CN107948549B - Image noise point adjusting method and device - Google Patents
Image noise point adjusting method and device Download PDFInfo
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- CN107948549B CN107948549B CN201711085959.XA CN201711085959A CN107948549B CN 107948549 B CN107948549 B CN 107948549B CN 201711085959 A CN201711085959 A CN 201711085959A CN 107948549 B CN107948549 B CN 107948549B
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Abstract
The invention provides an image noise point adjusting method and device, and relates to the technical field of image processing. The method comprises the following steps: shooting by utilizing a camera of a mobile terminal to obtain a basic image, and determining the light source angle type of the basic image; and carrying out noise point processing on the basic image according to the light source angle type to obtain an optimized image. According to the method and the device, the corresponding noise point processing is carried out on the basic image according to the light source angle type of the basic image, and the processing effect of the image noise point and the visual effect of the image can be improved.
Description
Technical Field
The present invention relates to the field of image processing technologies, and in particular, to a method and an apparatus for adjusting image noise.
Background
With the continuous development of computer technology and the rapid popularization of mobile terminals, images and videos have become common information carriers in human activities, however, the quality of images is often affected by the interference of noise in the processes of acquiring, transmitting and storing the images. For example, due to the influence of sensor performance, analog and digital circuits, optical imaging systems, environment, and other factors, noise is always associated with images captured by mobile terminals such as cameras and mobile phones. Moreover, when the types of angles of the light sources are not consistent (front light, side light, back light, etc.), the images obtained by shooting often have different noise problems. These all affect the texture of the image and even the cosmetic effect of the subsequent image. Therefore, image denoising processing is carried out at the same time, and image denoising is a process for reducing noise in a digital image.
However, due to the insufficient hardware conditions of mobile terminals such as mobile phones, the processing effect on image noise is poor, and the visual effect of the image is affected.
Disclosure of Invention
The embodiment of the invention provides an image noise point adjusting method and device, and aims to solve the problem that the prior art has poor processing effect on image noise points and further influences the visual effect of an image.
In order to solve the technical problem, the invention is realized as follows: an image noise point adjusting method comprises the following steps:
shooting by utilizing a camera of a mobile terminal to obtain a basic image, and determining the light source angle type of the basic image;
and carrying out noise point processing on the basic image according to the light source angle type to obtain an optimized image.
In a first aspect, an embodiment of the present invention further provides an image noise adjusting apparatus, including:
the device comprises a light source angle type determining module, a light source angle type determining module and a control module, wherein the light source angle type determining module is used for obtaining a basic image by utilizing a camera of the mobile terminal to shoot and determining the light source angle type of the basic image;
and the noise point adjusting module is used for carrying out noise point processing on the basic image according to the light source angle type to obtain an optimized image.
In a second aspect, an embodiment of the present invention additionally provides a mobile terminal, 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 image noise correction method as described above.
In a third aspect, the present invention 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 image noise point adjustment method as described above.
According to the embodiment of the invention, the corresponding noise point processing is carried out on the basic image according to the light source angle type of the basic image, so that the processing effect of the image noise point and the visual effect of the image can be improved.
The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings 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 based on these drawings without inventive labor.
FIG. 1 is a flowchart illustrating steps of a method for adjusting noise in an image according to a first embodiment of the present invention;
FIG. 2 is a flowchart illustrating steps of a method for adjusting noise in an image according to a second embodiment of the present invention;
FIG. 2A is a diagram of a histogram of distributions of brightness and darkness according to a second embodiment of the present invention;
fig. 3 is a schematic structural diagram of an image noise adjusting apparatus according to a third embodiment of the present invention;
fig. 4 is a schematic structural diagram of an image noise adjusting apparatus according to a fourth embodiment of the present invention;
fig. 5 is a schematic diagram of a hardware structure of a mobile terminal in a fifth 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.
Example one
The embodiment of the invention provides an image noise point adjusting method.
Referring to fig. 1, a flowchart illustrating steps of a method for adjusting image noise according to an embodiment of the present invention is shown.
And step 110, shooting by using a camera of the mobile terminal to obtain a basic image, and determining the light source angle type of the basic image.
The camera may include, but is not limited to, a front camera and a rear camera of the mobile terminal, or an external camera that establishes a connection with the mobile terminal in a wireless or wired manner, and so on. The embodiment of the present invention is not limited thereto.
As described above, the conventional photographing method does not perform noise adjustment on the photographed base image according to the light source angle, which results in poor visual effect of the photographed picture. In the embodiment of the invention, a proper noise point adjusting method can be selected according to the light source angle of the basic image to adjust the basic image, so that an optimized image is obtained. Then, the light source angle type of the base image needs to be determined first through analysis of the base image.
In the embodiment of the invention, different light source angle types can be defined according to requirements. For example, light source angle types can be defined to include front, back, and side light, and the definition of different light source angle types is as follows:
the irradiation direction of the light is consistent with the shooting direction of the camera, or the included angle between the irradiation direction of the light and the shooting direction of the camera is within a first preset angle range; the backlight, the irradiation direction of the light is opposite to the shooting direction of the camera, or the included angle between the irradiation direction of the light and the shooting direction of the camera is within a second preset angle range; and side light, wherein the irradiation direction of the light and the shooting direction of the camera form an included angle relation of 90 degrees. The first preset angle range and the second preset angle range may be preset according to requirements, and the embodiment of the present invention is not limited thereto.
