CN108810406B - Portrait light effect processing method, device, terminal and computer readable storage medium - Google Patents
Portrait light effect processing method, device, terminal and computer readable storage medium Download PDFInfo
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- CN108810406B CN108810406B CN201810500747.1A CN201810500747A CN108810406B CN 108810406 B CN108810406 B CN 108810406B CN 201810500747 A CN201810500747 A CN 201810500747A CN 108810406 B CN108810406 B CN 108810406B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/80—Camera processing pipelines; Components thereof
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/70—Circuitry for compensating brightness variation in the scene
- H04N23/76—Circuitry for compensating brightness variation in the scene by influencing the image signals
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Abstract
The embodiment of the application relates to a portrait light effect processing method, a portrait light effect processing device, a portrait light effect processing terminal and a computer-readable storage medium. The method comprises the following steps: acquiring an image to be processed, and determining a portrait area in the image to be processed; identifying a portrait type within the portrait area; acquiring a light effect processing model corresponding to the portrait type; and carrying out light effect processing on the portrait area according to the light effect processing model. By the method, the light effect processing model suitable for the portrait type can be selected according to different portrait types, so that the portrait has higher expressive force, the process of the user for processing the light effect of the portrait is simplified, and the user experience is improved.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to a method and an apparatus for processing a light effect of a portrait, a terminal, and a computer-readable storage medium.
Background
With the continuous development of internet technology, the intellectualization of the mobile terminal brings great convenience to users, for example, the picture taking function is higher and higher, the picture taking effect is even comparable to that of a professional photographic instrument, and the mobile terminal has the convenience in carrying and using, so that the picture taking through the mobile terminal becomes an indispensable entertainment item in the life of people.
In the process of taking a picture or processing an image, the image is usually required to be subjected to light effect processing so as to improve the viewing effect of the image. In a traditional portrait light effect processing method, a user usually selects the type of light effect to add the light effect to the portrait, parameters for performing light effect processing on the image are fixed, the effect is single, the traditional portrait light effect processing method lacks pertinence, and the light effect is poor.
Disclosure of Invention
The embodiment of the application provides a portrait light effect processing method, a portrait light effect processing device, a terminal and a computer readable storage medium, and light effects adaptive to the type of the portrait can be added to an image to be processed according to different types of the portrait, so that the portrait has better expressive force.
A portrait light effect processing method comprises the following steps:
acquiring an image to be processed, and determining a portrait area of the image to be processed;
identifying a portrait type within the portrait area;
acquiring a light effect processing model corresponding to the portrait type;
and carrying out light effect processing on the portrait area according to the light effect processing model.
A portrait light effect processing apparatus comprising:
the region identification module is used for acquiring an image to be processed and determining a portrait region in the image to be processed;
the type identification module is used for identifying the type of the portrait in the portrait area;
the model acquisition module is used for acquiring a light effect processing model corresponding to the portrait type;
and the light effect processing module is used for carrying out light effect processing on the portrait area according to the light effect processing model.
A terminal comprising a memory and a processor, the memory having stored therein a computer program which, when executed by the processor, causes the processor to carry out the method as described above.
A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the method as set forth above.
According to the portrait light effect processing method, the device, the terminal and the computer-readable storage medium, the to-be-processed image is obtained, the portrait area in the to-be-processed image is determined, the portrait type in the portrait area is identified, the light effect processing model corresponding to the portrait type is obtained, the light effect processing is carried out on the portrait area according to the light effect processing model, the light effect processing model suitable for the portrait type can be selected according to different portrait types, the portrait has expressive force, the process of the user for processing the portrait light effect is simplified, and the user experience is improved.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a diagram of an application environment of a light effect processing method for a human image according to an embodiment;
fig. 2 is a schematic diagram of the internal structure of the terminal in one embodiment;
FIG. 3 is a flowchart illustrating a method for processing light effects of a human image according to an embodiment;
FIG. 4 is a schematic flow chart of a light effect processing method for a human image according to another embodiment;
FIG. 5 is a flowchart illustrating a light effect processing method for a human image according to another embodiment;
FIG. 6 is a schematic flow chart of a light effect processing method for a portrait according to another embodiment;
FIG. 7 is a flowchart illustrating a light effect processing method for a human image according to another embodiment;
FIG. 8 is a schematic view of a light effect processing model in an embodiment;
FIG. 9 is a block diagram of a device for processing lighting effect of a portrait in one embodiment;
FIG. 10 is a schematic diagram of an image processing circuit in one embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein in the description of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application.
Fig. 1 is an application environment diagram of a light effect processing method for a human image in an embodiment. Referring to fig. 1, the terminal 110 may use a camera thereon to perform shooting, such as scanning an object 120 in an environment in real time to obtain a frame image, and generating a shot image according to the frame image. Optionally, the camera includes a first camera module 112 and a second camera module 124, and the first camera module 112 and the second camera module 124 jointly perform shooting. The terminal 110 is provided with a plurality of photographing modes, such as a portrait mode, and during the photographing process, the object 120 can be photographed by starting different photographing modes, so that images with different effects can be obtained.
The terminal 110 may use the frame image or the generated image as an image to be processed. Identifying a portrait area in a shooting scene in the image to be processed, and further identifying the type of the portrait in the portrait area; acquiring a light effect processing model corresponding to the type of the portrait; and carrying out light effect processing on the portrait area according to the light effect processing model.
