Image processing system, method and electronic device

Abstract

The application discloses an image processing system, method and electronic equipment, and belongs to the technical field of image processing. The image processing system comprises an image statistical processing chip integrated in a hardware layer and an updated image algorithm node arranged in a hardware abstraction layer. The updated image algorithm node is used for acquiring an image algorithm issued by a server and sending the image algorithm to the image statistical processing chip. The image statistical processing chip is used for calculating first feature statistical data of an image signal through the image algorithm, and the first feature statistical data is used for adjusting a target image.

Description

Technical Field

[0001] This application belongs to the field of image processing technology, specifically relating to an image processing system, method, and electronic device. Background Technology

[0002] Electronic devices can perform image processing using image algorithms (such as the 3A Stats algorithm). 3A refers to auto focus (AF), auto exposure (AE), and auto white balance (AWB). This algorithm can adjust the brightness and focal length of the image and compensate for color differences under different lighting conditions so that electronic devices can present high-quality images.

[0003] In related technologies, image processing algorithms are computationally intensive and can easily consume processor resources, leading to a decline in operating system performance. Summary of the Invention

[0004] The purpose of this application is to provide an image processing system, method, device, and storage medium that can save processor computing resources and improve operating system performance.

[0005] In a first aspect, embodiments of this application provide an image processing system, which may include:

[0006] An image statistical processing chip integrated in the hardware layer and an image update algorithm node set in the hardware abstraction layer; among them...

[0007] Update the image algorithm node to obtain the image algorithm issued by the server and send the image algorithm to the image statistical processing chip;

[0008] The image statistical processing chip is used to calculate the first feature statistics of the image signal through the image algorithm sent by the server. The first feature statistics are used to adjust the target image.

[0009] Secondly, embodiments of this application provide an image processing method, which may include:

[0010] By setting the image algorithm update node in the hardware abstraction layer, the image algorithm issued by the server can be obtained;

[0011] The image algorithm is sent to the image statistical processing chip integrated in the hardware layer by updating the image algorithm node;

[0012] The first feature statistics of the image signal are calculated using an image statistical processing chip and an image algorithm. The first feature statistics are used to adjust the target image.

[0013] Thirdly, embodiments of this application provide an electronic device, which includes a processor, a memory, and a program or instructions stored in the memory and executable on the processor. When the program or instructions are executed by the processor, they implement the steps of the image processing method as shown in the second aspect.

[0014] Fourthly, embodiments of this application provide a readable storage medium on which a program or instructions are stored, which, when executed by a processor, implement the steps of the image processing method as shown in the second aspect.

[0015] Fifthly, embodiments of this application provide a chip, which includes a processor and a display interface, the display interface and the processor being coupled together, the processor being used to run programs or instructions to implement the steps of the image processing method as shown in the second aspect.

[0016] In a sixth aspect, embodiments of this application provide a computer program product stored in a storage medium, which is executed by at least one processor to implement the steps of the image processing method as described in the second aspect.

[0017] In this embodiment, the image processing system may include an image statistical processing chip integrated in the hardware layer and an image algorithm update node disposed in the hardware abstraction layer. The image algorithm update node is used to obtain image algorithms sent from the server and send them to the image statistical processing chip. The image statistical processing chip is used to calculate a first feature statistical data of the image signal using the image algorithm. This first feature statistical data is used to adjust the target image. In this way, the image algorithm update node can obtain image algorithms from the server and send them to the image statistical processing chip, thereby enabling rapid iteration of the image algorithm in the image statistical processing chip. Based on this, the first feature statistical data of the image signal calculated by the image algorithm in the image statistical processing chip is closer to the feature statistical data required by the user. This makes the target image adjusted with feature statistical data that is closer to the user's required data better meet the user's needs for image processing results. This reduces the consumption of processor computing resources and improves the stability of image processing result quality while enhancing operating system performance. Attached Figure Description

[0018] Figure 1 A flowchart of an image processing system;

[0019] Figure 2 This is a schematic diagram of the structure of an image processing system provided in an embodiment of this application;

[0020] Figure 3 This is one of the structural schematic diagrams of an image processing system provided in an embodiment of this application;

[0021] Figure 4 This is a second schematic diagram of the structure of an image processing system provided in an embodiment of this application;

[0022] Figure 5 This is the third schematic diagram of the structure of an image processing system provided in an embodiment of this application;

[0023] Figure 6 This is the fourth schematic diagram of the structure of an image processing system provided in an embodiment of this application;

[0024] Figure 7 Fifth schematic diagram of an image processing system provided in this application embodiment;

[0025] Figure 8 A flowchart illustrating an image processing method provided in an embodiment of this application;

[0026] Figure 9 This is a schematic diagram of the structure of an image processing apparatus provided in an embodiment of this application;

[0027] Figure 10 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application;

[0028] Figure 11 This is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0029] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0030] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such terms can be used interchangeably where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0031] In image processing scenarios, since image algorithms are software algorithms, they usually rely on the Central Processing Unit (CPU) to perform 3A-related statistical calculations. These statistical calculations are simple but computationally intensive, which consumes a lot of CPU computing power, causing the CPU to be occupied for a long time. As a result, there is no time to process other modules, which ultimately leads to a decline in operating system performance, causing stuttering issues such as frame drops and frame drops, and also increases the power consumption of electronic devices.

[0032] In related technologies, to solve the above problems, the module that executes the image algorithm is typically hard-coded and integrated into the Image Signal Processor (ISP). For example, such as... Figure 1 As shown, its image processing flow path is divided into two paths.

[0033] The first path can perform the following image processing steps:

[0034] Step 1: Upon receiving the startup request of the camera application, the camera application can configure the working mode of the statistics module corresponding to the image algorithm, and confirm whether the software 3A stats algorithm or the hardened stats module is currently being used.

[0035] Step 2: If the hardened stats module is used, the Hardware Abstraction Layer (HAL) will notify the hardware ISP to call the hardened 3Astats module through the / dev / Isp_drv device node.

[0036] Step 3: When the sensor acquires the image signal, the image signal can be sent to the hardened 3A stats module inside the ISP to calculate the statistical data of each feature in AWB, AE, and AF of the current image signal.