Furthermore, based on the above definition of the illumination angle type, a principle of determining the light source angle type to which the light source belongs based on the shot picture or the base image obtained by shooting can be set. For example, when a bright area of the face of the subject in the captured picture occupies a first preset proportion range of the total area of the captured picture, the face is classified as a direct light; when the bright area of the face of the subject in the shot picture occupies a second preset proportion range of the total area of the shot picture, the shot picture is classified as sidelight; and when the bright part area of the face of the subject in the shot picture occupies 0-25% of the third preset proportion range of the total area of the shot picture, and the background brightness is greater than the brightness of the face of the subject, the shot picture is classified as backlight. The first preset proportion range, the second preset proportion unit and the third preset proportion range may be preset according to requirements, and the embodiment of the present invention is not limited thereto. For example, a first preset proportion range of (75%, 100% ]), a second preset proportion range of [ 25% -75% ], and a third preset proportion range of [ 0% -25%) may be set.
Then, in the embodiment of the present invention, the light source angle type of the currently captured basic image may be determined through analysis of the basic image based on the preset method for determining the light source angle type. For example, if the bright area of the face of the subject in the currently captured base image occupies a first preset proportion range of the total area of the captured picture through analysis of the base image, it may be determined that the light source angle type of the base image is a front light.
And 120, performing noise point processing on the basic image according to the light source angle type to obtain an optimized image.
In practical application, it is known that problems of over-clear and outstanding details are easily caused during forward light shooting, especially outdoor scene shooting with high illumination intensity, so that noise point adjustment under the forward light shooting condition mainly needs noise point suppression and equalization processing; when the side light shooting is performed, the phenomenon of uneven distribution of the noise of the bright and dark parts is easy to occur, so the noise adjustment under the side light shooting condition mainly adjusts the respective noise density values of the bright and dark areas (for example, the density value of the bright part is slightly larger than or equal to that of the dark part) and the balance; in a backlight shooting environment, a shot basic image is easy to lack details, so that the noise point adjustment under the backlight shooting condition mainly needs to achieve the effect of increasing effective noise points.
Therefore, in the embodiment of the present invention, after the light source angle type of the base image is determined, in order to improve the visual effect of the image, a noise adjustment method corresponding to the light source angle type needs to be selected to perform noise processing on the base image, so as to obtain an optimized image. The noise point adjustment methods corresponding to different light source angle types may be preset according to requirements or experience, or may be trained from at least one ideal image under the corresponding light source angle type condition to obtain a noise point adjustment model under the corresponding light source angle type condition, and then the noise point adjustment model includes the noise point adjustment method under the corresponding light source angle type condition, which is not limited in the embodiment of the present invention. The ideal image under a certain light source angle type condition can be understood as an image under the light source angle type condition and with noise satisfying the ideal noise effect under the light source angle type condition.
For example, suppose the desired noise effect for the front light is R1, the desired noise effect for the side light is R2, and the desired noise effect for the back light is R3. Then, the noise adjustment model under the forward light condition can be obtained by training at least one ideal image with the noise effect satisfying R1, the noise adjustment model under the side light condition can be obtained by training at least one ideal image with the noise effect satisfying R2, and the noise adjustment model under the backward light condition can be obtained by training at least one ideal image with the noise effect satisfying R3. The type of the noise point adjustment model may be preset according to requirements, such as a neural network model, a fuzzy mathematical model, and the like.
Optionally, in an embodiment of the present invention, the step 120 further includes:
and a substep 121, when the light source angle type is normal, performing noise suppression and equalization processing on the basic image to obtain an optimized image.
As mentioned above, in practical applications, in the case of photographing in a front light condition, especially in an outdoor scene with a large illumination intensity, the problem that details are too clear and prominent easily occurs. Therefore, in the embodiment of the present invention, when the light source angle type of the base image is a front light, noise suppression and equalization processing may be performed on the base image to obtain an optimized image. The specific principle and method for performing noise suppression and equalization processing on the base image may be preset according to the requirement, and the embodiment of the present invention is not limited thereto.
And a substep 122, when the light source angle type is the side light, respectively adjusting the noise density value and the balance for the bright area and the dark area of the basic image to obtain an optimized image, wherein the noise density value of the bright area is greater than the noise density value of the dark area.
As described above, in the side light photographing, the phenomenon of uneven distribution of the bright and dark noise is likely to occur, and therefore, in the embodiment of the present invention, when the light source angle type of the base image is the side light, the noise density value and the balance may be respectively adjusted for the bright area and the dark area of the base image to obtain an optimized image, and in order to improve the visual effect, the noise density value of the bright area needs to be set to be greater than the noise density value of the dark area. For example, a brightness critical value may be set, when the brightness value of a certain pixel point in the basic image is less than or equal to the brightness critical value, the pixel point is determined to belong to the dark region, and when the brightness value of a certain pixel point in the basic image is greater than the brightness critical value, the pixel point is determined to input the bright region. Of course, the bright area and the dark area in the base image may be determined by any other available method in the embodiment of the present invention, which is not limited to this embodiment of the present invention.
Moreover, the specific principle and method for adjusting the noise density value and the equalization respectively for the bright region and the dark region in the same basic image may also be preset according to requirements or experience, and the embodiment of the present invention is not limited thereto.
And a substep 123, when the light source angle type is the reverse light, increasing the effective noise of the basic image to obtain an optimized image.
As described above, in a backlight shooting environment, a captured base image tends to lack details. Therefore, in the embodiment of the present invention, when the light source angle type of the basic image is backlight, the effective noise of the basic image needs to be increased to obtain the optimized image. The principle of increasing the effective noise point may be preset according to requirements or experience, and the embodiment of the present invention is not limited thereto.
