Image processing method, image processor and electronic device

Abstract

The present application provides an image processing method, an image processor and an electronic device, wherein, by acquiring a current scene image of a shooting scene, determining a target object area that needs to be interpolated from multiple object areas of the current scene image, and acquiring a first motion vector corresponding to the target object area, and interpolating the interpolated image content of the target object area according to the first motion vector, and based on the interpolated image content of the target object area and the image content of the non-target object area, obtaining an interpolated image of the current scene image. In this way, the present application can not only increase the imaging frame rate of the electronic device by performing actual interpolation processing on a part of the image, but also will not cause a large increase in the power consumption of the electronic device.

Description

Technical Field

[0001] The present application relates to the field of image processing technology, and in particular to an image processing method, an image processor and an electronic device. Background Art

[0002] At present, the screen refresh rates of electronic devices such as smart phones and tablets are getting higher and higher, which can provide users with better display effects. However, the display effect of the screen is not only related to the refresh rate of the screen itself, but also to the display content to a greater extent. For example, an electronic device can shoot a shooting scene, and using the screen of the electronic device, the shooting scene can be previewed in real time, and the video of the recorded shooting scene can be played back. However, the frame rate of the imaging of the electronic device is physically limited by the camera, and the frame rate of the camera determines the frame rate of the imaging of the electronic device. Summary of the invention

[0003] The embodiments of the present application provide an image processing method, an image processor, and an electronic device, which can improve the frame rate of imaging of the electronic device.

[0004] The present application discloses an image processing method, comprising:

[0005] Acquire a current scene image of a shooting scene, and determine a target object area that needs to be interpolated from multiple object areas in the current scene image;

[0006] Acquire a first motion vector corresponding to the target object area;

[0007] Obtaining interpolated frame image content of the target object area according to the first motion vector interpolation;

[0008] An interpolated frame image of the current scene image is obtained based on the interpolated frame image content of the target object area and the image content of the non-target object area.

[0009] The present application also discloses an image processor, comprising:

[0010] A data interface unit, used to obtain a current scene image of a shooting scene;

[0011] a data processing unit, configured to determine a target object region that needs to be interpolated from a plurality of object regions of the current scene image, and to obtain a first motion vector corresponding to the target object region; and

[0012] The first motion vector is transmitted to an application processor, so that the application processor interpolates the interpolated image content of the target object area according to the first motion vector, and obtains the interpolated image of the current scene image based on the interpolated image content of the target object area and the image content of the non-target object area.

[0013] The present application also discloses an electronic device, comprising:

[0014] A camera, used to collect a current scene image of a shooting scene;

[0015] an image processor, configured to determine a target object region that needs to be interpolated from a plurality of object regions in the current scene image, and obtain a first motion vector corresponding to the target object region; and

[0016] An application processor is used to obtain interpolated image content of the target object area according to the first motion vector interpolation, and to obtain an interpolated image of the current scene image based on the interpolated image content of the target object area and the image content of the non-target object area.

[0017] The present application also discloses an electronic device, including a processor and a memory, wherein the memory stores a computer program, and is characterized in that the processor executes the image processing method provided in the present application by loading the computer program.

[0018] The present application performs actual frame insertion processing on a part of the image, which not only increases the imaging frame rate of the electronic device, but also does not cause a significant increase in the power consumption of the electronic device. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for describing the embodiments.

[0020] Figure 1 A schematic diagram of the structure of an image processor provided in an embodiment of the present application.

[0021] Figure 2 A schematic diagram of frame insertion processing in an embodiment of the present application.

[0022] Figure 3 This is an example diagram of selecting feature points in an embodiment of the present application.

[0023] Figure 4 Another schematic diagram of performing frame insertion processing in an embodiment of the present application.

[0024] Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0025] Figure 6 Another schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0026] Figure 7 A flowchart of an image processing method provided in an embodiment of the present application.

[0027] Figure 8 A flowchart of an image processing method provided in an embodiment of the present application. DETAILED DESCRIPTION

[0028] Please refer to Figure 1 , Figure 1 The first structural diagram of the image processor 100 provided in the embodiment of the present application. The image processor 100 may include a data interface unit 110 and a data processing unit 120, wherein:

[0029] The data interface unit 110 is used to obtain the current scene image of the shooting scene;

[0030] The data processing unit 120 is used to determine a target object region that needs to be interpolated from multiple object regions of the current scene image, and obtain a first motion vector corresponding to the target object region; and

[0031] The first motion vector is transmitted to the application processor, so that the application processor interpolates to obtain the interpolated image content of the target object area according to the first motion vector, and obtains the interpolated image of the current scene image based on the interpolated image content of the target object area and the image content of the non-target object area.

[0032] It should be noted that the image processor 100 provided in the present application can be configured in an electronic device having a camera and an application processor, and is used to perform frame insertion processing on an image captured by the camera. Figure 2 , interpolation processing can be generally understood as: inserting one or more frames of images related to the image content of adjacent images between adjacent images to improve the continuity of the image content. For example, assuming that the actual shooting frame rate of the camera is 30 frames / second, through interpolation processing, the frame rate of the captured image can be increased from 30 frames / second to 60 frames / second, or even higher.

[0033] Among them, the electronic device can be a mobile electronic device with a camera such as a smart phone, tablet computer, PDA, laptop computer, etc., or it can be a fixed electronic device with a camera such as a desktop computer, television, etc., and this application does not make any specific restrictions on this.

[0034] The embodiment of the present application does not specifically limit the type and number of cameras configured for the electronic device 100, and can be configured by ordinary technicians in the field according to actual needs. For example, using the shooting frame rate as the classification standard for camera types, the camera configured for the electronic device can be a low frame rate camera (the shooting frame rate is usually within 100 frames / second, such as 30 frames / second, 60 frames / second, etc.), or a high frame rate camera (the shooting frame rate is usually above 100 frames / second, such as 120 frames / second).

[0035] Generally, a camera consists of multiple parts, including lens, motor and image sensor, etc. Among them, the lens is used to project the external light signal to the image sensor; the image sensor is used to perform photoelectric conversion on the light signal projected by the lens, converting the light signal into a usable electrical signal to obtain the original image data; and the motor is used to drive the lens to move, thereby adjusting the distance between the lens and the image sensor to meet the imaging formula (also called lens imaging formula, Gaussian imaging formula, etc.), so that the image is clear.

[0036] The shooting scene of a camera can be understood as the area that the camera is aimed at after being enabled, that is, the area where the camera can convert light signals into corresponding image data. For example, after an electronic device enables the camera according to a user operation, if the user controls the camera of the electronic device to aim at an area including a certain object, the area including the object is the shooting scene of the camera.