Fig. 2 is a schematic diagram of an internal structure of the terminal in one embodiment. As shown in fig. 2, the terminal 110 includes a processor, a memory, a display screen, and a camera connected through a system bus. Wherein the processor is configured to provide computing and control capabilities to support the operation of the entire terminal 110. The memory is used for storing data, programs and the like, and the memory stores at least one computer program which can be executed by the processor to realize the portrait light effect processing method suitable for the terminal 110 provided in the embodiment of the present application. The Memory may include a non-volatile storage medium such as a magnetic disk, an optical disk, a Read-Only Memory (ROM), or a Random-Access-Memory (RAM). For example, in one embodiment, the memory includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The computer program can be executed by a processor for implementing a method for processing portrait light effects provided by the following embodiments. The internal memory provides a cached execution environment for the operating system computer programs in the non-volatile storage medium. The camera comprises the first camera module and the second camera module, and both can be used for generating frame images. The display screen may be a touch screen, such as a capacitive screen or a resistive screen, and is used for displaying visual information such as a frame image or a shot image, and may also be used for detecting a touch operation applied to the display screen to generate a corresponding instruction. The terminal 110 may be a mobile phone, a tablet computer, a PDA (Personal Digital Assistant), a POS (Point of Sales mobile terminal), a vehicle-mounted computer, a wearable device, and the like.
Those skilled in the art will appreciate that the configuration shown in fig. 2 is a block diagram of only a portion of the configuration associated with the present application and does not constitute a limitation on the terminal 110 to which the present application is applied, and that a particular terminal 110 may include more or less components than those shown, or combine certain components, or have a different arrangement of components.
As shown in fig. 3, in an embodiment, a portrait lighting effect processing method is provided, which can add lighting effects suitable for different types of portraits to the image to be processed, so that the portrait is more expressive. The embodiment is mainly explained by applying the method to the terminal shown in fig. 1, and the method includes the following steps 302 to 308:
step 302: acquiring an image to be processed, and determining a portrait area in the image to be processed.
The image to be processed is an image which needs to be subjected to portrait lighting effect processing, can be an image which is generated and stored by shooting, and can also be a frame image obtained by real-time scanning through a camera in a shooting mode. Optionally, the terminal may set a portrait lighting effect switch on the display interface, and the user may trigger the portrait lighting effect switch to select the image to be processed to perform the portrait lighting effect processing, where the portrait lighting effect processing refers to adding a lighting effect for the image to be processed, and the lighting effect may be a different type of lighting effect, for example, a lighting effect in a studio may be simulated, and a portrait in the image to be processed is polished to make a good light effect.
Optionally, a portrait lighting effect processing mode is arranged on the terminal, the portrait lighting effect processing mode is an optional mode in a terminal camera mode, and the terminal can automatically perform portrait lighting effect processing on the image to be shot in the portrait lighting effect processing mode. When shooting is carried out through the terminal, if the fact that the portrait light effect processing mode is started is detected, a light effect processing instruction is generated, and the light effect processing instruction is used for indicating the terminal to carry out portrait light effect processing on the image to be processed.
Optionally, when the image to be processed is an image that has been generated and stored, the image to be processed may be post-processed by an image editor on the terminal, and the image editor may be used to edit the picture browsed by the terminal on line, for example, after an image editing mode on the terminal is opened, an image editing interface is performed, and the image may be subjected to portrait lighting effect processing. When a light effect processing request acting on an image editor is received, a light effect processing instruction is generated, and the light effect processing instruction is used for instructing a terminal to perform portrait light effect processing on an image to be processed.
Further, the terminal can extract related feature data from the image to be processed, detect whether the feature data is matched with the portrait feature, and if the feature data is matched with the portrait feature, further acquire the area of the detected portrait in the image to be processed, wherein the area is the portrait area.
Specifically, the feature data may include features such as a face, hair, clothing, a human body posture, and the like, the terminal may identify whether the image to be processed includes the face to determine a portrait area in the image to be processed, the terminal may extract image features of the image to be processed, analyze the image features through a preset portrait detection model, and determine whether the image to be processed includes the face. The image features may include shape features, spatial features, edge features, and the like, where the shape features refer to local shapes in the image to be processed, the spatial features refer to mutual spatial positions or relative directional relationships between a plurality of regions divided from the image to be processed, and the edge features refer to boundary pixels constituting two regions in the image to be processed. The terminal can also identify whether the image to be processed contains hair features, such as identifying the length, the bang, the hairstyle, the color and the like of the hair, and determine the portrait area in the image to be processed according to the identified hair features. The terminal can also identify the portrait area by identifying the characteristic parts of clothing material, clothing color and the like in the image to be processed, and can also identify whether human body gestures exist, for example, identify whether characteristic gestures such as 'scissors hand' and 'OK gesture' exist in the image, so as to determine the portrait area in the image to be processed.
Optionally, the portrait detection model may be a decision model constructed in advance through machine learning, when the portrait detection model is constructed, a large number of sample images may be obtained, the sample images include portrait images and unmanned images, the sample images may be labeled according to whether each sample image includes a portrait, the labeled sample images are used as inputs of the portrait detection model, and the portrait detection model is obtained through machine learning and training.
Step 304: identifying a portrait type within the portrait area.