[0037] Step 4: The ISP sends the statistical data calculated in Step 3 to the HAL layer software 3A Stats node;

[0038] Step 5: The 3A Stats node in the software determines whether the statistical data meets the preset conditions. If the statistical data meets the preset conditions, the Sensor will not be notified to update the status. Otherwise, if the statistical data does not meet the preset conditions, Step 6 is executed. For example, taking AE as an example, the 3A Stats node in the software determines whether the statistical data of the AE of the image signal in each frame is consistent with the statistical data of the AE previously sent to the Sensor. If they are inconsistent, it is determined that the statistical data does not meet the preset conditions. Otherwise, if they are consistent, it is determined that the statistical data meets the preset conditions.

[0039] Step 6: Notify the sensor node to update the statistical data to the sensor hardware, and then repeat steps 3 through 6.

[0040] The second path can perform the following image processing steps:

[0041] Step 1 is the same as Step 1 of the first path. The specific steps are the same as Step 1 of the first path, and will not be repeated here.

[0042] Step 2: If the hardened stats module is not used, the image signal processing node, i.e., the ISP node, will notify the ISP to disable the hardened 3A stats module through the / dev / Isp_drv device node;

[0043] Step 3, ⑦ Sensor output: When the sensor acquires the image signal, the image signal can be sent to the software: 3A stats node. The image algorithm is used to calculate the statistical data of each feature in AWB, AE, and AF of the current image signal.

[0044] Step 4: The 3A Stats node in the software determines whether the statistical data meets the preset conditions. If the statistical data meets the preset conditions, the Sensor will not be notified to update the status. Otherwise, if the statistical data does not meet the preset conditions, step 5 is executed.

[0045] Step 5: Notify the sensor node to update the statistical data to the sensor hardware, and then repeat steps 3 to 5.

[0046] However, regarding the first pathway, with the rapid advancement of image processing technology and the rapid iteration of image algorithms, a newly hardened 3A stats algorithm in the hardened 3A stats module may be replaced by a better algorithm shortly after its initial use. This renders the newly hardened 3A stats algorithm meaningless, leading not only to unstable image processing results but also increasing image processing costs due to frequent module hardening processes. Regarding the second pathway, once the 3A stats algorithm is used through the software 3A stats node, its large computational load consumes significant processor resources, causing prolonged CPU occupation. This leaves no time for processing other modules, ultimately resulting in decreased operating system performance, causing frame drops and other stuttering issues, and increasing the power consumption of electronic devices.

[0047] To address the problems in related technologies, embodiments of this application provide an image processing system, method, apparatus, device, and storage medium. The following description, in conjunction with the accompanying drawings, details... Figures 2 to 7 The image processing system provided in this application will be described in detail through specific embodiments and application scenarios.

[0048] First, combined Figure 2 This application provides a detailed description of an image processing system according to an embodiment.

[0049] Figure 2 This is a schematic diagram of the structure of an image processing system provided in an embodiment of this application.

[0050] like Figure 2 As shown, the image processing system 20 provided in this application embodiment can be installed in an electronic device. Based on this, the image processing system 20 may include:

[0051] An image statistical processing chip 201 integrated in the hardware layer and an image update algorithm node 202 set in the hardware abstraction layer; wherein...

[0052] Update image algorithm node 202 to obtain image algorithms sent from the server and send the image algorithms to image statistics processing chip 202;

[0053] The image statistical processing chip 201 is used to calculate the first feature statistics of the image signal through an image algorithm. The first feature statistics are used to adjust the target image.

[0054] In this way, the image algorithm update node can obtain the image algorithm from the server and send it to the image statistical processing chip, thereby realizing the rapid iteration of the image algorithm in the image statistical processing chip. Based on this, the first feature statistics of the image signal calculated by the image algorithm in the image statistical processing chip are closer to the feature statistics required by the user. This makes the target image adjusted by the feature statistics that are closer to the user's needs better meet the user's requirements for image processing results. In this way, the consumption of processor computing resources is reduced, and the stability of the image processing result quality is improved while the operating system performance is enhanced.

[0055] Here, the image statistical processing chip 201 in this embodiment can be integrated on a 3A stats programmable digital chip (Field Programmable Gate Array, FPGA), which is a newly added chip in the electronic device. A node can refer to a software abstraction of the FPGA hardware. For example, if the software wants to operate hardware such as the image statistical processing chip 201, it can construct an update FPGA Algo Node 202. Thus, the image statistical processing chip 201 can be controlled by updating the image algorithm node 202. Furthermore, the first feature statistics of the image signal in the above-mentioned embodiments of this application can include at least one of the following: AF statistics, AE statistics, and AWB statistics.

[0056] It should be noted that, in one instance, the image processing system in this application embodiment can be separately installed in the electronic device, that is, the current electronic device can be removed, such as... Figure 1 The structure shown allows image processing to be performed using the image processing system described in this application. In another example, it can be based on, as... Figure 1 In the structure shown, a new image processing system provided in this application embodiment is added, such as... Figure 2 As shown, image processing can be selectively performed based on two image processing systems.

[0057] The above image processing system will be described in detail below.

[0058] In one or more possible embodiments, the image algorithm update node is further configured to: obtain first version information of the image algorithm in the image statistical processing chip; obtain second version information of the image algorithm most recently issued by the server; and, if it is determined that the first version information and the second version information do not match, send the image algorithm most recently issued by the server to the image statistical processing chip to update the image algorithm in the image statistical processing chip.

[0059] The image statistical processing chip is also used to calculate the first feature statistics of the image signal based on the image algorithm recently issued by the server. The first feature statistics are used to adjust the target image.

[0060] For example, when the image algorithm update node receives the latest image algorithm from the server, it can obtain the first version information of the image algorithm in the image statistical processing chip. Thus, if the first version information of the first image algorithm in the image statistical processing chip is not the latest version provided by the server, the update node can update the first image algorithm in the image statistical processing chip using the latest image algorithm provided by the server. This ensures that the image statistical processing chip always stores the latest image algorithm, enabling rapid iteration of the image algorithm in the image statistical processing chip. Based on this, the first feature statistics of the image signal calculated by the latest image algorithm in the image statistical processing chip are closer to the feature statistics required by the user. This allows the target image adjusted with feature statistics closer to the user's needs to better meet the user's requirements for image processing results. Therefore, the process of frequently executing the image algorithm module hardening on the image signal processor is eliminated, reducing image processing costs and improving the stability of image processing result quality.