[0037] In the embodiment of the present application, the data interface unit 110 is used to obtain the current scene image of the shooting scene for subsequent frame insertion processing. Exemplarily, the image processor 100 is directly connected to the camera through the data interface unit 110, and accordingly, the data interface unit 110 directly obtains the current scene image of the shooting scene collected by it from the camera. It should be noted that in the embodiment of the present application, there is no specific restriction on the entity type of the data interface unit 110, including but not limited to the mobile industry processor interface (Mobile Industry Processor Interface, MIPI), PCI-E interface, etc.

[0038] As described above, after the data interface unit 110 obtains the current scene image of the shooting scene from the camera, the data processing unit 120 determines the target object area that needs to be interpolated from multiple object areas of the current scene image according to the configured object determination strategy. The configuration of the aforementioned object determination strategy is not specifically limited here, and can be configured by those skilled in the art according to actual needs.

[0039] For example, for a shooting scene, there may be various objects, such as people, animals, plants, and buildings. When a user faces such a shooting scene, he usually cannot pay attention to all the objects in it, but only pays attention to the objects of interest. For example, when a user takes a portrait, he usually pays attention to the people in the shooting scene. Therefore, the object determination strategy can be configured as: the object area of ​​interest to the user among multiple object areas is determined as the target object area that needs to be interpolated. Among them, there is no specific limitation on how to identify the object area of ​​interest to the user, and a suitable identification method can be configured by those skilled in the art according to actual needs.

[0040] It should be noted that the purpose of interpolation is to improve the continuity of image content, and whether the image content is continuous depends on whether the motion of objects in adjacent images is continuous. Therefore, after determining the target object area that needs to be interpolated from multiple object areas in the current scene image, the data processing unit 120 further obtains a motion vector corresponding to the target object area, recorded as a first motion vector, which is used to describe the motion direction and motion speed of the object in the target object area.

[0041] Exemplarily, for a target object region, the data processing unit 120 analyzes and calculates a first motion vector of the target object region according to a position difference between the target object region in a current scene image and an adjacent previous scene image or a next scene image.

[0042] To improve the efficiency of obtaining the first motion vector, feature points may be selected from the target object region, and the feature points may be used to represent the target object region to obtain the first motion vector. The selection of feature points may be determined based on the characteristics of different objects.

[0043] For example, you can select the vertex positions of certain objects as feature points, such as a person's hands or head; you can select the edges of certain objects as feature points, such as the edge of a car.

[0044] It should be noted that the definition of feature points in the embodiments of the present application does not refer to a single pixel point, but to all pixel points in a specific relatively fixed small area, such as the fingertips of fingers, ears of the head, vertices of moving objects, etc. All pixel points corresponding to these areas are regarded as feature points.

[0045] For example, please refer to Figure 3 , for the current scene image, the regions where the head, hands, torso, and legs are located are all determined as target object regions, a total of six target object regions. Accordingly, the data processing unit 120 determines feature points from the six target object regions respectively, and uses the determined feature points to calculate the first motion vector of the target object region where it is located.

[0046] As described above, after determining the target object area that needs to be interpolated from multiple object areas in the current scene image, the data processing unit 120 transmits the current scene image, the division information of the target object area, and the first motion vector of each target object area to the application processor, and instructs the application processor to perform interpolation. Among them, the data processing unit 120 can directly transmit the current scene image, the division information of the target object area, and the first motion vector of each target object area to the application processor, or cache the current scene image, the division information of the target object area, and the first motion vector of each target object area into the memory, and instruct the application processor to read the current scene image, the division information of the target object area, and the first motion vector of each target object area from the memory.

[0047] On the other hand, after receiving the current scene image, the division information of the target object area and the first motion vector of each target object area transmitted by the image processor 110 through the data processing unit 120, the application processor interpolates the interpolated image content of the target object area based on the first motion vector of the target object area and the image content of the target object area in the current scene image and the image content of the target object area in the adjacent image (which can be the next scene image of the current scene image or the previous scene image of the current scene image). That is, based on the image content of the target object area in the current scene image and the image content of the target object area in the adjacent image, the image content of the target object area at the moment between the current scene image and the adjacent image is generated, which is the interpolated image content.

[0048] In addition, for the non-target object area, the application processor does not actually perform interpolation on it, but directly uses the image content of the non-target object area as the interpolation image content of the non-target object area.

[0049] At this point, the application processor, i.e., the actual interpolation, has obtained the interpolation image content of the target object area and the interpolation image content of the non-target object area. At this time, the interpolation image content of the target object area and the image content of the non-target object area are further spliced, and the spliced ​​image is used as the interpolation image of the current scene image.

[0050] As described above, after the interpolated frame images of the current scene image are obtained by stitching, the application processor can perform subsequent applications or processing on the interpolated frame images according to the current shooting type. For example, when previewing through the camera, the application processor can use the interpolated frame images together with the current scene image actually shot by the camera for preview; when recording a video through the camera, the application processor can use the interpolated frame images together with the current scene image actually shot by the camera for recording, etc.

[0051] For example, please refer to Figure 4 , the current scene image includes three object areas, one of which is determined as the target object area that needs to be interpolated, and the other two object areas are respectively recorded as non-target object area A and non-target object area B. The next scene image of the current scene image is used here for interpolation processing. Wherein, when performing interpolation processing, the application processor uses the image content of the target object area in the current scene image and the image content of the target object area in the next scene image to interpolate to obtain the interpolation image content of the target object area, and uses the image content of the non-target object area A in the current scene image as the interpolation image content of the non-target object area A, and uses the image content of the non-target object area B in the current scene image as the interpolation image content of the non-target object area B, thereby obtaining Figure 4 The interpolated image shown.

[0052] As can be seen from the above, the image processor provided by the present application obtains the current scene image of the shooting scene through the data interface unit, determines the target object area that needs to be interpolated from multiple object areas of the current scene image through the data processing unit, and obtains the first motion vector corresponding to the target object area, and transmits the first motion vector to the application processor, and the application processor interpolates the interpolated image content of the target object area according to the first motion vector, and obtains the interpolated image of the current scene image based on the interpolated image content of the target object area and the image content of the non-target object area. In this way, the present application not only increases the imaging frame rate of the electronic device by performing actual interpolation processing on a part of the image, but also does not significantly increase the power consumption of the electronic device.

[0053] Optionally, in one embodiment, the data processing unit 120 is configured to:

[0054] Obtaining information about the user's interest level in each object area in the current scene image;

[0055] According to the interest level information of each object region, a target object region that needs to be interpolated is determined from the plurality of object regions.

