unit 406, user input unit 407, interface unit 408, memory 409, processor 410, and power supply 411, and the like. Those skilled in the art will appreciate that the electronic device configuration shown in fig. 4 does not constitute a limitation of the electronic device, and that the electronic device may include more or fewer components than shown, or some components may be combined, or a different arrangement of components. In the embodiment of the present invention, the electronic device includes, but is not limited to, a mobile phone, a tablet computer, a notebook computer, a palm computer, a vehicle-mounted terminal, a wearable device, a pedometer, and the like.
The processor 410 acquires a target image shot by the camera; generating a first white balance gain coefficient of the target image according to a preset white balance algorithm; determining the confidence coefficient of the first white balance gain coefficient according to the target image and/or the brightness information when the target image is shot; acquiring the color temperature of a shooting environment; determining a second white balance gain coefficient of the target image according to the color temperature; calibrating the first white balance gain coefficient according to the confidence coefficient and the second white balance gain coefficient to generate a target white balance gain coefficient of the target image; and performing white balance gain processing on the target image according to the target white balance gain coefficient.
In the embodiment of the invention, the confidence coefficient of the first white balance gain coefficient is determined by utilizing the brightness information when the target image is shot and/or the shot target image, the confidence coefficient can express the reliability of the first white balance gain coefficient of the target image generated according to the preset white balance algorithm, the higher the confidence coefficient is, the higher the reliability of the first white balance gain coefficient is, the second white balance gain coefficient of the target image is determined according to the color temperature of the shooting environment, the first white balance gain coefficient is calibrated according to the confidence coefficient of the first white balance gain coefficient and the second white balance gain coefficient, so that the obtained target white balance gain coefficient is matched with the brightness condition of the shooting environment and/or the actual image parameter of the target image, and the accuracy and the reliability of the finally determined target white balance gain coefficient aiming at the target image are improved, then, the target white balance gain coefficient is used to perform white balance gain processing on the target image, so that the overall color expression of the processed image is stable.
It should be understood that, in the embodiment of the present invention, the radio frequency unit 401 may be used for receiving and sending signals during a message sending and receiving process or a call process, and specifically, receives downlink data from a base station and then processes the received downlink data to the processor 410; in addition, the uplink data is transmitted to the base station. Typically, radio unit 401 includes, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier, a duplexer, and the like. Further, the radio unit 401 can also communicate with a network and other devices through a wireless communication system.
The electronic device provides wireless broadband internet access to the user via the network module 402, such as assisting the user in sending and receiving e-mails, browsing web pages, and accessing streaming media.
The audio output unit 403 may convert audio data received by the radio frequency unit 401 or the network module 402 or stored in the memory 409 into an audio signal and output as sound. Also, the audio output unit 403 may also provide audio output related to a specific function performed by the electronic apparatus 400 (e.g., a call signal reception sound, a message reception sound, etc.). The audio output unit 403 includes a speaker, a buzzer, a receiver, and the like.
The input unit 404 is used to receive audio or video signals. The input Unit 404 may include a Graphics Processing Unit (GPU) 4041 and a microphone 4042, and the Graphics processor 4041 processes a target image of a still picture or video obtained by an image capturing apparatus (e.g., a camera) in a video capturing mode or an image capturing mode. The processed image frames may be displayed on the display unit 406. The image frames processed by the graphic processor 4041 may be stored in the memory 409 (or other storage medium) or transmitted via the radio frequency unit 401 or the network module 402. The microphone 4042 may receive sound, and may be capable of processing such sound into audio data. The processed audio data may be converted into a format output transmittable to a mobile communication base station via the radio frequency unit 401 in case of the phone call mode.
The electronic device 400 also includes at least one sensor 405, such as light sensors, motion sensors, and other sensors. Specifically, the light sensor includes an ambient light sensor that adjusts the brightness of the display panel 4061 according to the brightness of ambient light, and a proximity sensor that turns off the display panel 4061 and/or the backlight when the electronic apparatus 400 is moved to the ear. As one type of motion sensor, an accelerometer sensor can detect the magnitude of acceleration in each direction (generally three axes), detect the magnitude and direction of gravity when stationary, and can be used to identify the posture of an electronic device (such as horizontal and vertical screen switching, related games, magnetometer posture calibration), and vibration identification related functions (such as pedometer, tapping); the sensors 405 may also include a fingerprint sensor, a pressure sensor, an iris sensor, a molecular sensor, a gyroscope, a barometer, a hygrometer, a thermometer, an infrared sensor, etc., which will not be described in detail herein.
