CN114025079A - Method, device and system for processing image quality optimization parameters - Google Patents
Method, device and system for processing image quality optimization parameters Download PDFInfo
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Abstract
The embodiment of the invention provides a processing method, a device, a system, electronic equipment and a readable storage medium for image quality optimization parameters, wherein the method comprises the following steps: after finishing the image quality tuning, determining optimization parameter information output by each tuning module; and providing the optimized parameter information to corresponding imaging equipment in a data flow mode by adopting a preset data transmission rule so that the imaging equipment hijacks the optimized parameter information to a memory data segment of corresponding target initial optimized parameter information. According to the embodiment of the invention, the correlation between the compiler and the Tuning XML data is bypassed in a memory hijack mode, and the problems of cost and efficiency caused by different compilers adopted by different processing chips are solved.
Description
Technical Field
The present invention relates to the field of image processing technologies, and in particular, to a method and an apparatus for processing image quality optimization parameters, a system for processing image quality optimization parameters, an electronic device, and a computer-readable storage medium.
Background
The vision technology of the intelligent Internet of things industry is rapidly developed, and the purposes of high information content and low hardware investment can be achieved by a camera, a look-around monitoring device and a vision device by means of a lens with a wide field angle. Certain quality problems still exist with current camera products, including: modeling problems (distortion, chromatic aberration, blur, mottle, etc.), Sensor problems (noise, color, dead spots, etc.), reduction, mounting accuracy (viewing angle difference, viewing axis deviation, tilt deviation, etc.). The module and Sensor problem can be corrected by adjusting the Image Quality Tuning (Image Quality Tuning), which means that the performance of the camera is optimized by adjusting the system software, hardware and optical parameters according to the application requirements of the camera. However, the tools, processes and module groups for adjusting the imaging quality are different for different processing chips, and have great difference.
From the perspective of Camera developers, for Tuning parameter files under different platform conditions, namely, Tuning XML files, a corresponding Tuning compiler is compiled through a development kit provided by a platform, Tuning results are compiled into binary files adapted to the platform and a Sensor, and Tuning bin file patterns adopted by most platforms are provided for CAMHAL to perform Tuning control. Therefore, for the Camera developer, in the process of connecting the Tuning result and the platform, the independent development work caused by the difference of the compiler is inevitable, and the Tuning problem caused by the compiler is more difficult to locate and modify than the imaging quality problem, thereby affecting the efficiency of the whole Tuning process.
Disclosure of Invention
In view of the above problems, embodiments of the present invention are proposed to provide a processing method of an image quality optimization parameter and a corresponding processing apparatus of an image quality optimization parameter, a processing system of an image quality optimization parameter, an electronic device, and a computer-readable storage medium, which overcome or at least partially solve the above problems.
The embodiment of the invention discloses a processing method of image quality optimization parameters, which is applied to a server and comprises the following steps:
after finishing the image quality tuning, determining optimization parameter information output by each tuning module;
providing the optimized parameter information to corresponding imaging equipment in a data flow mode by adopting a preset data transmission rule so that the imaging equipment hijacks the optimized parameter information to a memory data segment of corresponding target initial optimized parameter information; the preset data transfer rules enable the imaging device to access the optimization parameter information.
Optionally, the providing the optimized parameter information to the corresponding imaging device in a data stream manner by using a preset data transfer rule includes:
and providing the optimization parameter information carrying the corresponding data storage information, the corresponding tuning module identification information and the corresponding tuning module function description information to the imaging equipment in a data flow mode.
The embodiment of the invention also discloses another processing method of the image quality optimization parameters, which is applied to imaging equipment, wherein the imaging equipment stores the initial optimization parameter information, and the method comprises the following steps:
acquiring optimization parameter information provided according to a preset data transmission rule, and determining target initial optimization parameter information corresponding to the optimization parameter information;
hijacking the optimized parameter information to a memory data segment corresponding to the target initial optimized parameter information.
Optionally, the imaging device has a first functional interface, and before determining the target initial optimization parameter information corresponding to the optimization parameter information, the method further includes:
searching a data stream for transmitting the initial optimization parameter information through the first functional interface in a hardware abstraction layer and an application framework layer of the imaging device;
judging whether the data storage capacity of all the optimization parameter information is far greater than that of all the initial optimization parameter information;
and if so, executing the step of determining the target initial optimization parameter information corresponding to the optimization parameter information.
Optionally, the determining of the target initial optimization parameter information corresponding to the optimization parameter information includes:
performing keyword matching on the function description information of the tuning and optimizing module and the function description information in the initial optimization parameter information to obtain corresponding matching degree;
and if the matching degree is greater than a preset matching threshold, determining the initial optimization parameter information corresponding to the matching degree as the target initial optimization parameter information of the optimization parameter information.