[0056] When the data processing unit 120 determines the target object area that needs to be interpolated from multiple object areas in the current scene image, it evaluates the user's interest level information for each object area in the current scene image according to the configured interest level information evaluation strategy, thereby obtaining the user's interest level information for each object area in the current scene image. The configuration of the interest level information evaluation strategy is not specifically limited here, and can be configured by those skilled in the art according to actual needs.

[0057] After acquiring the user's interest level information for each object region in the current scene image, the data processing unit 120 may determine a target object region that needs to be interpolated from multiple object regions in the current scene image according to the interest level information for each object region.

[0058] For example, the data processing unit 120 may determine the object region with the highest interest level information among the multiple object regions as the target object region, or may determine the object region with the interest level information reaching the level threshold among the multiple object regions as the target object region. The embodiment of the present application does not specifically limit the value of the level threshold, and those skilled in the art may determine the value according to actual needs.

[0059] Optionally, in one embodiment, the data processing unit 120 is configured to:

[0060] Obtaining the focus distance of the corresponding shooting scene, and obtaining the depth distance of each object area;

[0061] According to the difference between the depth distance of each object area and the focus distance, the user's interest level information on each object area is obtained.

[0062] The embodiment of the present application provides an optional interest level information evaluation strategy.

[0063] It should be noted that when a user operates an electronic device to take a photo, the user usually operates the electronic device to focus on an object of interest in the shooting scene. Therefore, the interest level information can be evaluated based on the focusing condition.

[0064] The data processing unit 120 first obtains the focus distance of the corresponding shooting scene and obtains the depth distance of each object area. There is no specific limitation on how to obtain the depth distance of each object area, and those skilled in the art can configure the depth distance acquisition method according to actual needs.

[0065] For example, when the electronic device is equipped with two cameras arranged in parallel, the data interface unit 110 can obtain the current scene image from one of the cameras, and obtain the other scene image taken synchronously from the other camera. Since the two cameras are arranged in parallel, there will be parallax between the current scene image and the other scene image. Accordingly, the data processing unit 120 can use a triangular parallax algorithm to calculate the depth distance of each object area in the current scene image based on the current scene image and the aforementioned other scene image.

[0066] As described above, after obtaining the focus distance corresponding to the current scene image and the depth distance of each object area in the current scene image, the data processing unit 120 further obtains the user's interest level information for each object area based on the difference between the depth distance of each object area and the focus distance.

[0067] Exemplarily, in an embodiment of the present application, the configuration interest level information is negatively correlated with the difference between the depth distance and the focus distance of the object area, that is, for an object area, the larger the difference between its depth distance and the focus distance, the lower the user's interest in it.

[0068] For example, the interest level information may be divided into three levels, namely low, medium and high, and three difference intervals between the depth distance and the focus distance may be divided accordingly, namely difference interval A, difference interval B and difference interval C, and difference interval A is associated with the interest level information "low", difference interval B is associated with the interest level information "medium", and difference interval C is associated with the interest level information "high". When the data processing unit 120 evaluates the interest level information, for an object area, if the depth distance and the focus distance of the object area are in difference interval A, the interest level information thereof is determined to be "low", if the depth distance and the focus distance of the object area are in difference interval B, the interest level information thereof is determined to be "medium", and if the depth distance and the focus distance of the object area are in difference interval C, the interest level information thereof is determined to be "high".

[0069] Optionally, in one embodiment, obtaining the user's interest level information for each object area includes:

[0070] The interest level information of each object region is evaluated by using the interest measurement model to obtain the interest level information of each object region.

[0071] It should be noted that the embodiment of the present application pre-trains an interest measurement model, which is configured to evaluate the interest level information of the image and output a numerical value representing the interest level information accordingly. The architecture and training method of the interest measurement model are not specifically limited here, and can be configured by those skilled in the art according to actual needs.

[0072] For example, a convolutional neural network can be selected as the basic architecture of the interest measurement model, and trained in a supervised manner using image samples labeled with interest level information, thereby obtaining an interest measurement model for evaluating interest level information.

[0073] Accordingly, in the embodiment of the present application, the data processing unit 120 evaluates the interest level information of each object region in the current scene image through the interest measurement model, thereby obtaining the interest level information of each object region in the current scene image.

[0074] Optionally, in one embodiment, the data processing unit 120 is further configured to:

[0075] Obtaining a general interest measurement model and obtaining user interest preference information;

[0076] The general interest measurement model is adjusted according to the interest preference information to obtain the interest measurement model.

[0077] Among them, the general interest measurement model is trained using a large number of labeled samples of different users, which can reflect the general user's interest in different objects. It is understandable that different users are often interested in different directions, for example, some users are more interested in people, while others are more interested in plants.

[0078] Therefore, in the embodiment of the present application, a pre-trained universal interest measurement model can be obtained, as well as the user's interest preference information, which is used to describe the user's preference for different objects. The user's interest preference information is used to adjust the aforementioned universal interest measurement model to obtain an interest measurement model that matches the user's preference.

[0079] It can be understood that, by using the interest measurement model obtained through the aforementioned adjustment and matching the user's preference, it is possible to evaluate and obtain the interest level information matching the user's real preference.

[0080] Optionally, in one embodiment, the data processing unit 120 is further configured to:

[0081] A second motion vector corresponding to the non-target object region is obtained, and if the second motion vector satisfies a preset frame insertion condition, the non-target object region is determined as the target object region.

[0082] As described above, in the embodiment of the present application, the target object region is divided based on the interest level information. In addition, in the embodiment of the present application, the target object region is further divided twice according to the movement of the object.

[0083] In the embodiment of the present application, after the target object region is divided for the first time according to the interest level information, the target object region is divided for the second time according to the motion vector.

[0084] Exemplarily, after the data processing unit 120 determines the target object area that needs to be interpolated from multiple object areas in the current scene image based on the interest level information of each object area, for non-target object areas that have not been determined as target object areas this time, the data processing unit 120 obtains motion vectors corresponding to these non-target object areas, recorded as second motion vectors, and also determines the non-target object areas whose second motion vectors meet preset interpolation conditions as target object areas.

[0085] How to obtain the second motion vector corresponding to the non-target object area may be specifically obtained by referring to the method of obtaining the first motion vector corresponding to the target object area in the above embodiment, which will not be described in detail here.

[0086] It should be noted that the configuration of the aforementioned preset interpolation conditions is not specifically limited in the embodiments of the present application and can be configured by those skilled in the art according to actual needs.

[0087] For example, you can configure the preset interpolation conditions as:

[0088] The movement direction of the non-target object area is towards a preset direction; or

[0089] The movement speed of the non-target object area is greater than or equal to a preset speed; or

[0090] The movement direction of the non-target object area is toward a preset direction, and the movement speed of the non-target object area is greater than or equal to a preset speed.