The terminal is preset with various portrait types, and the portrait types can be divided into various portrait types by clustering and the like according to a preset image library. The images in the image library all contain the portrait, and the portrait types of the preset number and the portrait type of the portrait in each image are formed by clustering the portrait in the image library. And aiming at each formed portrait type, calculating the portrait characteristics corresponding to the portrait type according to the portrait characteristics of the portrait in the image belonging to the portrait type. Alternatively, the portrait characteristics may be portrait characteristics obtained by performing a weighted average calculation on the portrait characteristics of the portrait.
The terminal can analyze the image in the portrait area in the image to be processed so as to identify the matching degree of the portrait characteristics of the portrait and the portrait characteristics of each preset portrait type, and select the portrait type with the highest matching degree as the portrait type to which the portrait belongs.
Furthermore, the terminal is also provided with a portrait template characteristic, and the portrait template characteristic is a portrait characteristic used as a reference standard when the portrait in the image is subjected to light effect processing. The portrait type can be classified into different portrait types according to the mass aesthetic standard, and the different portrait types are corresponding to different portrait template characteristics. The portrait template features and the portrait features both contain one or more kinds of feature information such as the size, the proportion, the position, the posture and the like of each part on the corresponding human body preset in the portrait area. For example, the area may include a human face, five sense organs, a face, a body shape, hands, feet, etc. The terminal can analyze and extract features from a plurality of templates of different portrait types to obtain portrait template features of different portrait types.
For example, the portrait type may include a soft-type, a sexy-type, a rigid-type, an lovely-type, an artistic-type, and the like, and for each portrait type, a corresponding portrait template feature is set. And when the matching degree of the portrait characteristics in the image to be processed and the portrait template characteristics of the soft-beauty type is identified to be the highest, the portrait type in the portrait area of the image to be processed is considered to be the soft-beauty type.
Step 306: and acquiring a light effect processing model corresponding to the portrait type.
Different light effect processing is performed on different portrait types, and the corresponding relation between the portrait type and the light effect processing model is established in the embodiment. One of the portrait types corresponds to one of the light effect processing models, and optionally, multiple light effect processing modes can be provided for the same portrait type for a user to select.
And further, determining a light effect processing model which should be selected for the current image to be processed according to the preset corresponding relation between the portrait type and the light effect processing model. The light effect processing model can be understood as an adjusting parameter of an image to be processed, the parameter can be exposure, contrast, highlight, shadow, level, saturation, color temperature and the like, and the image with better expressive force can be obtained for different portrait types by adjusting the parameter of the image to be processed.
Specifically, when the figure type in the image to be processed is identified to be a soft and beautiful type, a corresponding light effect processing model is selected according to the illumination effect suitable for the soft and beautiful type figure; when the figure type in the image to be processed is identified to be a sexy type, selecting a corresponding light effect processing model according to the illumination effect of the character with the sexy type; it is understood that the light effect processing model determination method in the embodiment is not limited to the above-mentioned determination method, and the light effect processing model may also be determined according to other different portrait types, such as a positive rigid type, an entertaining type, an artistic type, and the like, and the description of the embodiment is not repeated.
Step 308: and carrying out light effect processing on the portrait area according to the light effect processing model.
The lighting effects include, but are not limited to, lighting type, lighting intensity, lighting brightness, and lighting color. According to the embodiment, the light effect processing is carried out on the portrait area of the image to be processed according to the determined light effect processing model. Specifically, the light effect processing manner for the portrait area may include adding different types of light effects, improving the center position of the portrait area, improving the brightness of the image, adjusting the color of the image, adding a light distribution effect, and the like. The lighting type can be contour lighting, stage lighting, studio lighting, soft light and the like, the color can be warm tone, cold tone and the like, and the light distribution effect can be triangle light, cloudy sunlight, annular light and the like.
According to the portrait light effect processing method, the to-be-processed image is obtained, the portrait area in the to-be-processed image is determined, the portrait type in the portrait area is identified, the light effect processing model corresponding to the portrait type is obtained, the light effect processing model is used for performing light effect processing on the portrait area according to the light effect processing model, the light effect processing model suitable for the portrait type can be selected according to different portrait types, the portrait has higher expressive force, the process of performing light effect processing on the portrait by a user is simplified, and the user experience is improved.
In one embodiment, as shown in fig. 4, the identifying the portrait type in the portrait area, that is, step 304, includes:
step 402: and extracting the portrait characteristics of the portrait area, and matching the portrait characteristics with the portrait template characteristics.
If the terminal detects that the image to be processed contains the portrait, the portrait area can be determined, the portrait characteristics of the portrait area are extracted, and the portrait characteristics are matched with the preset portrait template characteristics. The portrait characteristics and the portrait template characteristics comprise but are not limited to human face characteristics, facial characteristics and body characteristics, the human face characteristics can comprise facial features such as 'three-family five-eye', willow leaf eyebrow, peach blossom eye, cherry mouth and the like, and the human face characteristics can also comprise facial features such as Chinese face, melon seed face, round face and the like; facial features may include facial expressions such as smiling, laughing, crying, sadness, seriousness, and familiarity; the physical characteristics may include physical characteristics such as a sexually sensitive curve, an inverted triangle, a golden ratio, etc.
Alternatively, the portrait features may be composed of feature points, which may include the shape, position, and contour of the five sense organs of the portrait, and the like. The portrait features can be described by coordinate values of each feature point, wherein the coordinate values can be represented by pixel positions corresponding to the feature points, for example, the coordinate values of the feature points are the X-th row and the Y-th column of the corresponding pixel positions.