Optionally, hijacking the optimized parameter information to the memory data segment corresponding to the target initial optimized parameter information includes:
determining the initial position of hijacking the optimized parameter information to the memory data segment;
determining a data conversion relation between the optimization parameter information and the target initial optimization parameter information;
and after the optimized parameter information is subjected to data conversion according to the data conversion relation, hijacking the optimized parameter information subjected to data conversion into the memory data segment from the initial position.
Optionally, the determining to hijack the optimization parameter information to the start position in the memory data segment includes:
determining a cross-correlation function between the optimization parameter information and the target initial optimization parameter information, and determining a maximum value position of the cross-correlation function; the optimization parameter information and the target initial optimization parameter information are both column vector parameter information;
and hijacking the optimization parameter information to the initial position in the memory data segment by using the maximum position.
Optionally, the determining a data conversion relationship between the optimization parameter information and the target initial optimization parameter information includes:
taking the initial position as an initial point, taking the length of the data segment of the optimized parameter information as a step length, and extracting a first data segment from the memory data segment;
taking the data segment corresponding to the optimization parameter information as a second data segment;
and fitting the transformation equations of the first data segment and the second data segment by a least square method to obtain the corresponding data conversion relation.
The embodiment of the invention also discloses a processing device of the image quality optimization parameters, which is applied to a server, and the device comprises:
the determining module is used for determining the optimization parameter information output by each adjusting and optimizing module after the image quality adjustment and optimization are finished;
the providing module is used for providing the optimized parameter information to the corresponding imaging equipment in a data flow mode by adopting a preset data transmission rule so that the imaging equipment hijacks the optimized parameter information to a memory data segment of the corresponding target initial optimized parameter information; the preset data transfer rules enable the imaging device to access the optimization parameter information.
Optionally, the providing module includes:
and the providing sub-module is used for providing the optimization parameter information carrying the corresponding data storage information, the corresponding tuning module identification information and the corresponding tuning module function description information to the imaging equipment in a data flow mode.
The embodiment of the invention also discloses another processing device for the image quality optimization parameters, which is applied to imaging equipment, wherein the imaging equipment stores initial optimization parameter information, and the device comprises:
the system comprises an acquisition module, a data transmission module and a data transmission module, wherein the acquisition module is used for acquiring optimization parameter information provided according to a preset data transmission rule and determining target initial optimization parameter information corresponding to the optimization parameter information;
and the hijacking module is used for hijacking the optimized parameter information into the memory data segment corresponding to the target initial optimized parameter information.
Optionally, the imaging device has a first functional interface, and the apparatus further includes:
a searching module, configured to search, in a hardware abstraction layer and an application framework layer of the imaging device, a data stream that transmits the initial optimization parameter information through the first functional interface;
the judging module is used for judging whether the data storage capacity of all the optimized parameter information is far greater than that of all the initial optimized parameter information;
and the execution module is used for executing the step of determining the target initial optimization parameter information corresponding to the optimization parameter information if the target initial optimization parameter information is the same as the optimization parameter information.
Optionally, the optimization parameter information carries corresponding tuning module function description information, and the obtaining module includes:
the matching sub-module is used for performing keyword matching on the function description information of the tuning module and the function description information in the initial optimization parameter information to obtain a corresponding matching degree;
a first determining submodule, configured to determine, if the matching degree is greater than a preset matching threshold, the initial optimization parameter information corresponding to the matching degree as the target initial optimization parameter information of the optimization parameter information.
Optionally, the hijacking module includes:
the second determining submodule is used for determining that the optimized parameter information is hijacked to the initial position in the memory data segment;
a third determining submodule, configured to determine a data conversion relationship between the optimization parameter information and the target initial optimization parameter information;
and the hijacking sub-module is used for hijacking the optimized parameter information after data conversion into the memory data segment from the initial position after the optimized parameter information performs data conversion according to the data conversion relation.
Optionally, the second determining sub-module includes:
a first determining unit, configured to determine a cross-correlation function between the optimization parameter information and the target initial optimization parameter information, and determine a maximum position of the cross-correlation function; the optimization parameter information and the target initial optimization parameter information are both column vector parameter information;
a second determining unit, configured to hijack the optimized parameter information to the start position in the memory data segment using the maximum position as the start position.
Optionally, the third determining sub-module includes:
an extracting unit, configured to extract a first data segment from the memory data segment by using the start position as a start point and using a data segment length of the optimized parameter information as a step length;
a third determining unit, configured to use a data segment corresponding to the optimization parameter information as a second data segment;
and the fitting unit is used for fitting the transformation equations of the first data segment and the second data segment by a least square method to obtain the corresponding data conversion relation.