[0091] Among them, the preset direction and the preset speed can be determined by skilled technicians according to actual needs, and the embodiments of the present application do not impose specific restrictions on this.

[0092] Optionally, in one embodiment, the data processing unit 120 is further configured to:

[0093] Get the current system power consumption;

[0094] Adjusting the target object region according to the system power consumption to obtain a first adjusted target object region; and

[0095] A first motion vector corresponding to the first adjusted target object area is acquired.

[0096] In the embodiment of the present application, the data processing unit 120 further adjusts the determined target object area according to the system power consumption of the electronic device to obtain a dynamic balance between the interpolation effect and the system power consumption.

[0097] After determining the target object area that needs to be interpolated, the data processing unit 120 further obtains the current system power consumption. The data processing unit 120 can determine the target object area only based on the interest level information of the object area, or after determining the target object area based on the interest level information of the object area, it can also determine a new target object area based on the motion vector of the object area.

[0098] As described above, after acquiring the current system power consumption, the data processing unit 120 adjusts the determined target object area according to the system power consumption according to the configured first adjustment strategy, and records the adjusted target object area as the first adjusted target object area. The adjustment of the target object area includes adding a target object area and deleting a target object area.

[0099] It should be noted that the configuration of the first adjustment strategy in the embodiment of the present application is not specifically limited and can be configured by those skilled in the art according to actual needs.

[0100] Exemplarily, the first adjustment strategy may be configured as:

[0101] When the system power consumption is greater than or equal to the power consumption threshold, the determined target object area is deleted;

[0102] When the system power consumption is less than the power consumption threshold, the target object area is added.

[0103] The power consumption threshold value may be determined by those skilled in the art according to the power consumption capability of the electronic device, and the present application embodiment does not impose any specific restrictions on this. In addition, the present application embodiment does not impose any specific restrictions on how to delete the determined target object area and how to increase the target object area.

[0104] Exemplarily, when deleting the determined target object region, the determination criteria for determining the target object region based on the interest level information and / or the determination criteria for determining the target object region based on the motion vector may be improved, so as to delete the target object region whose interest level information and / or motion vector do not meet the new determination criteria; or

[0105] Directly delete the target object region with the smallest interest level information, and / or delete the target object region with the smallest motion speed.

[0106] When adding the target object area, the judgment criteria for determining the target object area based on the interest level information can be lowered, and / or the judgment criteria for determining the target object area based on the motion vector can be lowered, so that the non-target object area whose interest level information and / or motion vector meet the new judgment criteria can be added as the target object area.

[0107] Optionally, in one embodiment, the data processing unit 120 is further configured to:

[0108] Get the object type of the target object area;

[0109] Adjusting the target object region according to the object type to obtain a second adjusted target object region;

[0110] as well as

[0111] A first motion vector corresponding to the second adjusted target object area is acquired.

[0112] In the embodiment of the present application, the data processing unit 120 further adjusts the determined target object area according to the object type of the target object area to perform frame insertion processing more flexibly.

[0113] After determining the target object region that needs to be interpolated, the data processing unit 120 further obtains the object type of the target object region. The data processing unit 120 may determine the target object region only based on the interest level information of the object region, or after determining the target object region based on the interest level information of the object region, further determine a new target object region based on the motion vector of the object region.

[0114] As described above, after acquiring the current object type, the data processing unit 120 adjusts the determined target object area according to the object type according to the configured second adjustment strategy, and records the adjusted target object area as the first adjusted target object area. The adjustment of the target object area includes adding a target object area.

[0115] It should be noted that the configuration of the second adjustment strategy in the embodiment of the present application is not specifically limited and can be configured by those skilled in the art according to actual needs.

[0116] Exemplarily, the second adjustment strategy may be configured as:

[0117] If the object type of the target object region is a preset object type, a non-target object region adjacent to the target object region is determined as the target object region.

[0118] Among them, the preset object type can be configured by technical personnel in this field according to actual needs. For example, when shooting children, since children move frequently, the preset object type can be configured to include a child type. In this way, when the object type of the target object area is determined to be a child type, the data processing unit 120 can also determine the surrounding non-target object area as the target object area, so as to improve the interpolation effect.

[0119] Please refer to Figure 5The present application also provides an electronic device 200, such as Figure 5 As shown, the electronic device 200 includes:

[0120] Camera 210, used to collect the current scene image of the shooting scene;

[0121] The image processor 220 is used to determine a target object region that needs to be interpolated from multiple object regions in the current scene image, and obtain a first motion vector corresponding to the target object region; and

[0122] The application processor 230 is configured to obtain interpolated image content of the target object region according to the first motion vector interpolation, and obtain an interpolated image of the current scene image based on the interpolated image content of the target object region and image content of the non-target object region.

[0123] It should be noted that the embodiment of the present application does not impose any specific restrictions on the physical presentation form of the electronic device 200. The physical presentation form of the electronic device 200 can be a mobile electronic device such as a smart phone, tablet computer, PDA, laptop computer, or a fixed electronic device such as a desktop computer or television.

[0124] Similarly, the embodiment of the present application does not specifically limit the type of camera 210. For example, using the shooting frame rate as the classification standard for camera types, the camera 210 can be a low frame rate camera (the shooting frame rate is usually within 100 frames / second, such as 30 frames / second, 60 frames / second, etc.), or it can be a high frame rate camera (the shooting frame rate is usually above 100 frames / second, such as 120 frames / second).

[0125] The shooting scene of the camera 210 can be understood as the area that the camera 210 is aimed at after being enabled, that is, the area where the camera 210 can convert the light signal into corresponding image data. For example, after the electronic device 200 enables the camera 210 according to the user operation, if the user controls the camera 210 of the electronic device 200 to aim at an area including a certain object, the area including the object is the shooting scene of the camera 210.

[0126] In the embodiment of the present application, the camera 210 is used to capture the current scene image of the shooting scene for subsequent frame insertion processing.

[0127] In the embodiment of the present application, the image processor 220 directly obtains the current scene image in RAW format of the captured shooting scene from the camera 210. Afterwards, the image processor 220 determines the target object area that needs to be interpolated from multiple object areas of the current scene image according to the configured object determination strategy. The configuration of the aforementioned object determination strategy is not specifically limited here, and can be configured by those skilled in the art according to actual needs.