For example, the proportion of the effective noise added to the base image under different backlight degree conditions to the base image and the principle of adding the effective noise can be respectively set, the number of the effective noise to be added to the base image is determined according to the backlight degree of the base image obtained by current shooting, and the effective noise with the corresponding number is added to the base image according to the corresponding principle of adding the noise, so as to obtain the optimized image.
In the embodiment of the invention, a basic image is obtained by shooting with a camera of the mobile terminal, and the light source angle type of the basic image is determined; and carrying out noise point processing on the basic image according to the light source angle type to obtain an optimized image. The method and the device can realize corresponding noise point processing on the basic image according to the light source angle type of the basic image, and further improve the processing effect of the image noise point and the visual effect of the image.
Moreover, in the embodiment of the present invention, when the light source angle type is a normal light, noise suppression and equalization processing may be performed on the base image to obtain an optimized image; when the light source angle type is side light, respectively adjusting the noise density value and the balance for the bright area and the dark area of the basic image to obtain an optimized image, wherein the noise density value of the bright area is larger than the noise density value of the dark area; and when the light source angle type is the reverse light, increasing the effective noise of the basic image to obtain an optimized image. Thereby further improving the processing effect of image noise and the visual effect of the image.
Example two
The embodiment of the invention provides an image noise point adjusting method.
Referring to fig. 2, a flowchart illustrating steps of a method for adjusting image noise according to an embodiment of the present invention is shown.
And step 210, shooting by using a camera of the mobile terminal to obtain a basic image, and performing shading analysis on the basic image to obtain a shading distribution result of the basic image.
In the embodiment of the present invention, the shading analysis may be performed on the base image by any available method to obtain a shading result of the base image, which is not limited in the embodiment of the present invention.
Optionally, in an embodiment of the present invention, the step 210 further includes:
a substep 211 of obtaining a histogram of the light and shade distribution of the base image.
The image histogram is a statistical table reflecting the distribution of image pixels, and the abscissa thereof represents the kind of image pixels, which may be gray-scale or color. The ordinate represents the total number of pixels in the image or the percentage of all pixels in each color value. The distribution histogram of the light and shade in the embodiment of the present invention is one of the image histograms. Fig. 2A is a schematic diagram of a histogram of light and dark distributions in an embodiment of the present invention. The abscissa corresponds to the brightness value and the ordinate corresponds to the number of pixels. In the embodiment of the invention, the shading analysis can be performed on the basic image by any available method, that is, the number of pixel points corresponding to different brightness values in the basic image is analyzed, so that a shading distribution histogram of the basic image is obtained.
And a substep 212, obtaining the number of first pixels belonging to the bright region and the number of second pixels belonging to the dark region in the bright-dark distribution histogram according to a preset bright-dark threshold parameter.
The brightness threshold parameter may be set before this step or before any step before this step according to requirements, and the embodiment of the present invention is not limited thereto.
For example, if the preset bright-dark portion threshold parameter is a, the number of pixels having a brightness value greater than or equal to a in the bright-dark distribution histogram may be obtained as the first number of pixels belonging to the bright portion region, and the number of pixels having a brightness value smaller than a in the bright-dark distribution histogram may be obtained as the second number of pixels belonging to the dark portion region.
For example, for the histogram of the light and shade distribution shown in fig. 2A, assuming that the preset light and shade threshold parameter is X2, the sum of the numbers of pixels corresponding to the X1 to X2 regions is calculated, that is, the area a in fig. 2A is the second number of pixels belonging to the dark portion region; and calculating in the same way to obtain the area B which is the number of the first pixel points belonging to the bright part area.
And a substep 213, obtaining the light and shade distribution parameter of the basic image as the light and shade distribution result based on a preset light and shade ratio calculation formula according to the number of the first pixel points and the number of the second pixel points.
The light-dark ratio calculation formula may be set before the step or before any step before the step according to requirements, and the embodiment of the present invention is not limited thereto. For example, the light-to-dark ratio calculation formula can be set as the ratio of the number of the second pixels to the number of the first pixels. Then, at this time, for the histogram of the light and shade distribution shown in fig. 2A, the area B/area a may be used, and then the light and shade distribution parameter of the base image corresponding to fig. 2A is obtained as the light and shade distribution result; or, in the embodiment of the present invention, a ratio of the number of the first pixel points to the number of the second pixel points may also be used as a light-to-dark ratio calculation formula, and then for the light-to-dark distribution histogram shown in fig. 2A, the area a/the area B may be used, so as to obtain the light-to-dark distribution parameter of the basic image corresponding to fig. 2A as the light-to-dark distribution result.
After the shading results of the base image are obtained, then the light source angle type of the base image may be determined based on the shading results. In the embodiment of the present invention, the corresponding relationship between the light and dark distribution result and the light source angle type may be set in advance according to requirements or experience, and the embodiment of the present invention is not limited by this.
For example, if the preset range of the shading result under the taillight condition is (a, b), then if the obtained shading result of the current base image is θ, and θ ∈ (a, b), then it may be determined that the type of the light source angle of the current base image is taillight.
Optionally, in an embodiment of the present invention, the step 220 further includes:
the substep 221 determines the light source angle type of the basic image according to the light and shade distribution parameter of the basic image based on a preset parameter threshold corresponding to different preset light source angle types.
In the embodiment of the present invention, if the obtained shading result is the aforementioned shading parameter, the corresponding relationship between the shading parameter and the light source angle type may be preset according to experience or requirements. Specifically, the preset parameter threshold corresponding to different light source angle types may be set in advance according to requirements or experience, and the light source angle type of the corresponding basic image may be determined according to the light and dark distribution parameter of the basic image.