The terminal can identify the portrait type according to the portrait characteristics, and the portrait type can comprise a soft and beautiful type, a sexy type, a rigid and male type, an lovely type, an artistic type and the like. The terminal can construct portrait template characteristics in advance, and the terminal can analyze the portrait characteristics through the portrait template characteristics to obtain the portrait type of the image to be processed. The mobile terminal can depict the portrait template characteristics according to the portrait images containing different portrait types as sample images. The terminal may mark the portrait type included in each sample image, for example, the type of the soft-beauty type is marked as 1, the type of the sexy type is marked as 2, the type of the positive-stiffness type is marked as 3, and the like, and may also mark the portrait in other manners, which is not limited thereto.
Step 404: and determining the portrait type of the portrait in the portrait area according to the matching result.
Specifically, when the portrait type is identified, the terminal may compare the extracted portrait features with the portrait template features, and calculate the similarity between the portrait features and the portrait template features mapped by each portrait type. If the similarity between the portrait characteristics and the portrait template characteristics is larger than the similarity threshold, the terminal can determine that the portrait type of the image to be processed is the type corresponding to the portrait template characteristics. For example, if the similarity between the portrait features and the portrait template features corresponding to the soft-beauty type is greater than the similarity threshold value of 80%, it is determined that the portrait type is the soft-beauty type.
According to the portrait lighting effect processing method provided by the embodiment, the portrait features of the portrait area are extracted, and the portrait features are matched with the portrait template features, so that the portrait type to which the portrait belongs in the portrait area is determined, the identification accuracy rate of the portrait type can be improved, and a better portrait lighting effect processing effect can be brought by accurately identifying the portrait type.
In one embodiment, the portrait features of the portrait area are extracted and matched with the portrait template features, that is, step 402 may further include: acquiring three-dimensional portrait characteristics corresponding to a portrait in the image to be processed by emitting structured light; and when the similarity between the three-dimensional actual information and the three-dimensional reference position information is greater than a preset threshold value, determining that the portrait characteristics are matched with the portrait template characteristics.
The portrait template features comprise three-dimensional reference position information of a preset organ, and the three-dimensional portrait features comprise three-dimensional actual position information of a preset part. The terminal can emit the structured light by calling the camera in the process of generating the picture to be processed so as to identify the distance between each pixel in the portrait area on the shot image and the camera, and the three-dimensional portrait characteristics of the portrait in the picture to be processed can be obtained according to the distance. Compared with the two-dimensional portrait characteristics such as the size of the parts and the distance between the parts presented by the common picture, the three-dimensional portrait characteristics and the portrait template characteristics further comprise three-dimensional position information of each preset part corresponding to the portrait, namely the three-dimensional position information of each part. For example, the distance between each part on the portrait and the reference plane can be obtained by taking a certain reference plane as a reference, and three-dimensional position information of each part, such as the height of the nose bridge, the depth of the eye socket, the thickness of the body and the like, can be represented according to the distance. Alternatively, the emitted structured light may be infrared structured light. And when the similarity between the three-dimensional actual information and the three-dimensional reference position information is greater than a preset threshold value, determining that the portrait characteristics are matched with the portrait template characteristics, and further determining the portrait type of the portrait area in the image to be processed.
In one embodiment, as shown in fig. 5, the portrait light effect processing method further includes a step of portrait template feature generation, including:
step 502: and acquiring a corresponding reference image set aiming at each portrait type.
In this embodiment, the reference image set refers to a set of reference images used for training the portrait template features. Each reference picture set includes a plurality of reference pictures. For each reference image set, a relationship between the reference image set and one of the portrait types is established. And the image types contained in the reference images in the reference image set corresponding to a certain image type all belong to the certain image type. For each portrait type, the terminal can acquire a corresponding reference image set according to a pre-established corresponding relationship.
Step 504: a portrait reference feature within each reference image in the set of reference images is obtained.
The portrait type of the portrait in the reference image is marked as the portrait type corresponding to the reference image set to which the image belongs. The figure in the reference image is a preselected figure that meets mass aesthetic criteria, such as a figure that may be a star. The portrait reference features may include feature data that embodies one or more of the size, color, location, and depth of various parts on the portrait.
Step 506: and generating portrait template features corresponding to the portrait types according to the portrait reference features.
According to the acquired portrait reference features of each portrait type, averaging operation can be carried out on the portrait reference features representing the same parts so as to calculate the portrait template features corresponding to the portrait types. Alternatively, a training model for the portrait template features may be preset, and the portrait template features may be generated by importing the portrait template features of the same portrait type into the training model for training.
In this embodiment, the portrait template features are generated by the above method, so that the accuracy of the portrait template features can be further improved.
In one embodiment, as shown in fig. 6, the light effect processing on the portrait area according to the light effect processing model, that is, step 308, includes:
step 602: and obtaining the adjusting range and the adjusting parameter of the light effect under the determined light effect processing model.
The adjustment range can be understood as a selected processing area in the image to be processed, the processing area can be determined by selecting preset pixel points, or different areas can be divided by analyzing the color difference of the pixel area, and then the pixel area needing to be processed is selected as the processing area. Alternatively, the treatment region may also be a pre-configured region having a particular shape, such as a circular region, an elliptical region, a triangular region, an annular region, or the like. The adjustment parameters may include exposure, white balance, contrast, highlight, shadow, gradation, saturation, color temperature, and the like. Different light effect processing models are preset with different adjusting ranges and adjusting parameters correspondingly. Optionally, the light effect processing model may further include a light effect simulation algorithm, and the light effect simulation algorithm is used to add simulated light effects to the image to be processed.