[0128] For example, for a shooting scene, there may be various objects, such as people, animals, plants, and buildings. When a user faces such a shooting scene, he usually cannot pay attention to all the objects in it, but only pays attention to the objects of interest. For example, when a user takes a portrait, he usually pays attention to the people in the shooting scene. Therefore, the object determination strategy can be configured as: the object area of ​​interest to the user among multiple object areas is determined as the target object area that needs to be interpolated. Among them, there is no specific limitation on how to identify the object area of ​​interest to the user, and a suitable identification method can be configured by those skilled in the art according to actual needs.

[0129] It should be noted that the purpose of interpolation is to improve the continuity of image content, and whether the image content is continuous depends on whether the motion of objects in adjacent images is continuous. Therefore, after the image processor 220 determines the target object area that needs to be interpolated from multiple object areas of the current scene image, it further obtains a motion vector corresponding to the target object area, recorded as a first motion vector, which is used to describe the motion direction and motion speed of the object in the target object area.

[0130] Exemplarily, for a target object region, the image processor 220 analyzes and calculates a first motion vector of the target object region according to a position difference between the target object region in a current scene image and an adjacent previous scene image or a next scene image.

[0131] To improve the efficiency of obtaining the first motion vector, feature points may be selected from the target object region, and the feature points may be used to represent the target object region to obtain the first motion vector. The selection of feature points may be determined based on the characteristics of different objects.

[0132] For example, you can select the vertex positions of certain objects as feature points, such as a person's hands or head; you can select the edges of certain objects as feature points, such as the edge of a car.

[0133] It should be noted that the definition of feature points in the embodiments of the present application does not refer to a single pixel point, but to all pixel points in a specific relatively fixed small area, such as the fingertips of fingers, ears of the head, vertices of moving objects, etc. All pixel points corresponding to these areas are regarded as feature points.

[0134] For example, please refer to Figure 3, for the current scene image, the regions where the head, hands, torso, and legs are located are all determined as target object regions, a total of six target object regions. Accordingly, the image processor 220 determines feature points from the six target object regions respectively, and uses the determined feature points to calculate the first motion vector of the target object region where the feature points are located.

[0135] As described above, after the image processor 220 determines the target object area that needs to be interpolated from the multiple object areas in the current scene image, it transmits the current scene image, the division information of the target object area, and the first motion vector of each target object area to the application processor 230, and instructs the application processor 230 to perform interpolation. Among them, the image processor 220 can directly transmit the current scene image, the division information of the target object area, and the first motion vector of each target object area to the application processor 230, or cache the current scene image, the division information of the target object area, and the first motion vector of each target object area into the memory, and instruct the application processor 230 to read the current scene image, the division information of the target object area, and the first motion vector of each target object area from the memory.

[0136] On the other hand, after receiving the current scene image, the division information of the target object area, and the first motion vector of each target object area transmitted by the image processor 110 through the image processor 220, the application processor 230 interpolates the interpolated image content of the target object area based on the first motion vector of the target object area and the image content of the target object area in the current scene image and the image content of the target object area in the adjacent image (which can be the next scene image of the current scene image or the previous scene image of the current scene image). That is, based on the image content of the target object area in the current scene image and the image content of the target object area in the adjacent image, the image content of the target object area at the moment between the current scene image and the adjacent image is generated, which is the interpolated image content.

[0137] In addition, for the non-target object area, the application processor 230 does not actually interpolate the non-target object area, but directly uses the image content of the non-target object area as the interpolated frame image content of the non-target object area.

[0138] At this point, the application processor 230 has actually interpolated and obtained the interpolated image content of the target object area and the interpolated image content of the non-target object area. At this time, the interpolated image content of the target object area and the image content of the non-target object area are further spliced, and the spliced ​​image is used as the interpolated image of the current scene image.

[0139] As described above, after the interpolated frame images of the current scene image are obtained by stitching, the application processor 230 can perform subsequent application / processing on the interpolated frame images according to the current shooting type. For example, when previewing through the camera, the application processor 230 can use the interpolated frame images together with the current scene image actually shot by the camera for preview; when video recording is currently performed through the camera, the application processor 230 can use the interpolated frame images together with the current scene image actually shot by the camera for recording.

[0140] For example, please refer to Figure 4 , the current scene image includes three object areas, one of which is determined to be a target object area that needs to be interpolated, and the other two object areas are respectively recorded as non-target object area A and non-target object area B. The next scene image of the current scene image is used here for interpolation processing. Wherein, when performing interpolation processing, the application processor 230 uses the image content of the target object area in the current scene image and the image content of the target object area in the next scene image to interpolate to obtain the interpolation image content of the target object area, and uses the image content of the non-target object area A in the current scene image as the interpolation image content of the non-target object area A, and uses the image content of the non-target object area B in the current scene image as the interpolation image content of the non-target object area B, thereby obtaining Figure 4 The interpolated image shown.

[0141] Optionally, in one embodiment, the image processor 220 is configured to:

[0142] Obtaining information about the user's interest level in each object area in the current scene image;

[0143] According to the interest level information of each object region, a target object region that needs to be interpolated is determined from the plurality of object regions.

[0144] When the image processor 220 determines the target object area that needs to be interpolated from multiple object areas in the current scene image, it evaluates the user's interest level information for each object area in the current scene image according to the configured interest level information evaluation strategy, thereby obtaining the user's interest level information for each object area in the current scene image. The configuration of the interest level information evaluation strategy is not specifically limited here, and can be configured by those skilled in the art according to actual needs.

[0145] After acquiring the user's interest level information for each object region in the current scene image, the image processor 220 may determine a target object region that needs to be interpolated from multiple object regions in the current scene image according to the interest level information for each object region.

[0146] For example, the image processor 220 may determine the object region with the highest interest level information among the multiple object regions as the target object region, or may determine the object region with the interest level information reaching the level threshold among the multiple object regions as the target object region. The embodiment of the present application does not specifically limit the value of the level threshold, and those skilled in the art may determine the value according to actual needs.

[0147] Optionally, in one embodiment, the image processor 220 is configured to:

[0148] Obtaining the focus distance of the corresponding shooting scene, and obtaining the depth distance of each object area;

[0149] According to the difference between the depth distance of each object area and the focus distance, the user's interest level information on each object area is obtained.

[0150] The embodiment of the present application provides an optional interest level information evaluation strategy.

[0151] It should be noted that when a user operates an electronic device to take a photo, the user usually operates the electronic device to focus on an object of interest in the shooting scene. Therefore, the interest level information can be evaluated based on the focusing condition.

[0152] The image processor 220 first obtains the focus distance of the corresponding shooting scene and the depth distance of each object area. There is no specific limitation on how to obtain the depth distance of each object area, and those skilled in the art can configure the depth distance acquisition method according to actual needs.