For example, the preset parameter threshold value under the corresponding frontlighting condition is (m1, n1), the preset parameter threshold value under the corresponding backlighting condition is (m2, n2), the preset parameter threshold value under the corresponding sidelight condition is (m3, n3), the light and shade distribution parameter of the base image obtained by current shooting is β, and if β ∈ (m2, n2), the light source angle type of the base image can be determined to be backlighting.
And 230, training to obtain noise adjustment models corresponding to different light source angle types according to at least one ideal image with ideal noise effects under the condition of each light source angle type and an original image corresponding to the ideal image.
In the embodiment of the invention, in order to conveniently select a proper noise point adjustment method to perform noise point processing on the basic image according to the light source angle type, noise point adjustment models corresponding to different light source angle types can be obtained by pre-training. Then, when selecting the noise adjustment model corresponding to the base image with the determined light source angle type, the noise adjustment model corresponding to the light source angle type needs to be obtained through training. Moreover, in the embodiment of the present invention, the noise point adjustment model corresponding to the basic image with the determined light source angle type may be preferentially trained, or noise point adjustment models corresponding to different light source angle types may be obtained through simultaneous training, which is not limited in the embodiment of the present invention. Specifically, the noise adjustment model of the corresponding light source angle type can be obtained by training according to at least one ideal image with an ideal noise effect under the condition of the corresponding light source angle type and the original image corresponding to each ideal image.
For example, training at least one ideal image with ideal noise effect under the taillight condition and an original image corresponding to each ideal image to obtain a noise adjustment model under the taillight condition; training to obtain a noise point adjustment model under the backlight condition by using at least one ideal image with an ideal noise point effect under the backlight condition and obtaining an original image corresponding to each ideal image; and training to obtain a noise point adjustment model under the side light condition by using at least one ideal image with ideal noise point effect under the side light condition and the original images corresponding to the ideal images. Moreover, if the light source angle type of the current basic image is determined, then the noise adjustment model under the light source angle type condition can be trained and obtained only according to at least one ideal image with an ideal noise effect under the light source angle type condition and the original images corresponding to the ideal images. The ideal image in which the noise effect is ideal may be determined by the user in advance according to the needs or experience, and the embodiment of the present invention is not limited thereto.
Moreover, the basic parameters such as the type structure of the noise adjustment model and the like may be set before this step or before any step before this step according to the requirements, and the embodiment of the present invention is not limited thereto. At this time, at least one ideal image with an ideal noise effect under the condition of each light source angle type and an original image corresponding to the ideal image can be used as the input of a preset training model, and a noise adjustment model corresponding to each light source angle type is obtained through training.
In addition, in the embodiment of the present invention, a preset training model may be used to train to obtain noise point adjustment models of different light source angle types, and at this time, the noise point adjustment model obtained through training may include noise point processing channels respectively corresponding to the conditions of different light source angle types, so that after receiving the base image, the noise point adjustment model may be allocated to corresponding noise point processing channels according to the light source angle type of the base image; the noise point adjustment models corresponding to the light source angle types can also be obtained by respectively utilizing the preset training models corresponding to the light source angle types for training, the structures of the preset training models corresponding to different light source angle types can be different or completely the same, the embodiment of the invention is not limited, and the basic image can be input into the corresponding noise point adjustment model according to the light source angle type of the basic image, so that the corresponding optimized image can be obtained.
For example, three training models A, B and C may be preset, so that at least one ideal image with an ideal noise effect under the taillight condition and an original image corresponding to the ideal image may be used as the input of the preset training model a to train to obtain a noise adjustment model corresponding to the taillight condition; training at least one ideal image with ideal noise effect under the backlight condition and an original image corresponding to the ideal image to obtain a noise adjustment model corresponding to the backlight condition as the input of a preset training model B; at least one ideal image with ideal noise effect under the side light condition and an original image corresponding to the ideal image can be used as the input of a preset training model C, and a noise adjustment model corresponding to the side light condition is obtained through training. The training models A, B and C may be models with the same structure, or models with structures that are not completely the same, and the embodiment of the present invention is not limited thereto.
Or, a training model D can be set, and then at least one ideal image with ideal noise effect under the taillight condition and an original image corresponding to the ideal image are respectively utilized; at least one ideal image with ideal noise effect under the backlight condition and an original image corresponding to the ideal image; and after receiving the basic image, distributing the basic image to a noise processing channel of the noise adjusting method corresponding to the light source angle type of the basic image according to the light source angle type of the basic image.
And 240, inputting the basic image into the noise point adjustment model obtained by training to obtain an optimized image corresponding to the basic image. And when the noise point adjustment model receives the basic image, distributing the basic image to a noise point processing channel corresponding to the light source angle type.
After the noise point adjustment model is trained, if noise point adjustment models corresponding to different light source angle types are obtained through respective training, when the noise point adjustment is performed on the basic image, the basic image can be directly input into the noise point adjustment model corresponding to the corresponding light source angle types obtained through training, and after the basic image is obtained through receiving the trained noise point adjustment model, the basic image can be subjected to noise point processing to obtain an optimized image; or, if a noise adjustment model is obtained by training and the noise adjustment model includes noise processing channels corresponding to different light source angle types, then the basic image can be allocated to the noise processing channel corresponding to the light source angle type of the basic image according to the light source angle type of the basic image, and then the noise adjustment of the basic image is completed by using a corresponding noise adjustment method to obtain a corresponding optimized image.