Step 604: and adding an illumination effect to the image to be processed according to the adjusting range and the adjusting parameters.
The post-processing is carried out on the image to be processed through the preset adjusting parameters, and the lighting effect can be added to the image, wherein the lighting effect comprises but is not limited to illumination type, illumination intensity, illumination brightness and illumination color.
For example, if the character-type figure is added with a light effect capable of fully showing the figure effect, parameters such as color, exposure and contrast of the image are adjusted according to the adjustment range and the adjustment parameters when the character type is the character-type figure, so that light effects with concentrated light, bright contrast and full color are added to the image, and the light effects are focused on the figure body to achieve the effect of highlighting the figure body. And for example, when the portrait type in the image to be processed is recognized to be a soft and beautiful type, adding the illumination effect of a soft light to the image to be processed. And adding the illumination effect of the contour light to the image to be processed when the type of the figure in the image to be processed is identified to be the positive rigid type so as to achieve the effect of highlighting the figure contour. It is understood that the present embodiment does not limit the above-listed effects after the light effect processing.
According to the portrait light effect processing method, light effects are added to the image to be processed according to different types of portraits, the light effects with different effects can be correspondingly added according to the characteristics of the different types of portraits, and expressive force and infectivity of the portraits are improved.
In one embodiment, as shown in fig. 7, the light effect processing model may be a two-dimensional gaussian distribution function, and the light effect processing on the portrait area according to the light effect processing model further includes:
step 702: a highlight location is obtained.
The terminal may acquire a highlight position, which may refer to a highlight center position where the image to be processed is highlighted, and the highlight position may be considered as a position where the intensity of the added light effect is highest. With the highlight location as the center, the intensity of the light effect added to the periphery of the highlight location may gradually decrease. Alternatively, the highlight location may be a fixed point preset by the terminal. For example, the highlight location may be the center point of the image to be processed. The terminal can obtain the length and the width of the image to be processed, and determine the center point of the image to be processed according to the length and the width, and the position of the center point of the image to be processed can be the middle value of the width and the middle value of the length. If the width of the image to be processed is W and the length is L, the position of the center point can be represented by (L/2, W/2). The highlight position may be other preset fixed points, but is not limited thereto.
Alternatively, the highlight position may be the center position of the portrait area in the image to be processed. After the terminal determines the portrait area, the center position of the portrait area can be obtained and used as the brightening position. The highlight location may also be a specific portion of the portrait area, for example, the face area of the portrait may be the highlight location. After the terminal determines the portrait area, the terminal can extract the feature points of the portrait area, and the feature points can be used for describing the face features, the body features and the like of the portrait area. The terminal can determine the face region according to the feature points, select the central point of the face region and take the central point of the face region as a brightening position. The specific part in the portrait area is selected as the brightening position, so that the light effect added to the image to be processed is better.
Alternatively, the highlight position may be a position selected by the user himself, and the user may select a desired highlight position by touching an arbitrary position of the image to be processed. The terminal can receive touch operation of a user, acquire a touch position according to the received touch operation, and use the touch position as a brightening position. The user can select the brightening position according to actual requirements, the requirements of different users are met, and the added light effect can be effectively improved. It will be appreciated that the highlight locations may be obtained in other ways, and are not limited to the ones described above.
Step 704: and determining the distribution center of the light effect processing model according to the brightening position, and determining the distribution amplitude according to the brightness enhancement coefficient in the light effect processing model.
In this embodiment, the light effect processing model is a two-dimensional gaussian distribution function, and the terminal may determine the distribution center of the light effect processing model according to the brightness enhancement position and determine the distribution amplitude according to the brightness enhancement coefficient. The distribution center of the light effect processing model can be used for determining the position of the light effect processing model, the terminal can use the brightening position as the distribution center of the light effect processing model, and the distribution center can be the highest point in the two-dimensional Gaussian distribution function. The distribution amplitude of the light effect processing model can be used to describe the shape of the two-dimensional gaussian distribution function. The shape of the light effect processing model may be "thin and tall" the larger the brightness enhancement factor is, and the shape of the light effect processing model may be "thin and small" the smaller the brightness enhancement factor is.
In one embodiment, the two-dimensional gaussian distribution function of the light effect processing model can be represented by equation (1):
wherein z represents a pixel point in the image to be processed; p (z) represents the brightness enhancement amplitude when the pixel point is subjected to the brightness enhancement treatment; d is a standard deviation, the brightness enhancement coefficient can influence the size of d, the larger the brightness enhancement coefficient is, the smaller d can be, and the smaller the brightness enhancement coefficient is, the larger d can be; μ denotes the center of distribution of the light effect processing model, which may alternatively be the acquired highlight position. In the light effect processing model, pixel points at different positions of an image to be processed have different corresponding brightness enhancement amplitudes, and the pixel points closer to the distribution center mu have stronger brightness enhancement amplitudes, and the pixel points farther from the distribution center mu have smaller brightness enhancement amplitudes.
Step 706: and constructing a two-dimensional Gaussian distribution function according to the distribution center and the distribution amplitude.