[0153] For example, when the electronic device is configured with two cameras arranged in parallel, the data interface unit 110 can obtain the current scene image from one of the cameras, and obtain the other scene image taken synchronously from the other camera. Since the two cameras are arranged in parallel, there will be parallax between the current scene image and the other scene image. Accordingly, the image processor 220 can use a triangular parallax algorithm to calculate the depth distance of each object area in the current scene image based on the current scene image and the aforementioned other scene image.

[0154] As described above, after obtaining the focus distance corresponding to the current scene image and the depth distance of each object area in the current scene image, the image processor 220 further obtains the user's interest level information for each object area based on the difference between the depth distance of each object area and the focus distance.

[0155] Exemplarily, in an embodiment of the present application, the configuration interest level information is negatively correlated with the difference between the depth distance and the focus distance of the object area, that is, for an object area, the larger the difference between its depth distance and the focus distance, the lower the user's interest in it.

[0156] For example, the interest level information may be divided into three levels, namely low, medium and high, and three difference intervals between the depth distance and the focus distance may be divided accordingly, namely difference interval A, difference interval B and difference interval C, and difference interval A is associated with the interest level information "low", difference interval B is associated with the interest level information "medium", and difference interval C is associated with the interest level information "high". When the image processor 220 evaluates the interest level information, for an object area, if the depth distance and the focus distance of the object area are in difference interval A, the interest level information thereof is determined to be "low", if the depth distance and the focus distance of the object area are in difference interval B, the interest level information thereof is determined to be "medium", and if the depth distance and the focus distance of the object area are in difference interval C, the interest level information thereof is determined to be "high".

[0157] Optionally, in one embodiment, obtaining the user's interest level information for each object area includes:

[0158] The interest level information of each object region is evaluated by using the interest measurement model to obtain the interest level information of each object region.

[0159] It should be noted that the embodiment of the present application pre-trains an interest measurement model, which is configured to evaluate the interest level information of the image and output a numerical value representing the interest level information accordingly. The architecture and training method of the interest measurement model are not specifically limited here, and can be configured by those skilled in the art according to actual needs.

[0160] For example, a convolutional neural network can be selected as the basic architecture of the interest measurement model, and trained in a supervised manner using image samples labeled with interest level information, thereby obtaining an interest measurement model for evaluating interest level information.

[0161] Accordingly, in the embodiment of the present application, the image processor 220 evaluates the interest level information of each object area in the current scene image through the interest measurement model, thereby obtaining the interest level information of each object area in the current scene image.

[0162] Optionally, in one embodiment, the image processor 220 is further configured to:

[0163] Obtaining a general interest measurement model and obtaining user interest preference information;

[0164] The general interest measurement model is adjusted according to the interest preference information to obtain the interest measurement model.

[0165] Among them, the general interest measurement model is trained using a large number of labeled samples of different users, which can reflect the general user's interest in different objects. It is understandable that different users are often interested in different directions, for example, some users are more interested in people, while others are more interested in plants.

[0166] Therefore, in the embodiment of the present application, a pre-trained universal interest measurement model can be obtained, as well as the user's interest preference information, which is used to describe the user's preference for different objects. The user's interest preference information is used to adjust the aforementioned universal interest measurement model to obtain an interest measurement model that matches the user's preference.

[0167] It can be understood that, by using the interest measurement model obtained through the aforementioned adjustment and matching the user's preference, it is possible to evaluate and obtain the interest level information matching the user's real preference.

[0168] Optionally, in one embodiment, the image processor 220 is further configured to:

[0169] A second motion vector corresponding to the non-target object region is obtained, and if the second motion vector satisfies a preset frame insertion condition, the non-target object region is determined as the target object region.

[0170] As described above, in the embodiment of the present application, the target object region is divided based on the interest level information. In addition, in the embodiment of the present application, the target object region is further divided twice according to the movement of the object.

[0171] In the embodiment of the present application, after the target object region is divided for the first time according to the interest level information, the target object region is divided for the second time according to the motion vector.

[0172] Exemplarily, after the image processor 220 determines the target object area that needs to be interpolated from multiple object areas in the current scene image based on the interest level information of each object area, for non-target object areas that have not been determined as target object areas this time, the image processor 220 obtains the motion vectors of these non-target object areas, records them as second motion vectors, and also determines the non-target object areas whose second motion vectors meet the preset interpolation conditions as target object areas.

[0173] How to obtain the second motion vector corresponding to the non-target object area may be specifically obtained by referring to the method of obtaining the first motion vector corresponding to the target object area in the above embodiment, which will not be described in detail here.

[0174] It should be noted that the configuration of the aforementioned preset interpolation conditions is not specifically limited in the embodiments of the present application and can be configured by those skilled in the art according to actual needs.

[0175] For example, you can configure the preset interpolation conditions as:

[0176] The movement direction of the non-target object area is towards a preset direction; or

[0177] The movement speed of the non-target object area is greater than or equal to a preset speed; or

[0178] The movement direction of the non-target object area is toward a preset direction, and the movement speed of the non-target object area is greater than or equal to a preset speed.

[0179] Among them, the preset direction and the preset speed can be determined by skilled technicians according to actual needs, and the embodiments of the present application do not impose specific restrictions on this.

[0180] Optionally, in one embodiment, the image processor 220 is further configured to:

[0181] Get the current system power consumption;

[0182] Adjusting the target object region according to the system power consumption to obtain a first adjusted target object region; and

[0183] A first motion vector corresponding to the first adjusted target object area is acquired.

[0184] In the embodiment of the present application, the image processor 220 further adjusts the determined target object area according to the system power consumption of the electronic device to obtain a dynamic balance between the interpolation effect and the system power consumption.

[0185] After determining the target object area that needs to be interpolated, the image processor 220 further obtains the current system power consumption. The image processor 220 may determine the target object area only based on the interest level information of the object area, or after determining the target object area based on the interest level information of the object area, it may additionally determine a new target object area based on the motion vector of the object area.

[0186] As described above, after acquiring the current system power consumption, the image processor 220 adjusts the determined target object area according to the system power consumption according to the configured first adjustment strategy, and records the adjusted target object area as the first adjusted target object area. The adjustment of the target object area includes adding a target object area and deleting a target object area.

[0187] It should be noted that the configuration of the first adjustment strategy in the embodiment of the present application is not specifically limited and can be configured by those skilled in the art according to actual needs.

[0188] Exemplarily, the first adjustment strategy may be configured as:

[0189] When the system power consumption is greater than or equal to the power consumption threshold, the determined target object area is deleted;

[0190] When the system power consumption is less than the power consumption threshold, the target object area is added.

[0191] The power consumption threshold value may be determined by those skilled in the art according to the power consumption capability of the electronic device, and the present application embodiment does not impose any specific restrictions on this. In addition, the present application embodiment does not impose any specific restrictions on how to delete the determined target object area and how to increase the target object area.