[0061] In another or more possible embodiments, the image processing system 20 in this application embodiment further includes an updated image algorithm interface disposed in the hardware abstraction layer and a first registered data channel node disposed in the driver layer;

[0062] The image algorithm update interface is called by the image algorithm update node to read the first version information from the image statistical processing chip through the first registered data channel node.

[0063] For example, such as Figure 3 As shown, a new chip hardware abstraction module (FPGA_hal.so) can be added in the hardware abstraction layer, and a new chip driver module (FPGA_driver) can be added in the driver layer. Data exchange can occur between the chip hardware abstraction module set in the hardware abstraction layer and the chip driver module set in the driver layer.

[0064] The chip hardware abstraction module may include at least one interface, which may include an updated image algorithm interface (Update 3A AlgoFW). The chip driver module may include at least one node, which includes a first registered data channel node ( / dev / dma_c2h).

[0065] Furthermore, the image processing system also includes a second registered data channel node located in the driver layer; wherein,

[0066] The image algorithm update interface is called by the image algorithm update node to write the most recently issued image algorithm from the server into the image statistical processing chip through the second registered data channel node.

[0067] For example, still refer to Figure 3 At least one node in the chip driver module may also include a second registered data channel node ( / dev / dma_h2c).

[0068] Based on this, the image algorithm update interface can be called by the image algorithm update node, and the image algorithm update interface can call the first registered data channel node. Thus, during the electronic device startup process, it can be achieved through... Figure 3 The structure shown executes the process of updating the image algorithm for the FPGA.

[0069] Specifically, such as Figure 3 As shown, during the startup process of an electronic device, the Camera HAL process in an image capture application, such as a camera application, is automatically started by the operating system (Linux) of the electronic device as a daemon process and performs the following steps:

[0070] Step 1: The Update FPGA Algo Node 202 in the Hardware Abstraction Layer will call the Update 3A AlgoFW interface in the newly added chip hardware abstraction module;

[0071] Step 2: The Update 3A AlgoFW interface will read the first version information of the first image algorithm stored in the image statistics processing chip 201 through the first registered data channel node / dev / dma_c2h;

[0072] Step 3: After the FPGA Algo Node obtains the first version information, it will match it with the second version information of the image algorithm most recently issued by the server, which is stored in the file / sdcard / camera_config / 3a_algo_ver in the electronic device.

[0073] Step 4: If the version information of the image statistics processing chip 201 is lower than the second version information, then the UpdateFPGA Algo Node will write the image algorithm most recently issued by the server into the image statistics processing chip 201 through the second registered data channel node ( / dev / dma_h2c).

[0074] It should be noted that, in one example, the file ` / sdcard / camera_config / 3a_algo_ver` only stores the second version information of the image algorithm most recently issued by the server, and does not include the image algorithm itself. Therefore, the electronic device will only be triggered to download the image algorithm corresponding to the second version information from the server when the version information of the image statistics processing chip 201 is lower than the second version information, and then write the downloaded image algorithm corresponding to the second version information into the image statistics processing chip 201 through the second registered data channel node. Thus, when the version information of the image statistics processing chip 201 is equal to the second version information, there is no need to download the latest image algorithm, saving storage space in the electronic device.

[0075] Of course, in another example, the latest image algorithm and the second version information of the latest image algorithm provided by the server can also be stored in the file / sdcard / camera_config / 3a_algo_ver. Thus, when the first version information of the first image algorithm in the image statistical processing chip 201 is lower than the second version information, the second version information can be quickly written into the image statistical processing chip 201, thereby improving the efficiency of calculating the first feature statistics of the image signal.

[0076] In another or more possible embodiments, the image processing system in this application embodiment further includes an image sensor integrated in the hardware layer and an image statistics node disposed in the hardware abstraction layer; wherein,

[0077] Image sensor for receiving second feature statistics configured by the user;

[0078] The image statistics node is used to output the first feature statistics when it is determined that the first feature statistics match the second feature statistics. The first feature statistics are used to adjust the target image.

[0079] Furthermore, image sensors are also used to acquire image signals.

[0080] For example, such as Figure 4As shown, an image statistics node (3A_stats Node) can also be set at the hardware abstraction layer. The image sensor can include a sensor that can acquire image signals and receive user-configured second feature statistics. This second feature statistics can be user-pre-configured reference data. For example, setting the second feature statistics, i.e., the AWB reference data, to interval A for AWB statistics, means that when the calculated AWB statistics value is within interval A, the image statistics node can determine that the first feature statistics match the second feature statistics. Conversely, when the calculated AWB statistics value is not within interval A, the image statistics node can determine that the first feature statistics do not match the second feature statistics.

[0081] Thus, when the first feature statistics match the second feature statistics, it indicates that the image processing result meets the user's expectations. The first feature statistics can then be output, and the target image can be adjusted using the first feature statistics to enable the electronic device to display a high-quality image.

[0082] Alternatively, in one or more possible embodiments, the image statistics node is further configured to send the first feature statistics to the image sensor if it is determined that the first feature statistics do not match the second feature statistics.

[0083] The image statistical processing chip is also used to recalculate the first feature statistical data of the image signal based on the image signal and the first feature statistical data, using the latest image algorithm issued by the server, until it is determined that the recalculated first feature statistical data matches the second feature statistical data, and then outputs the recalculated first feature statistical data.

[0084] In this way, the first feature statistics can be used as a reference parameter so that the recalculated first feature statistics can be quickly matched with the second feature statistics, thereby shortening the output of the first feature statistics required by the user and thus improving the efficiency of image processing.

[0085] In one or more possible embodiments, the image processing system in this application embodiment further includes an initialization interface disposed in the hardware abstraction layer and a configuration file node disposed in the driver layer;

[0086] The initialization interface is called by the image statistics node to send shooting mode parameters to the image statistics processing chip through the configuration file node;

[0087] The shooting mode parameter is used to trigger the image statistics processing chip to enter working mode. The shooting mode parameter is determined by the image statistics node based on the shooting mode in the application. Here, the application can be a camera application.