The terminal can construct a two-dimensional Gaussian distribution function according to the determined distribution center and the distribution amplitude, and brighten the image to be processed according to the constructed two-dimensional Gaussian distribution function.
FIG. 8 is a diagram of a light effect processing model in an embodiment. As shown in fig. 8, the light effect processing model is a two-dimensional gaussian distribution function, and both edge distributions of the two-dimensional gaussian distribution function are in the form of one-dimensional normal distribution. In the light effect processing model, an x axis and a y axis can be used for representing position coordinates of pixel points in an image to be processed, and a z axis can be used for representing brightness enhancement amplitude of the pixel points. The distribution center 402 is a pixel point with position coordinates of (x0, y0), the terminal can acquire the highlight position and use the highlight position as the distribution center 402, and the distribution center 402 is a point with the maximum brightness enhancement amplitude in the light effect processing model. The brightness enhancement coefficient can be used for influencing the distribution amplitude of the light effect processing model, and the larger the brightness enhancement coefficient is, the larger the brightness enhancement amplitude of the pixel points in the light effect processing model is, and the larger the brightness of the pixel points is; the smaller the brightness enhancement coefficient is, the smaller the brightness enhancement amplitude of the pixel points in the light effect processing model is, and the smaller the brightness improved by the pixel points is.
Step 708: and adding an illumination effect to the image to be processed according to the two-dimensional Gaussian distribution function.
The terminal can calculate the brightness enhancement amplitude of the pixel points according to the two-dimensional Gaussian distribution function, and the brightness enhancement amplitude is multiplied by the original brightness values of the pixel points, so that the brightness values after the brightness enhancement processing can be calculated. The terminal can perform brightening treatment on the pixel points according to the calculated brightness values, and adds light effects to the image to be processed.
In this embodiment, the image to be processed can be processed by the two-dimensional gaussian distribution function to add the light effect, and the brightness enhancement amplitudes of the pixel points at different positions are different, so that the image has a better light effect, and the added light effect is more real and natural.
It should be understood that although the various steps in the flow charts of fig. 3-7 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 3-7 may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternating with other steps or at least some of the sub-steps or stages of other steps.
As shown in fig. 9, in one embodiment, there is provided a portrait light effect processing apparatus, the apparatus including: an area identification module 910, a type identification module 920, a model acquisition module 930 and a light effect processing module 940.
The region identification module 910 is configured to acquire an image to be processed and determine a portrait region in the image to be processed.
And a type identification module 920, configured to identify a type of the portrait in the portrait area.
A model obtaining module 930, configured to obtain a light effect processing model corresponding to the portrait type.
And a light effect processing module 940, configured to perform light effect processing on the portrait area according to the light effect processing model.
According to the portrait light effect processing device, the region identification module 910 is used for acquiring an image to be processed, a portrait region in the image to be processed is determined, the type identification module 920 is used for identifying the type of a portrait in the portrait region, the model acquisition module 930 is used for acquiring a light effect processing model corresponding to the type of the portrait, the light effect processing module 940 is used for performing light effect processing on the portrait region according to the light effect processing model, the light effect processing model suitable for the type of the portrait can be selected according to different types of the portrait, the portrait has better expressive force, the process of performing light effect processing on the portrait by a user is simplified, and the user experience is improved.
In one embodiment, the type identification module 920 is further configured to extract portrait features of the portrait area, and match the portrait features with portrait template features; and determining the portrait type of the portrait in the portrait area according to the matching result.
In one embodiment, the type identification module 920 is further configured to obtain three-dimensional portrait features corresponding to the portrait in the image to be processed by emitting structured light; the three-dimensional portrait characteristics comprise three-dimensional actual position information of a preset part; and when the similarity between the three-dimensional actual information and the three-dimensional reference position information is greater than a preset threshold value, determining that the portrait characteristics are matched with the portrait template characteristics.
In one embodiment, the model obtaining module 930 is further configured to obtain an adjustment range and an adjustment parameter for the light effect under the determined light effect processing model; and adding an illumination effect to the image to be processed according to the adjusting range and the adjusting parameters.
In one embodiment, the model retrieval module 930 is further configured to retrieve the highlight position; determining the distribution center of the light effect processing model according to the brightening position, and determining the distribution amplitude according to the brightness enhancement coefficient in the light effect processing model; constructing a two-dimensional Gaussian distribution function according to the distribution center and the distribution amplitude; and adding an illumination effect to the image to be processed according to the two-dimensional Gaussian distribution function.
In one embodiment, the portrait light effect processing apparatus further includes a template generation module, configured to obtain, for each portrait type, a corresponding reference image set; acquiring a character reference feature in each reference image in the reference image set; and generating a portrait template characteristic corresponding to the portrait type according to the character reference characteristic.
The division of each module in the above-mentioned portrait light effect processing apparatus is only used for illustration, in other embodiments, the signal processing apparatus may be divided into different modules as required to complete all or part of the functions of the above-mentioned portrait light effect processing apparatus.
For specific definition of the portrait light effect processing apparatus, reference may be made to the above definition of the portrait light effect processing method, which is not described herein again. All or part of each module in the portrait light effect processing device can be realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent of a processor in the terminal, and can also be stored in a memory in the terminal in a software form, so that the processor can call and execute operations corresponding to the modules.
The modules in the portrait light effect processing apparatus provided in the embodiments of the present application may be implemented in the form of a computer program. The computer program may be run on a terminal or a server. The program modules constituted by the computer program may be stored on the memory of the terminal or the server. The computer program, when executed by a processor, implements the steps of the method for processing a portrait light effect described in the embodiments of the present application.