[0192] Exemplarily, when deleting the determined target object region, the determination criteria for determining the target object region based on the interest level information and / or the determination criteria for determining the target object region based on the motion vector may be improved, so as to delete the target object region whose interest level information and / or motion vector do not meet the new determination criteria; or

[0193] Directly delete the target object region with the smallest interest level information, and / or delete the target object region with the smallest motion speed.

[0194] When adding the target object area, the judgment criteria for determining the target object area based on the interest level information can be lowered, and / or the judgment criteria for determining the target object area based on the motion vector can be lowered, so that the non-target object area whose interest level information and / or motion vector meet the new judgment criteria can be added as the target object area.

[0195] Optionally, in one embodiment, the image processor 220 is further configured to:

[0196] Get the object type of the target object area;

[0197] Adjusting the target object region according to the object type to obtain a second adjusted target object region;

[0198] as well as

[0199] A first motion vector corresponding to the second adjusted target object area is acquired.

[0200] In the embodiment of the present application, the image processor 220 further adjusts the determined target object area according to the object type of the target object area to perform interpolation processing more flexibly.

[0201] After determining the target object region that needs to be interpolated, the image processor 220 further obtains the object type of the target object region. The image processor 220 may determine the target object region only based on the interest level information of the object region, or after determining the target object region based on the interest level information of the object region, it may additionally determine a new target object region based on the motion vector of the object region.

[0202] As described above, after acquiring the current object type, the image processor 220 adjusts the determined target object area according to the object type according to the configured second adjustment strategy, and records the adjusted target object area as the first adjusted target object area. The adjustment of the target object area includes adding a target object area.

[0203] It should be noted that the configuration of the second adjustment strategy in the embodiment of the present application is not specifically limited and can be configured by those skilled in the art according to actual needs.

[0204] Exemplarily, the second adjustment strategy may be configured as:

[0205] If the object type of the target object region is a preset object type, a non-target object region adjacent to the target object region is determined as the target object region.

[0206] Among them, the preset object type can be configured by technical personnel in this field according to actual needs. For example, when shooting children, since children move frequently, the preset object type can be configured to include a child type. In this way, when the object type of the target object area is determined to be a child type, the image processor 220 can also determine the non-target object area around it as the target object area, so as to improve the interpolation effect.

[0207] Please refer to Figure 6 The present application also provides an electronic device 300, such as Figure 6 As shown, the electronic device 300 may include a camera 310, a memory 320, and a processor 330. Those skilled in the art will appreciate that Figure 6 The structure of the electronic device 300 shown in the figure does not constitute a limitation on the electronic device 300, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0208] The camera 310 is composed of multiple parts, including a lens, a motor, and an image sensor. The lens is used to project external light signals to the image sensor; the image sensor is used to perform photoelectric conversion on the light signals projected by the lens, converting the light signals into usable electrical signals to obtain the original image data; and the motor is used to drive the lens to move, thereby adjusting the distance between the lens and the image sensor to meet the imaging formula (also called lens imaging formula, Gaussian imaging formula, etc.), so that the image is clear.

[0209] The memory 320 may be used to store computer programs and data. The computer programs stored in the memory 320 include executable codes. The computer programs may be divided into various functional modules. The processor 330 executes various functional applications and data processing by running the computer programs stored in the memory 320.

[0210] The processor 330 is the control center of the electronic device 300. It uses various interfaces and lines to connect various parts of the entire electronic device 300, and executes various functions and processes data of the electronic device 300 by running or executing computer programs stored in the memory 320 and calling data stored in the memory 320, thereby controlling the electronic device 300 as a whole.

[0211] In the embodiment of the present application, the processor 330 in the electronic device 300 loads the executable code corresponding to one or more computer programs into the memory 320 in the following order, and the processor 330 executes the following steps:

[0212] Acquire a current scene image of a shooting scene, and determine a target object area that needs to be interpolated from multiple object areas in the current scene image;

[0213] Acquire a first motion vector corresponding to the target object area;

[0214] Interpolate frames according to the first motion vector to obtain interpolated frame image content of the target object area;

[0215] Based on the interpolated frame image content of the target object area and the image content of the non-target object area, an interpolated frame image of the current scene image is obtained.

[0216] Optionally, in one embodiment, when determining a target object region that needs to be interpolated from multiple object regions in the current scene image, the processor 330 is configured to execute:

[0217] Obtaining information about the user's interest level in each object area;

[0218] According to the interest level information of each object region, a target object region that needs to be interpolated is determined from the plurality of object regions.

[0219] Optionally, in one embodiment, when obtaining the user's interest level information for each object area, the processor 330 is configured to execute:

[0220] Obtain the focus distance corresponding to the current scene image, and obtain the depth distance of each object area;

[0221] According to the difference between the depth distance of each object area and the focus distance, the user's interest level information on each object area is obtained.

[0222] Optionally, in one embodiment, when obtaining the user's interest level information for each object area, the processor 330 is configured to execute:

[0223] The interest level information of each object region is evaluated by using the interest measurement model to obtain the interest level information of each object region.

[0224] Optionally, in one embodiment, after determining the target object region that needs to be interpolated from the multiple object regions according to the interest level information of each object region, the processor 330 is further configured to execute:

[0225] A second motion vector corresponding to the non-target object region is obtained, and if the second motion vector satisfies a preset frame insertion condition, the non-target object region is determined as the target object region.

[0226] Optionally, in one embodiment, before acquiring the first motion vector corresponding to the target object area, the processor 330 is further configured to execute:

[0227] Get the current system power consumption;

[0228] Adjusting the target object area according to the system power consumption to obtain a first adjusted target object area;

[0229] When acquiring the first motion vector corresponding to the target object area, the processor 330 is configured to execute:

[0230] A first motion vector corresponding to the first adjusted target object area is acquired.

[0231] Optionally, in one embodiment, before acquiring the first motion vector corresponding to the target object area, the processor 330 is further configured to execute:

[0232] Get the object type of the target object area;

[0233] Adjusting the target object region according to the object type to obtain a second adjusted target object region;

[0234] When acquiring the first motion vector corresponding to the target object area, the processor 330 is configured to execute:

[0235] A first motion vector corresponding to the second adjusted target object area is acquired.

[0236] Please refer to Figure 7 , the present application also provides an image processing method, such as Figure 7 As shown, the process of the image processing method may include:

[0237] In 410, a current scene image of a shooting scene is acquired, and a target object area that needs to be interpolated is determined from multiple object areas in the current scene image;

[0238] At 420, a first motion vector corresponding to the target object region is obtained;

[0239] In 430, interpolating frames according to the first motion vector obtains interpolated frame image content of the target object area;

[0240] In 440 , an interpolated frame image of the current scene image is obtained based on the interpolated frame image content of the target object area and the image content of the non-target object area.