[0088] Furthermore, the image statistics node is also used to obtain shooting mode parameters corresponding to the shooting modes in the application from the application's runtime data.

[0089] For example, such as Figure 5 As shown, at least one interface in the chip hardware abstraction module can also be initialized. At least one node in the chip driver module can also include a configuration file node ( / dev / config_reg). The initialization interface can be called by the image statistics node, and the initialization interface can call the configuration file node. Based on this, the initialization interface can be used to send shooting mode parameters to the image statistics processing chip through the configuration file node.

[0090] Based on such Figure 4 The structure shown can execute the process of sending parameters to the FPGA after the electronic device is started, or when the user opens the camera application.

[0091] Specifically, refer to Figure 4 Given the structure, perform the following steps:

[0092] Step 1: After the electronic device receives the user's launch of the camera application, the camera application will send the current shooting mode (such as "photo", "video", etc.) and the shooting mode parameters corresponding to the shooting mode to the image statistics node 3A_stats Node.

[0093] Step 2: The image statistics node 3A_stats Node can call the initialization interface Initialize, and send the current shooting mode parameters to the image statistics processing core 201 through the configuration file node / dev / config_reg, thereby putting the image statistics processing core into working mode.

[0094] In one or more possible embodiments, the image processing system in this application further includes a control node disposed in the hardware abstraction layer; wherein,

[0095] The control node is invoked by the image capture application to adjust the working mode of the image statistics node and the image signal processor.

[0096] For example, such as Figure 6 As shown, in order to avoid interference from the original software ISP node and hardware ISP when calculating the first feature statistics of the image signal using the image algorithm recently issued by the server, the operating mode of the ISP node and hardware ISP can be adjusted to off by calling the control node through the camera application when the user starts the camera application.

[0097] In one or more possible embodiments, the image processing system in this application further includes an interrupt unit integrated in the hardware layer and a configuration file node disposed in the driver layer; wherein,

[0098] The interrupt unit is used to generate an interrupt event based on the first feature statistics output by the image statistics processing chip; and to call the configuration file node to send an interrupt notification corresponding to the interrupt event to the image statistics node. The interrupt notification is used to notify the image statistics node to read the first feature statistics from the image statistics processing chip.

[0099] Based on this, the image processing system in this embodiment further includes a processing request interface disposed in the hardware abstraction layer and a first registered data channel node disposed in the driver layer; wherein,

[0100] The request processing interface is called by the image statistics node to read the first feature statistics of image features from the image statistics processing chip through the first registered data channel node.

[0101] For example, such as Figure 7 As shown, at least one interface in the chip hardware abstraction module may also include a process request interface and an interrupt request (IRQ) unit integrated in the hardware layer.

[0102] Based on such Figure 7 The structure shown can perform 3A stats statistical procedures on image signals acquired by the sensor, specifically combined with... Figure 7 The following steps can be performed:

[0103] Step 1: When the user launches the camera application, the camera application calls the control node to adjust the working mode of the ISP Node and the hardware ISP to off;

[0104] Step 2: The sensor acquires image signals and sends them to the image statistical processing chip 201. The image statistical processing chip 201 uses the image algorithm recently issued by the server to calculate at least one of the following features of the image signal: first feature statistics of AWB, AE, and AF.

[0105] Step 3: Send the first feature statistics data to the image statistics node 3A stats Node. In this 3Astats Node, it is determined whether the first feature statistics data and the second feature statistics data of the image information match. If the first feature statistics data and the second feature statistics data match, then the Sensor will not be notified to update the status. Otherwise, the following step 4 is executed.

[0106] Step 4: The 3A stats Node notifies the sensor node to update the first feature statistics to the sensor. Then, steps 2 to 4 are executed repeatedly until the first feature statistics match the second feature statistics. The image processing system then outputs the recalculated first feature statistics. Both the first feature statistics and the recalculated first feature statistics are used to adjust the target image.

[0107] Specifically, step 3 in this embodiment can be as follows:

[0108] Step 31: After the image statistical processing chip calculates the first feature statistical data, it first generates an interrupt event through the interrupt unit;

[0109] Step 32: The interrupt unit sends the interrupt notification corresponding to the interrupt event to the chip driver module. The interrupt unit at the hardware layer implements asynchronous notification. When there is no event notification, the chip driver module is in a sleep state. In this way, the chip driver module will not occupy any CPU time slices when there is no event notification, thereby greatly reducing the CPU performance consumption.

[0110] Step 33: After receiving the interrupt notification, the chip driver module sends the interrupt notification to the image statistics node in HAL through the callback function. The interrupt notification is used to notify the image statistics node to calculate the first feature statistics data from the image statistics processing chip and read the first feature statistics data from the image statistics processing chip.

[0111] Step 34: The image statistics node calls the processing request interface in the chip hardware abstraction module and reads the first feature statistics data in the image statistics processing chip 201 through the first registered data channel node / dev / dma_c2h.

[0112] Therefore, the image processing system update node provided in this application can update the first image algorithm in the image statistical processing chip with the latest image algorithm provided by the server when it is determined that the first version information of the first image algorithm in the image statistical processing chip is not the latest version provided by the server. This ensures that the latest image algorithm is always stored in the image statistical processing chip, thereby realizing rapid iteration of the image algorithm in the image statistical processing chip. Based on this, the first feature statistics of the image signal calculated by the latest image algorithm in the image statistical processing chip are closer to the feature statistics required by the user. This makes the target image adjusted by the feature statistics that are closer to the user's requirements better meet the user's needs for image processing results. In this way, the process of frequently executing the module hardening of the image algorithm on the image signal processor is eliminated, reducing the image processing cost and improving the quality of the image processing results.

[0113] Secondly, based on the aforementioned image processing system, combined with Figure 8 This application provides a detailed description of an image processing system according to an embodiment.

[0114] Figure 8 This is a flowchart of an image processing method provided in an embodiment of this application.