If the noise point adjustment model corresponding to the corresponding light source angle type is obtained by training respectively by using the preset training models corresponding to different light source angle types, the basic image can be directly input into the trained preset training model corresponding to the light source angle type of the basic image, and then the optimized image corresponding to the basic image is obtained.
In the embodiment of the invention, a basic image is obtained by shooting with a camera of the mobile terminal, and the light source angle type of the basic image is determined; and carrying out noise point processing on the basic image according to the light source angle type to obtain an optimized image. The method and the device can realize corresponding noise point processing on the basic image according to the light source angle type of the basic image, and further improve the processing effect of the image noise point and the visual effect of the image.
Moreover, in the embodiment of the present invention, a camera of the mobile terminal may be further used to capture a basic image, and the basic image is subjected to shading analysis to obtain a shading distribution result of the basic image; and determining the light source angle type of the basic image based on the light and shade distribution result. Acquiring a light and shade distribution histogram of the basic image; acquiring the number of first pixel points belonging to a bright part area and the number of second pixel points belonging to a dark part area in the light and shade distribution histogram according to a preset light and shade part threshold parameter; and acquiring a light and shade distribution parameter of the basic image as the light and shade distribution result based on a preset light and shade ratio calculation formula according to the number of the first pixel points and the number of the second pixel points. And determining the light source angle type of the basic image according to the light and shade distribution parameter of the basic image based on a preset parameter threshold corresponding to different preset light source angle types. The efficiency and accuracy of the determined angle type of the light source may thereby be further improved.
In addition, in the embodiment of the present invention, a noise adjustment model corresponding to different light source angle types may be obtained by training according to at least one ideal image with an ideal noise effect under each light source angle type and an original image corresponding to the ideal image. And inputting the basic image into the noise point adjustment model obtained by training to obtain an optimized image corresponding to the basic image. And when the noise point adjustment model receives the basic image, distributing the basic image to a noise point processing channel corresponding to the light source angle type. Therefore, the accuracy and convenience of noise point processing of the basic images corresponding to different light source angle types are improved.
EXAMPLE III
The embodiment of the invention provides an image noise point adjusting device.
Referring to fig. 3, a schematic structural diagram of an image noise adjusting apparatus according to an embodiment of the present invention is shown.
The image noise adjusting apparatus 300 according to the embodiment of the present invention includes: a light source angle type determination module 310 and a noise point adjustment module 320.
The functions of the modules and the interaction relationship between the modules are described in detail below.
The light source angle type determining module 310 is configured to obtain a basic image by using a camera of the mobile terminal to capture the basic image, and determine a light source angle type of the basic image.
And a noise point adjusting module 320, configured to perform noise point processing on the base image according to the light source angle type to obtain an optimized image.
The image noise point adjusting device provided by the embodiment of the present invention can implement each process implemented by the mobile terminal in the method embodiments of fig. 1 and fig. 2, and is not described herein again in order to avoid repetition.
According to the embodiment of the invention, the corresponding noise point processing is carried out on the basic image according to the light source angle type of the basic image, so that the processing effect of the image noise point and the visual effect of the image can be improved.
Moreover, in the embodiment of the present invention, when the light source angle type is a normal light, noise suppression and equalization processing may be performed on the base image to obtain an optimized image; when the light source angle type is side light, respectively adjusting the noise density value and the balance for the bright area and the dark area of the basic image to obtain an optimized image, wherein the noise density value of the bright area is larger than the noise density value of the dark area; and when the light source angle type is the reverse light, increasing the effective noise of the basic image to obtain an optimized image. Thereby further improving the processing effect of image noise and the visual effect of the image.
Example four
The embodiment of the invention provides an image noise point adjusting device.
Referring to fig. 4, a schematic structural diagram of an image noise adjusting apparatus according to an embodiment of the present invention is shown.
The image noise adjusting apparatus 400 according to the embodiment of the present invention includes: light source angle type determination module 410, noise adjustment model training module 420, and noise adjustment module 430.
The functions of the modules and the interaction relationship between the modules are described in detail below.
And a light source angle type determining module 410, configured to obtain a basic image by using a camera of the mobile terminal, and determine a light source angle type of the basic image.
Optionally, in an embodiment of the present invention, the light source angle type determining module 410 further includes:
and the shading analysis submodule 411 is configured to obtain a basic image by using a camera of the mobile terminal to capture the basic image, and perform shading analysis on the basic image to obtain a shading distribution result of the basic image.
Optionally, in an embodiment of the present invention, the shading analysis submodule 411 may further include:
a shading distribution histogram acquisition unit configured to acquire a shading distribution histogram of the base image.
And the bright and dark pixel point counting unit is used for acquiring the number of first pixel points belonging to a bright part area and the number of second pixel points belonging to a dark part area in the bright and dark distribution histogram according to a preset bright and dark part threshold parameter.
And the light and shade distribution parameter acquisition unit is used for acquiring the light and shade distribution parameters of the basic image as the light and shade distribution result based on a preset light and shade ratio calculation formula according to the number of the first pixel points and the number of the second pixel points.
A light source angle type determining submodule 412, configured to determine a light source angle type of the base image based on the shading distribution result.
Optionally, in this embodiment of the present invention, the light source angle type determining sub-module 412 is further configured to determine the light source angle type of the base image according to a light and dark distribution parameter of the base image based on a preset parameter threshold corresponding to different preset light source angle types.
And the noise adjustment model training module 420 is configured to train to obtain noise adjustment models corresponding to different light source angle types according to at least one ideal image with an ideal noise effect under each light source angle type and an original image corresponding to the ideal image.
And a noise point adjusting module 430, configured to perform noise point processing on the basic image according to the light source angle type to obtain an optimized image.