The embodiment of the application also provides a computer readable storage medium. One or more non-transitory computer-readable storage media containing computer-executable instructions that, when executed by one or more processors, cause the processors to perform the portrait light effect processing methods as described in the embodiments above.
The embodiment of the application also provides a computer program product. A computer program product comprising instructions which, when run on a computer, cause the computer to perform the method of portrait light effect processing described in the embodiments above.
The embodiment of the application also provides the terminal equipment. The terminal device includes therein an Image Processing circuit, which may be implemented using hardware and/or software components, and may include various Processing units defining an ISP (Image Signal Processing) pipeline. FIG. 10 is a schematic diagram of an image processing circuit in one embodiment. As shown in fig. 10, for convenience of explanation, only aspects of the image processing technology related to the embodiments of the present application are shown.
As shown in fig. 10, the image processing circuit includes an ISP processor 1040 and control logic 1050. The image data captured by the imaging device 1010 is first processed by the ISP processor 1040, and the ISP processor 1040 analyzes the image data to capture image statistics that may be used to determine and/or control one or more parameters of the imaging device 1010. The imaging device 1010 may include a camera having one or more lenses 1012 and an image sensor 1014. The image sensor 1014 may include an array of color filters (e.g., Bayer filters), and the image sensor 1014 may acquire light intensity and wavelength information captured with each imaging pixel of the image sensor 1014 and provide a set of raw image data that may be processed by the ISP processor 1040. The sensor 1020 (e.g., a gyroscope) may provide parameters of the acquired image processing (e.g., anti-shake parameters) to the ISP processor 1040 based on the type of sensor 1020 interface. The sensor 1020 interface may utilize an SMIA (Standard Mobile Imaging Architecture) interface, other serial or parallel camera interfaces, or a combination of the above.
In addition, the image sensor 1014 may also send raw image data to the sensor 1020, the sensor 1020 may provide the raw image data to the ISP processor 1040 based on the type of interface of the sensor 1020, or the sensor 1020 may store the raw image data in the image memory 1030.
The ISP processor 1040 processes the raw image data pixel by pixel in a variety of formats. For example, each image pixel may have a bit depth of 8, 10, 12, or 14 bits, and ISP processor 1040 may perform one or more image processing operations on the raw image data, gathering statistical information about the image data. Wherein the image processing operations may be performed with the same or different bit depth precision.
Upon receiving raw image data from image sensor 1014 interface or from sensor 1020 interface or from image memory 1030, ISP processor 1040 may perform one or more image processing operations, such as temporal filtering. The processed image data may be sent to image memory 1030 for additional processing before being displayed. ISP processor 1040 may also receive processed data from image memory 1030 for image data processing in the raw domain and in the RGB and YCbCr color spaces. The processed image data may be output to a display 1080 for viewing by a user and/or for further Processing by a Graphics Processing Unit (GPU). Further, the output of ISP processor 1040 can also be sent to image memory 1030, and display 1080 can read image data from image memory 1030. In one embodiment, image memory 1030 may be configured to implement one or more frame buffers. In addition, the output of the ISP processor 1040 may be transmitted to the encoder/decoder 1070 in order to encode/decode image data. The encoded image data may be saved and decompressed before being displayed on the display 1080 device.
The steps of the ISP processor 1040 processing the image data include: the image data is subjected to VFE (Video Front End) Processing and CPP (Camera Post Processing). The VFE processing of the image data may include modifying the contrast or brightness of the image data, modifying digitally recorded lighting status data, performing compensation processing (e.g., white balance, automatic gain control, gamma correction, etc.) on the image data, performing filter processing on the image data, etc. CPP processing of image data may include scaling an image, providing a preview frame and a record frame to each path. Among other things, the CPP may use different codecs to process the preview and record frames. The image data processed by the ISP processor 1040 may be sent to the light effect processing module 1060 for light effect processing of the image before being displayed. The light effect processing module 1060 light effect processing on the image data may include: clear lighting, cloudy lighting, natural light, studio light, stage light, contour light, and the like. The light effect Processing module 1060 can be a Central Processing Unit (CPU), a GPU, a coprocessor, or the like in the mobile terminal. The data processed by the light effect processing module 1060 may be transmitted to the encoder/decoder 1070 in order to encode/decode the image data. The encoded image data may be saved and decompressed before being displayed on the display 1080 device. The light effect processing module 1060 can also be located between the encoder/decoder 1070 and the display 1080, that is, the light effect processing module 1060 performs light effect processing on the imaged image. The encoder/decoder 1070 may be a CPU, GPU, coprocessor, or the like in a mobile terminal.
The statistics determined by the ISP processor 1040 may be sent to the control logic 1050 unit. For example, the statistical data may include image sensor 1014 statistics such as auto-exposure, auto-white balance, auto-focus, flicker detection, black level compensation, lens 1012 shading correction, and the like. Control logic 1050 may include a processor and/or microcontroller that executes one or more routines (e.g., firmware) that may determine control parameters of imaging device 1010 and ISP processor 1040 based on the received statistical data. For example, the control parameters of the imaging device 1010 may include sensor 1020 control parameters (e.g., gain, integration time for exposure control), camera flash control parameters, lens 1012 control parameters (e.g., focal length for focusing or zooming), or a combination of these parameters. The ISP control parameters may include gain levels and color correction matrices for automatic white balance and color adjustment (e.g., during RGB processing), and lens 1012 shading correction parameters.