The display unit 406 is used to display information input by the user or information provided to the user. The Display unit 406 may include a Display panel 4061, and the Display panel 4061 may be configured in the form of a Liquid Crystal Display (LCD), an Organic Light-Emitting Diode (OLED), or the like.
The user input unit 407 may be used to receive input numeric or character information and generate key signal inputs related to user settings and function control of the electronic device. Specifically, the user input unit 407 includes a touch panel 4071 and other input devices 4072. Touch panel 4071, also referred to as a touch screen, may collect touch operations by a user on or near it (e.g., operations by a user on or near touch panel 4071 using a finger, a stylus, or any suitable object or attachment). The touch panel 4071 may include two parts, a touch detection device and a touch controller. The touch detection device detects the touch direction of a user, detects a signal brought by touch operation and transmits the signal to the touch controller; the touch controller receives touch information from the touch sensing device, converts the touch information into touch point coordinates, sends the touch point coordinates to the processor 410, receives a command from the processor 410, and executes the command. In addition, the touch panel 4071 can be implemented by using various types such as a resistive type, a capacitive type, an infrared ray, and a surface acoustic wave. In addition to the touch panel 4071, the user input unit 407 may include other input devices 4072. Specifically, the other input devices 4072 may include, but are not limited to, a physical keyboard, function keys (such as volume control keys, switch keys, etc.), a track ball, a mouse, and a joystick, which are not described herein again.
Further, the touch panel 4071 can be overlaid on the display panel 4061, and when the touch panel 4071 detects a touch operation thereon or nearby, the touch operation is transmitted to the processor 410 to determine the type of the touch event, and then the processor 410 provides a corresponding visual output on the display panel 4061 according to the type of the touch event. Although in fig. 4, the touch panel 4071 and the display panel 4061 are two independent components to implement the input and output functions of the electronic device, in some embodiments, the touch panel 4071 and the display panel 4061 may be integrated to implement the input and output functions of the electronic device, and the implementation is not limited herein.
The interface unit 408 is an interface for connecting an external device to the electronic apparatus 400. For example, the external device may include a wired or wireless headset port, an external power supply (or battery charger) port, a wired or wireless data port, a memory card port, a port for connecting a device having an identification module, an audio input/output (I/O) port, a video I/O port, an earphone port, and the like. The interface unit 408 may be used to receive input (e.g., data information, power, etc.) from an external device and transmit the received input to one or more elements within the electronic apparatus 400 or may be used to transmit data between the electronic apparatus 400 and an external device.
The memory 409 may be used to store software programs as well as various data. The memory 409 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone, and the like. Further, the memory 409 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device.
The processor 410 is a control center of the electronic device, connects various parts of the entire electronic device using various interfaces and lines, performs various functions of the electronic device and processes data by operating or executing software programs and/or modules stored in the memory 409 and calling data stored in the memory 409, thereby performing overall monitoring of the electronic device. Processor 410 may include one or more processing units; preferably, the processor 410 may integrate an application processor, which mainly handles operating systems, user interfaces, application programs, etc., and a modem processor, which mainly handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 410.
The electronic device 400 may further include a power supply 411 (e.g., a battery) for supplying power to various components, and preferably, the power supply 411 may be logically connected to the processor 410 through a power management system, so as to implement functions of managing charging, discharging, and power consumption through the power management system.
In addition, the electronic device 400 includes some functional modules that are not shown, and are not described in detail herein.
Preferably, an embodiment of the present invention further provides an electronic device, which includes a processor 410, a memory 409, and a computer program that is stored in the memory 409 and can be run on the processor 410, and when being executed by the processor 410, the computer program implements each process of the foregoing white balance calibration method embodiment, and can achieve the same technical effect, and in order to avoid repetition, details are not described here again.
An embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program implements each process of the white balance calibration method, and can achieve the same technical effect, and in order to avoid repetition, details are not repeated here. The computer-readable storage medium may be a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
While the present invention has been described with reference to the embodiments shown in the drawings, the present invention is not limited to the embodiments, which are illustrative and not restrictive, and it will be apparent to those skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (10)
1. A white balance calibration method applied to electronic equipment is characterized by comprising the following steps:
acquiring a shot target image;
generating a first white balance gain coefficient of the target image according to a preset white balance algorithm;
determining the confidence coefficient of the first white balance gain coefficient according to the target image and/or the brightness information when the target image is shot;
acquiring the color temperature of a shooting environment;
determining a second white balance gain coefficient of the target image according to the color temperature;
calibrating the first white balance gain coefficient according to the confidence coefficient and the second white balance gain coefficient to generate a target white balance gain coefficient of the target image;
and performing white balance gain processing on the target image according to the target white balance gain coefficient.