Optionally, in this embodiment of the present invention, the noise adjustment module 430 is further configured to input the base image into the noise adjustment model obtained through training, so as to obtain an optimized image corresponding to the base image. And when the noise point adjustment model receives the basic image, distributing the basic image to a noise point processing channel corresponding to the light source angle type.
The image noise point adjusting device provided by the embodiment of the present invention can implement each process implemented by the mobile terminal in the method embodiments of fig. 1 and fig. 2, and is not described herein again in order to avoid repetition.
In the embodiment of the invention, a basic image is obtained by shooting with a camera of the mobile terminal, and the light source angle type of the basic image is determined; and carrying out noise point processing on the basic image according to the light source angle type to obtain an optimized image. The method and the device can realize corresponding noise point processing on the basic image according to the light source angle type of the basic image, and further improve the processing effect of the image noise point and the visual effect of the image.
Moreover, in the embodiment of the present invention, a camera of the mobile terminal may be further used to capture a basic image, and the basic image is subjected to shading analysis to obtain a shading distribution result of the basic image; and determining the light source angle type of the basic image based on the light and shade distribution result. Acquiring a light and shade distribution histogram of the basic image; acquiring the number of first pixel points belonging to a bright part area and the number of second pixel points belonging to a dark part area in the light and shade distribution histogram according to a preset light and shade part threshold parameter; and acquiring a light and shade distribution parameter of the basic image as the light and shade distribution result based on a preset light and shade ratio calculation formula according to the number of the first pixel points and the number of the second pixel points. And determining the light source angle type of the basic image according to the light and shade distribution parameter of the basic image based on a preset parameter threshold corresponding to different preset light source angle types. The efficiency and accuracy of the determined angle type of the light source may thereby be further improved.
In addition, in the embodiment of the present invention, a noise adjustment model corresponding to different light source angle types may be obtained by training according to at least one ideal image with an ideal noise effect under each light source angle type and an original image corresponding to the ideal image. And inputting the basic image into the noise point adjustment model obtained by training to obtain an optimized image corresponding to the basic image. And when the noise point adjustment model receives the basic image, distributing the basic image to a noise point processing channel corresponding to the light source angle type. Therefore, the accuracy and convenience of noise point processing of the basic images corresponding to different light source angle types are improved.
EXAMPLE five
Fig. 5 is a schematic diagram of a hardware structure of a mobile terminal implementing various embodiments of the present invention.
The mobile terminal 500 includes, but is not limited to: a radio frequency unit 501, a network module 502, an audio output unit 503, an input unit 504, a sensor 505, a display unit 506, a user input unit 507, an interface unit 508, a memory 509, a processor 510, and a power supply 511. Those skilled in the art will appreciate that the mobile terminal architecture shown in fig. 5 is not intended to be limiting of mobile terminals, and that a mobile terminal 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 mobile terminal 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.
A processor 510, configured to obtain a basic image through shooting by using a camera of the mobile terminal, and determine a light source angle type of the basic image; and carrying out noise point processing on the basic image according to the light source angle type to obtain an optimized image.
In the embodiment of the invention, a basic image is obtained by shooting with a camera of the mobile terminal; shooting by utilizing a camera of the mobile terminal to obtain a basic image, and determining the light source angle type of the basic image; and carrying out noise point processing on the basic image according to the light source angle type to obtain an optimized image. The method and the device can realize corresponding noise point processing on the basic image according to the light source angle type of the basic image, and further improve the processing effect of the image noise point and the visual effect of the image.
Moreover, in the embodiment of the present invention, when the light source angle type is a normal light, noise suppression and equalization processing may be performed on the base image to obtain an optimized image; when the light source angle type is side light, respectively adjusting the noise density value and the balance for the bright area and the dark area of the basic image to obtain an optimized image, wherein the noise density value of the bright area is larger than the noise density value of the dark area; and when the light source angle type is the reverse light, increasing the effective noise of the basic image to obtain an optimized image. Thereby further improving the processing effect of image noise and the visual effect of the image.
In addition, in the embodiment of the present invention, a camera of the mobile terminal may be further used to capture a basic image, and the basic image is subjected to shading analysis to obtain a shading distribution result of the basic image; and determining the light source angle type of the basic image based on the light and shade distribution result. Acquiring a light and shade distribution histogram of the basic image; acquiring the number of first pixel points belonging to a bright part area and the number of second pixel points belonging to a dark part area in the light and shade distribution histogram according to a preset light and shade part threshold parameter; and acquiring a light and shade distribution parameter of the basic image as the light and shade distribution result based on a preset light and shade ratio calculation formula according to the number of the first pixel points and the number of the second pixel points. And determining the light source angle type of the basic image according to the light and shade distribution parameter of the basic image based on a preset parameter threshold corresponding to different preset light source angle types. The efficiency and accuracy of the determined angle type of the light source may thereby be further improved.
Further, in the embodiment of the present invention, a noise adjustment model corresponding to different light source angle types may be obtained by training according to at least one ideal image with an ideal noise effect under each light source angle type and an original image corresponding to the ideal image. And inputting the basic image into the noise point adjustment model obtained by training to obtain an optimized image corresponding to the basic image. And when the noise point adjustment model receives the basic image, distributing the basic image to a noise point processing channel corresponding to the light source angle type. Therefore, the accuracy and convenience of noise point processing of the basic images corresponding to different light source angle types are improved.
It should be understood that, in the embodiment of the present invention, the radio frequency unit 501 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 510; in addition, the uplink data is transmitted to the base station. In general, radio frequency unit 501 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. In addition, the radio frequency unit 501 can also communicate with a network and other devices through a wireless communication system.