[0115] like Figure 8 As shown, the image processing method provided in this application embodiment can be applied to electronic devices, which include a hardware abstraction layer, a hardware layer, and a driver layer. Based on this, the image processing method may include the following steps:

[0116] Step 810: Obtain the image algorithm sent by the server by updating the image algorithm node set in the hardware abstraction layer; Step 820: Send the image algorithm to the image statistical processing chip integrated in the hardware layer by updating the image algorithm node; Step 830: Calculate the first feature statistical data of the image signal by using the image statistical processing chip and the image algorithm. The first feature statistical data is used to adjust the target image.

[0117] In this way, image algorithms can be obtained from the server by updating the image algorithm node, and then sent to the image statistical processing chip integrated in the hardware layer. This enables rapid iteration of the image algorithm in the image statistical processing chip. Based on this, the first feature statistics of the image signal calculated by the image algorithm in the image statistical processing chip are closer to the feature statistics required by the user. This makes the target image adjusted by the feature statistics that are closer to the user's needs better meet the user's requirements for image processing results. As a result, the consumption of processor computing resources is reduced, and the stability of the image processing result quality is improved while the operating system performance is enhanced.

[0118] The steps described above are explained in detail below.

[0119] First, regarding step 810, in one or more possible embodiments, the first version information of the image algorithm in the image statistical processing chip is obtained by updating the image algorithm node; and the second version information of the image algorithm most recently issued by the server is obtained.

[0120] In another or more possible embodiments, the electronic device further includes an updated image algorithm interface disposed in the hardware abstraction layer and a first registered data channel node disposed in the driver layer. Based on this, step 810 may specifically include:

[0121] When the image algorithm update interface is called by the image algorithm update node, the first registered data channel node is called through the image algorithm update interface to read the first version information from the image statistical processing chip.

[0122] Receiving, involving step 820, in one or more possible embodiments, based on an example of step 810 described above, step 820 may specifically include:

[0123] If the first version information and the second version information are determined to be mismatched, the image algorithm most recently issued by the server is sent to the image statistical processing chip to update the image algorithm in the image statistical processing chip.

[0124] Then, relating to step 830, in one or more possible embodiments, based on the embodiment in step 810, step 830 may specifically include:

[0125] The image statistical processing chip calculates the first feature statistics of the image signal based on the image algorithm recently issued by the server. The first feature statistics are used to adjust the target image.

[0126] In another or more possible embodiments, the electronic device further includes an initialization interface disposed in the hardware abstraction layer and a configuration file node disposed in the driver layer. Based on this, before step 830, the image processing method may further include:

[0127] When the initialization interface is called by the image statistics node, the initialization interface calls the configuration file node to send the shooting mode parameters to the image statistics processing chip.

[0128] Among them, the shooting mode parameter is used to trigger the image statistics processing chip to enter the working mode. The shooting mode parameter is determined by the image statistics node based on the shooting mode in the application.

[0129] Based on this, prior to step 830, the image processing method may further include:

[0130] By using the image statistics node, the shooting mode parameters corresponding to the shooting mode in the image shooting application are obtained from the running data of the image shooting application.

[0131] Furthermore, prior to step 830, the electronic device also includes a control node disposed in the hardware abstraction layer, and the image processing method may further include:

[0132] When the control node is invoked by the application, the working mode of the image statistics node and the working mode of the image signal processor are adjusted through the control node.

[0133] Additionally, in one or more possible embodiments, after step 830, the electronic device further includes a second registered data channel node disposed in the driving layer. Based on this, the image processing method may further include:

[0134] When the image algorithm update interface is called by the image algorithm update node, the second registered data channel node is called through the image algorithm update interface to write the image algorithm most recently issued by the server into the image statistical processing chip.

[0135] In another or more possible embodiments, following step 830, the electronic device further includes an image sensor integrated in the hardware layer and an image statistics node disposed in the hardware abstraction layer. Based on this, the image processing method may further include:

[0136] Receive user-configured second feature statistics via an image sensor;

[0137] By using the image statistics node, if it is determined that the first feature statistics match the second feature statistics, the first feature statistics are output. The first feature statistics are used to adjust the target image.

[0138] In one or more possible embodiments, after step 830, the electronic device further includes an interrupt unit integrated in the hardware layer and a configuration file node disposed in the driver layer. Based on this, after step 830, the image processing method may further include:

[0139] An interrupt event is generated by the interrupt unit based on the first feature statistics output by the image statistics processing chip.

[0140] The interrupt unit calls the configuration file node to send an interrupt notification corresponding to the interrupt event to the image statistics node. The interrupt notification is used to notify the image statistics node to read the first feature statistics data from the image statistics processing chip.

[0141] Furthermore, the electronic device also includes a processing request interface disposed in the hardware abstraction layer and a first registered data channel node disposed in the driver layer. Based on this, after step 830, the image processing method may further include:

[0142] When the request processing interface is called by the image statistics node, the first registered data channel node is called through the request processing interface to read the first feature statistics data of the image features from the image statistics processing chip.

[0143] In one or more possible embodiments, after step 830, the image processing method may further include:

[0144] If the first feature statistics data and the second feature statistics data do not match, the first feature statistics data are sent to the image sensor through the image statistics node.

[0145] The image statistical processing chip recalculates the first feature statistics of the image signal based on the image signal and the first feature statistics, using the latest image algorithm issued by the server, until it is determined that the recalculated first feature statistics match the second feature statistics, and then outputs the recalculated first feature statistics.

[0146] The image processing method provided in this application can be executed by an image processing device. This application uses an image processing device executing the image processing method as an example to illustrate the apparatus of the image processing method provided in this application.

[0147] Based on the same inventive concept, this application also provides an image processing apparatus. (Specifically combined with...) Figure 9 Please provide a detailed explanation.

[0148] Figure 9 This is a schematic diagram of the structure of an image processing device provided in an embodiment of this application.

[0149] like Figure 9 As shown, the image processing device 90 can be applied to electronic devices, and the image processing device 90 specifically includes:

[0150] The acquisition module 901 is used to acquire the image algorithm issued by the server through the image algorithm update node set in the hardware abstraction layer;

[0151] The transmission module 902 is used to send image algorithms to the image statistical processing chip integrated in the hardware layer by updating the image algorithm node;

[0152] The calculation module 903 is used to calculate the first feature statistics of the image signal through the image statistical processing chip and the image algorithm. The first feature statistics are used to adjust the target image.