2. The method of claim 1, wherein determining a confidence level for the first white balance gain factor based on the target image comprises:
determining gray pixels meeting preset conditions in the target image;
acquiring the number of the gray pixels;
determining a ratio of the number of gray pixels to the total number of pixels of the target image as a confidence of the first white balance gain coefficient.
3. The method of claim 2, wherein the determining gray pixels in the target image that satisfy a preset condition comprises:
identifying a first pixel point set of which the color coordinates are in a preset gray area in a chromaticity diagram in the target image;
identifying a second pixel point set of which the brightness value is within a preset brightness interval in the target image;
and determining the pixel points in the intersection of the first pixel point set and the second pixel point set as gray pixels meeting preset conditions.
4. The method of claim 1, wherein determining the confidence level of the first white balance gain factor based on brightness information when the target image was captured comprises:
acquiring a maximum brightness value which can be identified by a camera of the electronic equipment;
and determining the confidence coefficient of the first white balance gain coefficient according to the maximum brightness value and the brightness information of the shooting environment when the target image is shot.
5. The method of claim 1, wherein the calibrating the first white balance gain factor to generate a target white balance gain factor for the target image based on the confidence level and the second white balance gain factor comprises:
when the confidence coefficient is larger than a first confidence coefficient threshold value, determining the first white balance gain coefficient as a target white balance gain coefficient of the target image;
when the confidence coefficient is greater than or equal to a second confidence coefficient threshold and less than or equal to the first confidence coefficient threshold, performing weighted calculation on the first white balance gain coefficient and the second white balance gain coefficient to generate a target white balance gain coefficient of the target image;
when the confidence coefficient is smaller than the second confidence coefficient threshold value, determining the second white balance gain coefficient as a target white balance gain coefficient of the target image;
wherein the second confidence threshold is less than the first confidence threshold.
6. A white balance calibration apparatus, characterized in that the white balance calibration apparatus comprises:
the first acquisition module is used for acquiring a shot target image;
the generating module is used for generating a first white balance gain coefficient of the target image according to a preset white balance algorithm;
the first determining module is used for determining the confidence coefficient of the first white balance gain coefficient according to the target image and/or the brightness information when the target image is shot;
the second acquisition module is used for acquiring the color temperature of the shooting environment;
the second determining module is used for determining a second white balance gain coefficient of the target image according to the color temperature;
the calibration module is used for calibrating the first white balance gain coefficient according to the confidence coefficient and the second white balance gain coefficient to generate a target white balance gain coefficient of the target image;
and the processing module is used for carrying out white balance gain processing on the target image according to the target white balance gain coefficient.
7. The apparatus of claim 6, wherein the first determining module comprises:
the first determining submodule is used for determining gray pixels meeting preset conditions in the target image;
the first obtaining submodule is used for obtaining the number of the gray pixels;
and the second determining submodule is used for determining the ratio of the number of the gray pixels to the total number of the pixels of the target image as the confidence coefficient of the first white balance gain coefficient.
8. The apparatus of claim 7, wherein the first determination submodule comprises:
the first identification unit is used for identifying a first pixel point set of which the color coordinates are located in a preset gray area in a chromaticity diagram in the target image;
the second identification unit is used for identifying a second pixel point set of which the brightness value is within a preset brightness interval in the target image;
and the second determining unit is used for determining the pixel points in the intersection of the first pixel point set and the second pixel point set as the gray pixels meeting the preset conditions.
9. The apparatus of claim 6, wherein the first determining module comprises:
the second obtaining submodule is used for obtaining the maximum brightness value which can be identified by a camera of the electronic equipment;
and the third determining submodule is used for determining the confidence coefficient of the first white balance gain coefficient according to the maximum brightness value and the brightness information of the shooting environment when the target image is shot.
10. The apparatus of claim 6, wherein the calibration module comprises:
a fourth determining submodule, configured to determine the first white balance gain coefficient as a target white balance gain coefficient of the target image when the confidence is greater than a first confidence threshold;
the generation submodule is used for performing weighted calculation on the first white balance gain coefficient and the second white balance gain coefficient when the confidence coefficient is greater than or equal to a second confidence coefficient threshold and is less than or equal to the first confidence coefficient threshold so as to generate a target white balance gain coefficient of the target image;
a fifth determining sub-module, configured to determine the second white balance gain coefficient as a target white balance gain coefficient of the target image when the confidence is smaller than the second confidence threshold;
wherein the second confidence threshold is less than the first confidence threshold.
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