The mobile terminal provides the user with wireless broadband internet access through the network module 502, such as helping the user send and receive e-mails, browse webpages, access streaming media, and the like.
The audio output unit 503 may convert audio data received by the radio frequency unit 501 or the network module 502 or stored in the memory 509 into an audio signal and output as sound. Also, the audio output unit 503 may also provide audio output related to a specific function performed by the mobile terminal 500 (e.g., a call signal reception sound, a message reception sound, etc.). The audio output unit 503 includes a speaker, a buzzer, a receiver, and the like.
The input unit 504 is used to receive an audio or video signal. The input Unit 504 may include a Graphics Processing Unit (GPU) 5041 and a microphone 5042, and the Graphics processor 5041 processes image data of a still image or video obtained by an image capturing device (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 506. The image frames processed by the graphic processor 5041 may be stored in the memory 509 (or other storage medium) or transmitted via the radio frequency unit 501 or the network module 502. The microphone 5042 may receive sounds and may be capable of processing such sounds 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 501 in case of the phone call mode.
The mobile terminal 500 also includes at least one sensor 505, such as a light sensor, motion sensor, and other sensors. Specifically, the light sensor includes an ambient light sensor that adjusts the brightness of the display panel 5061 according to the brightness of ambient light, and a proximity sensor that turns off the display panel 5061 and/or a backlight when the mobile terminal 500 is moved to the ear. As one of the motion sensors, the 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 the mobile terminal (such as horizontal and vertical screen switching, related games, magnetometer posture calibration), and vibration identification related functions (such as pedometer, tapping); the sensors 505 may also include fingerprint sensors, pressure sensors, iris sensors, molecular sensors, gyroscopes, barometers, hygrometers, thermometers, infrared sensors, etc., which are not described in detail herein.
The display unit 506 is used to display information input by the user or information provided to the user. The Display unit 506 may include a Display panel 5061, and the Display panel 5061 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 507 may be used to receive input numeric or character information and generate key signal inputs related to user settings and function control of the mobile terminal. Specifically, the user input unit 507 includes a touch panel 5071 and other input devices 5072. Touch panel 5071, 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 5071 using a finger, stylus, or any suitable object or attachment). The touch panel 5071 may include two parts of 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 510, and receives and executes commands sent by the processor 510. In addition, the touch panel 5071 may be implemented in various types such as a resistive type, a capacitive type, an infrared ray, and a surface acoustic wave. In addition to the touch panel 5071, the user input unit 507 may include other input devices 5072. In particular, other input devices 5072 may include, but are not limited to, a physical keyboard, function keys (e.g., volume control keys, switch keys, etc.), a trackball, a mouse, and a joystick, which are not described in detail herein.
Further, the touch panel 5071 may be overlaid on the display panel 5061, and when the touch panel 5071 detects a touch operation thereon or nearby, the touch operation is transmitted to the processor 510 to determine the type of the touch event, and then the processor 510 provides a corresponding visual output on the display panel 5061 according to the type of the touch event. Although in fig. 5, the touch panel 5071 and the display panel 5061 are two independent components to implement the input and output functions of the mobile terminal, in some embodiments, the touch panel 5071 and the display panel 5061 may be integrated to implement the input and output functions of the mobile terminal, and is not limited herein.
The interface unit 508 is an interface through which an external device is connected to the mobile terminal 500. 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 508 may be used to receive input (e.g., data information, power, etc.) from external devices and transmit the received input to one or more elements within the mobile terminal 500 or may be used to transmit data between the mobile terminal 500 and external devices.
The memory 509 may be used to store software programs as well as various data. The memory 509 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 509 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 510 is a control center of the mobile terminal, connects various parts of the entire mobile terminal using various interfaces and lines, and performs various functions of the mobile terminal and processes data by operating or executing software programs and/or modules stored in the memory 509 and calling data stored in the memory 509, thereby performing overall monitoring of the mobile terminal. Processor 510 may include one or more processing units; preferably, the processor 510 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 processor 510.
The mobile terminal 500 may further include a power supply 511 (e.g., a battery) for supplying power to various components, and preferably, the power supply 511 may be logically connected to the processor 510 via a power management system, so that functions of managing charging, discharging, and power consumption are performed via the power management system.
In addition, the mobile terminal 500 includes some functional modules that are not shown, and thus, are not described in detail herein.
Preferably, an embodiment of the present invention further provides a mobile terminal, including: the processor 510, the memory 509, and a computer program stored in the memory 509 and capable of running on the processor 510, where the computer program, when executed by the processor 510, implements each process of the above-mentioned embodiment of the image noise point adjustment method, and can achieve the same technical effect, and are not described herein again to avoid repetition.
The 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 being executed by a processor, the computer program implements each process of the above-mentioned embodiment of the image noise point adjustment method, and can achieve the same technical effect, and in order to avoid repetition, the detailed description is omitted 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.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a U disk, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (8)
1. An image noise point adjustment method, applied to a mobile terminal, includes:
shooting by utilizing a camera of the mobile terminal to obtain a basic image, and determining the light source angle type of the basic image;
according to the light source angle type, carrying out noise point processing on the basic image to obtain an optimized image;
the noise processing is performed on the basic image according to the light source angle type to obtain an optimized image, and the method comprises the following steps:
when the light source angle type is normal light, noise suppression and equalization processing are carried out on the basic image to obtain an optimized image;
when the light source angle type is side light, respectively adjusting the density value and the balance of noise points aiming at the bright part area and the dark part area of the basic image to obtain an optimized image; the respectively adjusting the noise density value and the balance comprises: adjusting the density of the noise in the bright area and the dark area to make the noise density value of the bright area greater than the noise density value of the dark area, thereby respectively adjusting the noise density value and the balance; when the light source angle type is the reverse light, increasing the effective noise of the basic image to obtain an optimized image; the increasing the effective noise of the base image comprises: setting the proportion of effective noise points added to the basic image and the basic image under different backlight degree conditions and the principle of increasing the effective noise points; determining the number of the increased effective noise points according to the backlight degree of the basic image and the proportion; and increasing the number of the effective noise points in the basic image according to the noise point increasing principle.