The portrait light effect processing method as described above can be implemented using the image processing technology in fig. 10. By the portrait light effect processing method, the light effect processing model suitable for the portrait type can be selected according to different portrait types, so that the portrait has higher expressive force, the process of the user for the light effect processing of the portrait is simplified, and the user experience is improved.
Any reference to memory, storage, database, or other medium used herein may include non-volatile and/or volatile memory. Suitable non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM), which acts as external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), Enhanced SDRAM (ESDRAM), synchronous Link (Synchlink) DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and bus dynamic RAM (RDRAM).
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present application. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A portrait light effect processing method is characterized by comprising the following steps:
acquiring an image to be processed, and determining a portrait area of the image to be processed;
identifying portrait types in the portrait area, wherein the portrait types comprise a soft-beauty type, a sexy type, a rigid-male type, an lovely type or an artistic type;
acquiring a light effect processing model corresponding to the portrait type, wherein the light effect processing model is a two-dimensional Gaussian distribution function;
obtaining the adjusting range and adjusting parameters of the lighting effect under the determined lighting effect processing model;
processing the image to be processed by adding the illumination effect according to the adjustment range and the adjustment parameter; wherein the illumination effect comprises an illumination type, and the illumination type comprises at least one of a lamplight type and a light distribution type.
2. The method of claim 1, wherein the identifying the type of portrait within the portrait area comprises:
extracting portrait characteristics of the portrait area, and matching the portrait characteristics with portrait template characteristics; wherein the portrait characteristics and the portrait template characteristics comprise at least one of facial characteristics, facial characteristics and body characteristics;
and determining the portrait type of the portrait in the portrait area according to the matching result.
3. The method of claim 2, wherein the portrait template features include three-dimensional reference location information of a predetermined organ;
the extracting the portrait characteristics of the portrait area and matching the portrait characteristics with the portrait template characteristics comprises:
acquiring three-dimensional portrait characteristics corresponding to the portrait in the image to be processed; the three-dimensional portrait characteristics comprise actual position information of a preset part;
and when the similarity between the actual position information and the three-dimensional reference position information is greater than a preset threshold value, determining that the portrait characteristics are matched with the portrait template characteristics.
4. The method according to claim 1, wherein prior to said obtaining a light effect processing model corresponding to said portrait type, further comprising:
and establishing a corresponding relation between the portrait type and the light effect processing model.
5. The method of claim 1, wherein said light effect processing said portrait area according to said light effect processing model, further comprises:
acquiring a brightening position;
determining the distribution center of the light effect processing model according to the brightening position, and determining the distribution amplitude according to the brightness enhancement coefficient in the light effect processing model;
constructing a two-dimensional Gaussian distribution function according to the distribution center and the distribution amplitude;
and adding an illumination effect to the image to be processed according to the two-dimensional Gaussian distribution function.
6. The method according to any one of claims 1 to 5, further comprising:
acquiring a corresponding reference image set aiming at each portrait type;
acquiring a character reference feature in each reference image in the reference image set;
and generating a portrait template characteristic corresponding to the portrait type according to the character reference characteristic.
7. A portrait light effect processing apparatus, comprising:
the region identification module is used for acquiring an image to be processed and determining a portrait region in the image to be processed;
the type identification module is used for identifying the portrait type in the portrait area, and the portrait type comprises a soft type, a sexy type, a rigid type, an lovely type or an artistic type;
the model acquisition module is used for acquiring a light effect processing model corresponding to the portrait type, and the light effect processing model is a two-dimensional Gaussian distribution function;
the light effect processing module is used for acquiring the adjusting range and the adjusting parameters of the light effect under the determined light effect processing model; processing the image to be processed by adding the illumination effect according to the adjustment range and the adjustment parameter; wherein the illumination effect comprises an illumination type, and the illumination type comprises at least one of a lamplight type and a light distribution type.
8. The apparatus of claim 7, wherein the type recognition module is further configured to extract portrait features of the portrait area and match the portrait features with portrait template features, wherein the portrait features and portrait template features include at least one of facial features, and body features; and determining the portrait type of the portrait in the portrait area according to the matching result.
9. A terminal comprising a memory and a processor, the memory having stored therein a computer program which, when executed by the processor, causes the processor to carry out the steps of the method according to any one of claims 1 to 6.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 6.
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| CN109584149B (en) * | 2018-11-28 | 2023-03-07 | 东软集团股份有限公司 | Image processing method, device, equipment and computer readable storage medium |
| CN111476304B (en) * | 2020-04-10 | 2023-09-05 | 国网冀北电力有限公司承德供电公司 | Image data processing method and device |
| CN113489901B (en) * | 2021-06-30 | 2023-04-28 | 维沃移动通信（杭州）有限公司 | Shooting method and device thereof |
| CN115705614A (en) * | 2021-08-05 | 2023-02-17 | 北京小米移动软件有限公司 | Image processing method, image processing device, electronic equipment and storage medium |
| US11770621B2 (en) | 2021-09-30 | 2023-09-26 | Snap Inc. | Customized image reprocessing system using a machine learning model |
| WO2023055817A1 (en) * | 2021-09-30 | 2023-04-06 | Snap Inc. | Customized image reprocessing system |
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