[0153] The steps described above are explained in detail below.

[0154] In one or more possible embodiments, the acquisition module 901 is further configured to: acquire the first version information of the image algorithm in the image statistical processing chip by updating the image algorithm node; and acquire the second version information of the image algorithm most recently issued by the server.

[0155] In another or more possible embodiments, the image processing apparatus 90 may further include a first reading module; wherein,

[0156] The first reading module is used to read first version information from the image statistical processing chip by calling the first registered data channel node through the image update algorithm interface when the electronic device also includes an update image algorithm interface set in the hardware abstraction layer and a first registered data channel node set in the driver layer, and the update image algorithm interface is called by the update image algorithm node.

[0157] In one or more possible embodiments, the transmission module 902 may also be used to send the most recently issued image algorithm from the server to the image statistical processing chip to update the image algorithm in the image statistical processing chip if it is determined that the first version information and the second version information do not match.

[0158] In one or more possible embodiments, the calculation module 903 may also be used to calculate a first feature statistical data of the image signal based on the image algorithm most recently issued by the server through the image statistical processing chip, and the first feature statistical data is used to adjust the target image.

[0159] In one or more possible embodiments, the transmission module 902 can also be used to send shooting mode parameters to the image statistics processing chip by calling the configuration file node through the initialization interface when the electronic device also includes an initialization interface set in the hardware abstraction layer and a configuration file node set in the driver layer, and the initialization interface is called by the image statistics node; wherein, the shooting mode parameters are used to trigger the image statistics processing chip to be in working mode, and the shooting mode parameters are determined by the image statistics node based on the shooting mode in the application.

[0160] In one or more possible embodiments, the acquisition module 901 can also be used to acquire, through the image statistics node, shooting mode parameters corresponding to the shooting mode in the image shooting application from the running data of the image shooting application.

[0161] In one or more possible embodiments, the image processing apparatus 90 may further include an adjustment module; wherein,

[0162] The adjustment module is used to adjust the working mode of the image statistics node and the working mode of the image signal processor through the control node when the electronic device also includes a control node set in the hardware abstraction layer and the control node is invoked by the application.

[0163] In one or more possible embodiments, the image processing apparatus 90 may further include a processing module; wherein,

[0164] The processing module is used to write the most recently issued image algorithm from the server into the image statistical processing chip by calling the second registered data channel node through the image update algorithm interface when the electronic device also includes a second registered data channel node set in the driver layer and the image update algorithm interface is called by the image update algorithm node.

[0165] In one or more possible embodiments, the image processing apparatus 90 may further include a receiving module and an output module; wherein,

[0166] The receiving module is used to receive second feature statistics configured by the user through the image sensor, in cases where the electronic device also includes an image sensor integrated in the hardware layer and an image statistics node set in the hardware abstraction layer.

[0167] The output module is used to output the first feature statistics data when the first feature statistics data matches the second feature statistics data data, based on the image statistics node. The first feature statistics data ...

[0168] In one or more possible embodiments, the image processing apparatus 90 may further include a generation module and an output module; wherein,

[0169] The generation module is used to generate interrupt events through the interrupt unit based on the first feature statistics output by the image statistics processing chip, in cases where the electronic device also includes an interrupt unit integrated in the hardware layer and a configuration file node set in the driver layer.

[0170] The transmission module 902 is also used to send an interrupt notification corresponding to the interrupt event to the image statistics node by calling the configuration file node through the interrupt unit. The interrupt notification is used to notify the image statistics node to read the first feature statistics data from the image statistics processing chip.

[0171] In one or more possible embodiments, the image processing apparatus 90 may further include a second reading module; wherein,

[0172] The second reading module is used to read the first feature statistics of image features from the image statistics processing chip by calling the first registered data channel node through the processing request interface when the electronic device also includes a processing request interface set in the hardware abstraction layer and a first registered data channel node set in the driver layer.

[0173] In one or more possible embodiments, the transmission module 902 is further configured to send the first feature statistics data to the image sensor via the image statistics node when it is determined that the first feature statistics data and the second feature statistics data do not match.

[0174] The calculation module 903 is also used to recalculate the first feature statistics of the image signal based on the image signal and the first feature statistics using the latest image algorithm issued by the server, through the image statistical processing chip, until it is determined that the recalculated first feature statistics match the second feature statistics, and output the recalculated first feature statistics.

[0175] The image processing device in this application embodiment can be an electronic device or a component within an electronic device, such as an integrated circuit or a chip. The electronic device can be a terminal or other devices besides a terminal. For example, the electronic device can be a mobile phone, tablet computer, laptop computer, PDA, in-vehicle electronic device, mobile internet device (MID), augmented reality (AR) / virtual reality (VR) device, robot, wearable device, ultra-mobile personal computer (UMPC), netbook, or personal digital assistant (PDA), etc. It can also be a server, network attached storage (NAS), personal computer (PC), television set (TV), ATM, or self-service machine, etc. This application embodiment does not specifically limit the device.

[0176] The image processing device in this application embodiment can be a device with an operating system. The operating system can be Android, iOS, or other possible operating systems; this application embodiment does not specifically limit the specific operating system.

[0177] The device coordination apparatus provided in this application embodiment can achieve... Figure 8 The various processes implemented in the image processing method embodiments shown achieve the same technical effect, and will not be described again here to avoid repetition.

[0178] Based on this, the image processing apparatus provided in this application embodiment can obtain image algorithms from the server by updating the image algorithm node, and send the image algorithm to the image statistical processing chip integrated in the hardware layer by updating the image algorithm node, thereby realizing rapid iteration of the image algorithm in the image statistical processing chip. Based on this, the first feature statistics of the image signal calculated by the image algorithm in the image statistical processing chip are closer to the feature statistics required by the user, so that the target image adjusted by the feature statistics that are closer to the user's requirements can better meet the user's needs for image processing results. In this way, the consumption of processor computing resources is reduced, and the stability of the image processing result quality is improved while the operating system performance is enhanced.

[0179] It should be noted that the electronic devices in the embodiments of this application include the aforementioned mobile electronic devices and non-mobile electronic devices.

[0180] Figure 11 This is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of this application.