2. The method according to claim 1, wherein the step of obtaining a base image by using a camera of the mobile terminal, and determining the light source angle type of the base image comprises:
shooting by using a camera of the mobile terminal to obtain a basic image, and performing shading analysis on the basic image to obtain a shading distribution result of the basic image;
and determining the light source angle type of the basic image based on the light and shade distribution result.
3. The method according to claim 2, wherein the step of capturing a basic image by using a camera of the mobile terminal and performing shading analysis on the basic image to obtain a shading result of the basic image comprises:
acquiring a light and shade distribution histogram of the basic image;
acquiring the number of first pixel points belonging to a bright part area and the number of second pixel points belonging to a dark part area in the light and shade distribution histogram according to a preset light and shade part threshold parameter;
acquiring a light and shade distribution parameter of the basic image as a light and shade distribution result based on a preset light and shade ratio calculation formula according to the number of the first pixel points and the number of the second pixel points; wherein, the calculation mode expressed by the preset light and shade ratio calculation formula is as follows: calculating the ratio of the number of the second pixel points to the number of the first pixel points;
further, the step of determining the light source angle type of the base image based on the shading result includes:
and determining a preset parameter threshold range to which the light and shade distribution parameter belongs based on preset parameter threshold ranges corresponding to different preset light source angle types, and determining the light source angle type corresponding to the preset parameter threshold range to be the light source angle type of the basic image.
4. An image noise adjusting apparatus, comprising:
the device comprises a light source angle type determining module, a light source angle type determining module and a control module, wherein the light source angle type determining module is used for obtaining a basic image by utilizing a camera of the mobile terminal to shoot and determining the light source angle type of the basic image;
the noise point adjusting module is used for carrying out noise point processing on the basic image according to the light source angle type to obtain an optimized image;
the noise point adjusting module comprises:
the forward light noise point adjusting submodule is used for carrying out noise point suppression and equalization processing on the basic image to obtain an optimized image when the light source angle type is forward light;
the side light noise point adjusting submodule is used for respectively adjusting the noise point density value and the balance aiming at the bright area and the dark area of the basic image to obtain an optimized image when the light source angle type is side light; the respectively adjusting the noise density value and the balance comprises: adjusting the density of the noise in the bright area and the dark area to make the noise density value of the bright area greater than the noise density value of the dark area, thereby respectively adjusting the noise density value and the balance;
the backlight noise point adjusting submodule is used for increasing the effective noise point of the basic image when the light source angle type is backlight so as to obtain an optimized image; the increasing the effective noise of the base image comprises: setting the proportion of effective noise points added to the basic image and the basic image under different backlight degree conditions and the principle of increasing the effective noise points; determining the number of the increased effective noise points according to the backlight degree of the basic image and the proportion; and increasing the number of the effective noise points in the basic image according to the noise point increasing principle.
5. The image noise adjustment apparatus of claim 4, wherein the light source angle type determining module comprises:
the bright and dark analysis submodule is used for obtaining a basic image by utilizing the shooting of a camera of the mobile terminal and carrying out bright and dark analysis on the basic image to obtain a bright and dark distribution result of the basic image;
and the light source angle type determining submodule is used for determining the light source angle type of the basic image based on the light and shade distribution result.
6. The image noise adjustment device of claim 5, wherein the shading sub-module comprises:
a shading distribution histogram acquisition unit configured to acquire a shading distribution histogram of the base image;
the bright-dark pixel point counting unit is used for acquiring the number of first pixel points belonging to a bright part area and the number of second pixel points belonging to a dark part area in the bright-dark distribution histogram according to a preset bright-dark part threshold parameter;
a shading parameter obtaining unit, configured to obtain, according to the number of the first pixel points and the number of the second pixel points, a shading parameter of the base image as the shading result based on a preset shading ratio calculation formula; wherein, the calculation mode expressed by the preset light and shade ratio calculation formula is as follows: calculating the ratio of the number of the second pixel points to the number of the first pixel points;
the light source angle type determining submodule is further configured to determine a preset parameter threshold range to which the light and dark distribution parameter belongs based on preset parameter threshold ranges corresponding to different preset light source angle types, and determine the light source angle type corresponding to the preset parameter threshold range to be the light source angle type of the basic image.
7. A mobile terminal, comprising: memory, processor and computer program stored on the memory and executable on the processor, the computer program, when executed by the processor, implementing the steps of the image noise adjustment method according to any one of claims 1 to 3.
8. A computer-readable storage medium, having stored thereon a computer program which, when being executed by a processor, carries out the steps of the image noise adjustment method according to any one of claims 1 to 3.
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| CN103067661A (en) * | 2013-01-07 | 2013-04-24 | 华为终端有限公司 | Image processing method, image processing device and shooting terminal |
| CN105049743A (en) * | 2015-08-21 | 2015-11-11 | 宇龙计算机通信科技(深圳)有限公司 | Backlight testing method, backlight testing system, picture taking device and terminal |
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