[0241] Optionally, in one embodiment, determining a target object region that needs to be interpolated from a plurality of object regions in the current scene image includes:

[0242] Obtaining information about the user's interest level in each object area;

[0243] According to the interest level information of each object region, a target object region that needs to be interpolated is determined from the plurality of object regions.

[0244] Optionally, in one embodiment, obtaining the user's interest level information for each object area includes:

[0245] Obtain the focus distance corresponding to the current scene image, and obtain the depth distance of each object area;

[0246] According to the difference between the depth distance of each object area and the focus distance, the user's interest level information on each object area is obtained.

[0247] Optionally, in one embodiment, obtaining the user's interest level information for each object area includes:

[0248] The interest level information of each object region is evaluated by using the interest measurement model to obtain the interest level information of each object region.

[0249] Optionally, in an embodiment, after determining the target object region to be interpolated from the plurality of object regions according to the interest level information of each object region, the method further includes:

[0250] A second motion vector corresponding to the non-target object region is obtained, and if the second motion vector satisfies a preset frame insertion condition, the non-target object region is determined as the target object region.

[0251] Optionally, in one embodiment, before obtaining the first motion vector corresponding to the target object area, the method further includes:

[0252] Get the current system power consumption;

[0253] Adjusting the target object area according to the system power consumption to obtain a first adjusted target object area;

[0254] Obtaining a first motion vector corresponding to a target object area includes:

[0255] A first motion vector corresponding to the first adjusted target object area is acquired.

[0256] Optionally, in one embodiment, before obtaining the first motion vector corresponding to the target object area, the method further includes:

[0257] Get the object type of the target object area;

[0258] Adjusting the target object region according to the object type to obtain a second adjusted target object region;

[0259] Obtaining a first motion vector corresponding to a target object area includes:

[0260] A first motion vector corresponding to the second adjusted target object area is acquired.

[0261] Please refer to Figure 8 The image processing method provided in this application may also include:

[0262] In 510, a current scene image of a shooting scene is acquired.

[0263] In 520 , the depth distance of each object area in the current scene image is obtained, and the focus distance corresponding to the current scene image is obtained.

[0264] In 530 , information on the user's interest level in each object area is obtained based on the difference between the depth distance and the focus distance of each object area.

[0265] In 540 , a target object region that needs to be interpolated is determined from a plurality of object regions according to the interest level information of each object region.

[0266] In 550 , feature points representing the target object region are selected from the target object region, and motion vectors corresponding to the feature points are obtained.

[0267] In 560 , interpolation is performed according to the motion vector of the feature point to obtain interpolated image content of the target object area.

[0268] In 570 , an interpolated frame image of the current scene image is obtained based on the interpolated frame image content of the target object area and the image content of the non-target object area.

[0269] It should be noted that the image processing method provided in the present application can be executed by the image processor or electronic device provided in the above embodiments. For specific instructions, please refer to the relevant instructions in the above embodiments, which will not be repeated here.

[0270] The above describes in detail the image processor, electronic device, and image processing method provided by the embodiments of the present application. Specific examples are used herein to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the present application. At the same time, for those skilled in the art, according to the ideas of the present application, there will be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as limiting the present application.

Claims

1. An image processing method, characterized in that: include: Get the current scene image of the shooting scene; Acquire a focus distance corresponding to the current scene image, and acquire a depth distance of each object area of ​​the current scene image; Acquiring information on the user's interest level in each of the object areas according to a difference between the depth distance of each of the object areas and the focus distance; Determining a target object region that needs to be interpolated from the plurality of object regions according to the interest level information of each of the object regions; Acquire a first motion vector corresponding to the target object area; Obtaining interpolated frame image content of the target object area according to the first motion vector interpolation; Based on the interpolated frame image content of the target object area and the image content of the non-target object area, an interpolated frame image of the current scene image is obtained.

2. The image processing method according to claim 1, characterized in that: After determining the target object region to be interpolated from the plurality of object regions according to the interest level information of each object region, the method further includes: A second motion vector corresponding to the non-target object region is acquired, and if the second motion vector satisfies a frame insertion condition, the non-target object region is determined as a target object region.

3. The image processing method according to claim 1 or 2, characterized in that: Before acquiring the first motion vector corresponding to the target object area, the method further includes: Get the current system power consumption; Adjusting the target object area according to the system power consumption to obtain a first adjusted target object area; The acquiring a first motion vector corresponding to the target object area includes: A first motion vector corresponding to the first adjusted target object area is obtained.

4. The image processing method according to claim 1 or 2, characterized in that: Before acquiring the first motion vector corresponding to the target object area, the method further includes: Acquire the object type of the target object area; Adjusting the target object region according to the object type to obtain a second adjusted target object region; The acquiring a first motion vector corresponding to the target object area includes: A first motion vector corresponding to the second adjusted target object area is acquired.

5. An image processor, characterized in that: include: A data interface unit, used to obtain a current scene image of a shooting scene; A data processing unit, used to obtain a focus distance corresponding to the current scene image, and to obtain a depth distance of each object area of ​​the current scene image; Acquiring information on the user's interest level in each of the object areas according to a difference between the depth distance of each of the object areas and the focus distance; Determining a target object region that needs to be interpolated from the plurality of object regions according to the interest level information of each of the object regions, and acquiring a first motion vector corresponding to the target object region; as well as The first motion vector is transmitted to an application processor, so that the application processor obtains the interpolated image content of the target object area according to the first motion vector interpolation, and obtains the interpolated image of the current scene image based on the interpolated image content of the target object area and the image content of the non-target object area.

6. An electronic device, characterized in that: include: A camera, used to collect a current scene image of a shooting scene; An image processor, used to obtain a focus distance corresponding to the current scene image, and to obtain a depth distance of each object area of ​​the current scene image; Acquiring information on the user's interest level in each of the object areas according to a difference between the depth distance of each of the object areas and the focus distance; Determining a target object region that needs to be interpolated from the plurality of object regions according to the interest level information of each of the object regions, and acquiring a first motion vector corresponding to the target object region; as well as The application processor is used to obtain the interpolated image content of the target object area according to the first motion vector interpolation, and obtain the interpolated image of the current scene image based on the interpolated image content of the target object area and the image content of the non-target object area.

7. An electronic device, comprising a processor and a memory, wherein the memory stores a computer program, wherein: The processor executes the image processing method according to any one of claims 1 to 4 by loading the computer program.

Images