[0181] The electronic device 1100 includes, but is not limited to, the following components: radio frequency unit 1101, network module 1102, audio output unit 1103, input unit 1104, sensor 1105, display unit 1106, user input unit 1107, interface unit 1108, memory 1109, processor 1110, etc.

[0182] Those skilled in the art will understand that the electronic device 1100 may also include a power supply (such as a battery) for supplying power to various components. The power supply may be logically connected to the processor 1110 through a power management system, thereby enabling functions such as managing charging, discharging, and power consumption through the power management system. Figure 11 The electronic device structure shown does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown, or combine certain components, or have different component arrangements, which will not be elaborated here.

[0183] In this embodiment, the processor 1110 is configured to obtain an image algorithm sent from the server via an image algorithm update node located in the hardware abstraction layer. The processor 1110 can also be configured to send the image algorithm to an image statistical processing chip integrated in the hardware layer via the image algorithm update node. Furthermore, the processor 1110 can be configured to calculate a first feature statistical data of the image signal using the image statistical processing chip and the image algorithm; the first feature statistical data is used to adjust the target image.

[0184] The steps described above are explained in detail below.

[0185] In one or more possible embodiments, the processor 1110 is further configured to: obtain first version information of the image algorithm in the image statistical processing chip by updating the image algorithm node; and obtain second version information of the image algorithm most recently issued by the server.

[0186] In another or one possible embodiment, the processor 1110 is further configured to, when the electronic device further includes an update image algorithm interface disposed in the hardware abstraction layer and a first registered data channel node disposed in the driver layer, and the update image algorithm interface is called by the update image algorithm node, call the first registered data channel node through the update image algorithm interface to read the first version information from the image statistical processing chip.

[0187] In one or more possible embodiments, the processor 1110 is further configured to, if it is determined that the first version information and the second version information do not match, send the most recently issued image algorithm from the server to the image statistics processing chip to update the image algorithm in the image statistics processing chip.

[0188] In one or more possible embodiments, the processor 1110 is further configured to calculate a first feature statistical data of the image signal based on the image algorithm most recently issued by the server, using an image statistical processing chip, wherein the first feature statistical data is used to adjust the target image.

[0189] In one or more possible embodiments, the processor 1110 is further configured to, when the electronic device also includes an initialization interface disposed in the hardware abstraction layer and a configuration file node disposed in the driver layer, and the initialization interface is called by the image statistics node, call the configuration file node through the initialization interface to send shooting mode parameters to the image statistics processing chip; wherein, the shooting mode parameters are used to trigger the image statistics processing chip to be in working mode, and the shooting mode parameters are determined by the image statistics node based on the shooting mode in the application.

[0190] In one or more possible embodiments, the processor 1110 is further configured to obtain, via an image statistics node, shooting mode parameters corresponding to the shooting mode in the image shooting application from the running data of the image shooting application.

[0191] In one or more possible embodiments, the processor 1110 is also configured to adjust the operating mode of the image statistics node and the operating mode of the image signal processor by means of the control node, when the electronic device further includes a control node disposed in the hardware abstraction layer and the control node is invoked by the application.

[0192] In one or more possible embodiments, the processor 1110 is further configured to, when the electronic device also includes a second registered data channel node disposed in the driver layer, and the image algorithm update interface is called by the image algorithm update node, call the second registered data channel node through the image algorithm update interface to write the most recently issued image algorithm from the server into the image statistical processing chip.

[0193] In one or more possible embodiments, the processor 1110 is further configured to receive, via the image sensor, a second feature statistical data set by the user, when the electronic device further includes an image sensor integrated in the hardware layer and an image statistics node disposed in the hardware abstraction layer.

[0194] By using the image statistics node, if it is determined that the first feature statistics match the second feature statistics, the first feature statistics are output. The first feature statistics are used to adjust the target image.

[0195] In one or more possible embodiments, the processor 1110 is further configured to, in the case that the electronic device further includes an interrupt unit integrated in the hardware layer and a configuration file node set in the driver layer, generate an interrupt event through the interrupt unit based on the first feature statistics output by the image statistics processing chip.

[0196] The interrupt unit calls the configuration file node to send an interrupt notification corresponding to the interrupt event to the image statistics node. The interrupt notification is used to notify the image statistics node to read the first feature statistics data from the image statistics processing chip.

[0197] In one or more possible embodiments, the processor 1110 is further configured to, when the electronic device also includes a processing request interface disposed in the hardware abstraction layer and a first registered data channel node disposed in the driver layer, and the processing request interface is invoked by the image statistics node, invoke the first registered data channel node through the processing request interface to read the first feature statistics data of the image features from the image statistics processing chip.

[0198] In one or more possible embodiments, the processor 1110 is further configured to send the first feature statistics to the image sensor via the image statistics node if it is determined that the first feature statistics do not match the second feature statistics.

[0199] The image statistical processing chip recalculates the first feature statistics of the image signal based on the image signal and the first feature statistics, using the latest image algorithm issued by the server, until it is determined that the recalculated first feature statistics match the second feature statistics, and then outputs the recalculated first feature statistics.

[0200] It should be understood that the input unit 1104 may include a graphics processing unit (GPU) 11041 and a microphone 11042. The GPU 11041 processes image data of still images or videos acquired by an image capture device (such as a camera) in video capture mode or image capture mode. The display unit 1106 may include a display panel, which may be configured in the form of a liquid crystal display, an organic light-emitting diode, or the like. The user input unit 1107 includes at least one of a touch panel 11071 and other input devices 11072. The touch panel 11071 is also called a touch screen. The touch panel 11071 may include a touch detection device and a touch display. Other input devices 11072 may include, but are not limited to, a physical keyboard, function keys (such as volume display buttons, power buttons, etc.), a trackball, a mouse, and a joystick, which will not be described in detail here.

[0201] The memory 1109 can be used to store software programs and various data. The memory 1109 may primarily include a first storage area for storing programs or instructions and a second storage area for storing data. The first storage area may store the operating system, application programs or instructions required for at least one function (such as sound playback function, image playback function, etc.). Furthermore, the memory 1109 may include volatile memory or non-volatile memory, or both. The non-volatile memory may be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory can be random access memory (RAM), static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct memory bus RAM (DRRAM). The memory 1109 in this embodiment includes, but is not limited to, these and any other suitable types of memory.