The embodiment of the invention also discloses a processing system of the image quality optimization parameters, which comprises a server and the imaging equipment, wherein the imaging equipment stores the initial optimization parameter information;
the server is used for determining the optimization parameter information output by each tuning module after the image quality tuning is finished; providing the optimized parameter information to corresponding imaging equipment in a data flow mode by adopting a preset data transmission rule;
the imaging device is used for acquiring optimization parameter information provided according to a preset data transmission rule and determining target initial optimization parameter information corresponding to the optimization parameter information; hijacking the optimized parameter information to a memory data segment corresponding to the target initial optimized parameter information.
The embodiment of the invention also discloses an electronic device, which comprises: a processor, a memory and a computer program stored on said memory and capable of running on said processor, said computer program, when executed by said processor, implementing the steps of a method of processing image quality optimization parameters as described above.
The embodiment of the invention also discloses a computer readable storage medium, wherein a computer program is stored on the computer readable storage medium, and when the computer program is executed by a processor, the steps of the processing method for the image quality optimization parameters are realized.
The embodiment of the invention has the following advantages:
in the embodiment of the present invention, the server may provide the optimized parameter information to the imaging device in a data stream manner by using a preset data transmission rule, and the imaging device may hijack the optimized parameter information directly to the memory data segment of the corresponding target initial optimized parameter information. By adopting the method, the correlation between the compiler and the Tuning XML data is bypassed in a memory hijack mode, and the problems of cost and efficiency caused by different compilers adopted by different processing chips are solved.
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Fig. 1 is a flowchart illustrating steps of a method for processing image quality optimization parameters according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating steps of another method for processing image quality optimization parameters according to an embodiment of the present invention;
FIG. 3 is a flowchart illustrating steps of a system for processing image quality optimization parameters according to an embodiment of the present invention;
fig. 4 is a block diagram of a processing apparatus for optimizing image quality according to an embodiment of the present invention;
fig. 5 is a block diagram of another image quality optimization parameter processing apparatus according to an embodiment of the present invention.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below, and it is apparent that the described embodiments are only a part of the embodiments of the present invention, not all of them. All other embodiments that can be derived by one of ordinary skill in the art from the embodiments given herein are intended to be within the scope of the present invention.
Camera Tuning refers to a process of adjusting the imaging quality of a Camera by a chip platform tool. The Tuning chip platform is an integrated circuit assembly with an independent computing control unit (CPU), supports System On Chip (SOC) development, and can support software and hardware expansion (such as video card, storage, video capture, and the like). The TuningBIN file refers to a tuningdata file read by a camera hardware abstraction layer (CAMHAL). The Tuning XML file is also a Tuning data file for storing tuned Tuning parameters. The Tuning BIN file is generated from a Tuning XML file. CAMHAL refers to the hardware abstraction layer of Camera, and provides an interface for controlling hardware for software.
The tools, processes and module groups for adjusting the imaging quality are different or even have larger differences according to different processing chips. For example: under the Haesi platform, there is a separate module 3DNR for denoising, while the high-pass platform does not exist. The differences between the different platforms make the platforms relatively independent.
From the perspective of Camera developers, for Tuning parameter files under different platform conditions, namely, Tuning XML files, a corresponding Tuning compiler is compiled through a development kit provided by a platform, Tuning results are compiled into binary files adapted to the platform and a Sensor, and Tuning bin file patterns adopted by most platforms are provided for CAMHAL to perform Tuning control. Therefore, for the Camera developer, in the process of connecting the Tuning result and the platform, the independent development work caused by the difference of the compiler is inevitable, and the Tuning problem caused by the compiler is more difficult to locate and modify than the imaging quality problem, thereby affecting the efficiency of the whole Tuning process.
For compiler differences, the problem of differences between different chip platforms is still solved in development mode at present, namely: 1) the platform provides a development kit; 2) generating a compiler based on the development kit; 3) generating a Tuning XML file based on CameraTuning; 4) compiling the Tuning XML file through a compiler which is matched with the Sensor through a corresponding platform, and shooting on imaging equipment; 5) if the shooting process is normal, the compiler is proved to have no obvious logic problem, otherwise, the operation is continued to be carried out for 2) -4).
In the above compiling process of Tuning parameters, if there is a large difference between the actual imaging quality and the XML adjustment quality or the simulation quality, the difficulty in positioning and solving the imaging quality problem will be increased. At present, an effective solution is not provided for the difference of compilers, and because the combinations of the chip platform and the sensor are different, if all the combinations are exhausted, the number of the generated compilers is tens of thousands, and the verification investment for each compiler is also very large.