[0202] Processor 1110 may include one or more processing units; optionally, processor 1110 integrates an application processor and a modem processor, wherein the application processor mainly handles operations involving the operating system, user interface, and applications, and the modem processor mainly handles wireless display signals, such as a baseband processor. It is understood that the aforementioned modem processor may also not be integrated into processor 1110.

[0203] This application also provides a readable storage medium storing a program or instructions. When the program or instructions are executed by a processor, they implement the various processes of the above-described image processing method embodiments and achieve the same technical effects. To avoid repetition, they will not be described again here.

[0204] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0205] In addition, this application embodiment provides another chip, which includes a processor and a display interface. The display interface and the processor are coupled. The processor is used to run programs or instructions to implement the various processes of the above-described image processing method embodiments and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0206] It should be understood that the chip mentioned in the embodiments of this application may also be referred to as a system-on-a-chip, system chip, chip system, or system-on-a-chip, etc.

[0207] This application provides a computer program product, which is stored in a storage medium and executed by at least one processor to implement the various processes of the above-described image processing method embodiments, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0208] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0209] Furthermore, it should be noted that the scope of the methods and apparatus in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. In addition, features described with reference to certain examples may be combined in other examples.

[0210] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a computer software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods of the various embodiments of this application.

[0211] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

Claims

1. An image processing system, characterized in that, include: An image statistical processing chip integrated in the hardware layer and an image update algorithm node set in the hardware abstraction layer; The image algorithm update node is used to obtain the image algorithm issued by the server and send the image algorithm to the image statistics processing chip; The image statistical processing chip is used to calculate a first feature statistical data of the image signal through the image algorithm, and the first feature statistical data is used to adjust the target image; The image processing system also includes an image sensor integrated in the hardware layer, an image statistics node set in the hardware abstraction layer, an initialization interface set in the hardware abstraction layer, and a configuration file node set in the driver layer; The image sensor is used to acquire second feature statistics. The image statistics node is used to output the first feature statistics when it is determined that the first feature statistics match the second feature statistics. The first feature statistics are used to adjust the target image. The initialization interface is called by the image statistics node to send shooting mode parameters to the image statistics processing chip through the configuration file node; wherein, the shooting mode parameters are used to trigger the image statistics processing chip to enter the working mode, and the shooting mode parameters are determined by the image statistics node based on the shooting mode of the application.

2. The system according to claim 1, characterized in that, The image algorithm update node is further configured to: obtain first version information of the image algorithm in the image statistical processing chip; obtain second version information of the image algorithm most recently issued by the server; and, if it is determined that the first version information and the second version information do not match, send the image algorithm most recently issued by the server to the image statistical processing chip to update the image algorithm in the image statistical processing chip. The image statistical processing chip is also used to calculate a first feature statistical data of the image signal using the image algorithm most recently issued by the server. The first feature statistical data is used to adjust the target image.

3. The system according to claim 2, characterized in that, The image processing system also includes an image update algorithm interface set in the hardware abstraction layer and a first registered data channel node set in the driver layer. The updated image algorithm interface is called by the updated image algorithm node to read the first version information from the image statistical processing chip through the first registered data channel node.

4. The system according to claim 3, characterized in that, The image processing system also includes a second registered data channel node disposed in the driver layer; wherein... The image update algorithm interface is called by the image update algorithm node to write the most recently issued image algorithm from the server into the image statistics processing chip through the second registered data channel node.

5. The system according to claim 1, characterized in that, The image statistics node is also used to obtain shooting mode parameters corresponding to the shooting mode in the application from the application's running data.

6. The system according to claim 1 or 5, characterized in that, The image processing system further includes a control node disposed in the hardware abstraction layer; wherein... The control node is invoked by the application to adjust the working mode of the image statistics node and the working mode of the image signal processor.

7. The system according to claim 1, characterized in that, The image processing system also includes an interrupt unit integrated in the hardware layer and a configuration file node located in the driver layer; wherein... The interrupt unit is configured to generate an interrupt event based on the first feature statistics output by the image statistics processing chip; and to call the configuration file node to send an interrupt notification corresponding to the interrupt event to the image statistics node, wherein the interrupt notification is used to notify the image statistics node to read the first feature statistics from the image statistics processing chip.

8. The system according to claim 7, characterized in that, The image processing system also includes a processing request interface set in the hardware abstraction layer and a first registered data channel node set in the driver layer. The processing request interface is invoked by the image statistics node to read the first feature statistics data of the image features from the image statistics processing chip through the first registered data channel node.

9. The system according to claim 1, characterized in that, The image statistics node is also used to send the first feature statistics to the image sensor when it is determined that the first feature statistics do not match the second feature statistics. The image statistical processing chip is also used to recalculate the first feature statistical data of the image signal based on the image signal and the first feature statistical data, using the image algorithm most recently issued by the server. If the recalculated first feature statistics match the second feature statistics, the recalculated first feature statistics are output.

10. An image processing method, characterized in that, include: By setting the image algorithm update node in the hardware abstraction layer, the image algorithm issued by the server can be obtained; The image algorithm is sent to the image statistical processing chip integrated in the hardware layer through the updated image algorithm node; The image statistical processing chip and the image algorithm are used to calculate the first feature statistical data of the image signal, which is used to adjust the target image. Second feature statistics are obtained by using an image sensor integrated into the hardware layer; By setting an image statistics node in the hardware abstraction layer, when it is determined that the first feature statistics match the second feature statistics, the first feature statistics are output, and the first feature statistics are used to adjust the target image. By calling the initialization interface set in the hardware abstraction layer through the image statistics node set in the hardware abstraction layer, and sending shooting mode parameters to the image statistics processing chip through the configuration file node set in the driver layer; wherein, the shooting mode parameters are used to trigger the image statistics processing chip to enter the working mode, and the shooting mode parameters are determined by the image statistics node based on the shooting mode of the application.

11. An electronic device, characterized in that, include: A processor, a memory, and a program or instructions stored in the memory and executable on the processor, wherein the program or instructions, when executed by the processor, implement the steps of the image processing method as claimed in claim 10.

Images