In summary, independent development and production of compilers with different platforms increases the Tuning trial and error cost. The investment brought by the platform and Sensor-based exhaustive compiling mode is intolerable. Currently, there is no method to mitigate the cost or efficiency issues with compiler differences.
One of the core ideas of the embodiment of the present invention is that a server can provide optimized parameter information to an imaging device in a data stream manner by using a preset data transmission rule, and the imaging device can hijack the optimized parameter information to a memory data segment of corresponding target initial optimized parameter information directly. By adopting the method, the correlation between the compiler and the Tuning XML data is bypassed in a memory hijack mode, and the problems of cost and efficiency caused by different compilers adopted by different processing chips are solved.
Referring to fig. 1, a flowchart illustrating steps of a processing method for an image quality optimization parameter according to an embodiment of the present invention is shown, and applied to a server, the method may specifically include the following steps:
and 101, after the image quality tuning is finished, determining optimization parameter information output by each tuning module.
The server may be a server in communication connection with the chip platform debugging tool, or may be a server where the chip platform debugging tool is located.
In the embodiment of the invention, a plurality of tuning models are arranged in the chip platform debugging tool for tuning the imaging quality, and after the imaging quality is tuned on the chip platform debugging tool, each tuning module of the chip platform debugging tool outputs corresponding optimized parameter information. In one example, the optimization parameter information may be stored in an XML file. The optimization parameter information may also be vectorized. The tuning module may include BLC (black level compensation), LSC (lens shading correction), Demosaic (color interpolation), Gamma, and the like.
For example, in the debugging tool of the chip platform, based on the description file of the chip platform and the initial TuningXML file, it can be determined to perform the image quality tuning, and the tuning module required to be involved in the debugging tool of the chip platform is recorded as ie [1, N ∈ [ ]]And the XML column vector parameter m output by the tuning moduleiAssuming that N E Z exists+A module capable of representing all XML column vector parameters in a set form, and is written as M ═ Mi|miE.g. R }. That is, in the embodiment of the present invention, the set model may be used to represent the optimization parameter information output by all tuning modules.
And step 102, providing the optimized parameter information to the corresponding imaging equipment in a data flow mode by adopting a preset data transmission rule, so that the imaging equipment hijacks the optimized parameter information to a memory data segment of the corresponding target initial optimized parameter information.
Wherein the preset data transfer rule enables the imaging device to access the optimized parameter information.
In the embodiment of the invention, the optimized parameter information of each tuning module can be provided to the corresponding imaging equipment in a data flow mode by adopting a preset data transmission rule. Specifically, the set model containing all the optimized parameter information may be provided to the imaging device in a prescribed data flow manner. The predetermined data stream mode may be an offline file mode.
In an alternative embodiment, for step 102, the following steps may be performed:
and a substep S11, providing the optimization parameter information carrying the corresponding data storage information, the corresponding tuning module identification information and the corresponding tuning module function description information to the imaging device in a data stream manner.
As shown in table 1 below, is a data transfer rule according to an embodiment of the present invention.
TABLE 1 tuning module data delivery rule example
| Module number | Corresponding module | Description of functions | Number of quantization bits of module data | Length of |
| i | i | Gamma | 16bit | 256 |
As can be seen from table 1, the transmitted optimization parameter information may carry corresponding tuning module identification information, corresponding tuning module function description information, and data storage information of the tuning module itself.
The data transmission rule is formulated for transmitting the optimized parameter information to the imaging device in a unified format, so that the optimized parameter information can be accessible to a processing chip of the imaging device without obstacles, and imaging can be performed by adopting the optimized parameter information, thereby obtaining a better imaging effect.
And after the imaging equipment acquires the optimized parameter information, directly hijacking the optimized parameter information into a memory data segment of the corresponding target initial optimized parameter information.
In summary, in the embodiment of the present invention, the server may provide the optimized parameter information to the imaging device in a data stream manner by using a preset data transmission rule, and the imaging device may hijack the optimized parameter information directly into the memory data segment of the corresponding target initial optimized parameter information. By adopting the method, the correlation between the compiler and the Tuning XML data is bypassed in a memory hijack mode, and the problems of cost and efficiency caused by different compilers adopted by different processing chips are solved.
Referring to fig. 2, a flowchart illustrating steps of another method for processing an image quality optimization parameter according to an embodiment of the present invention is shown, and the method is applied to an imaging device, where the imaging device stores initial optimization parameter information, and the method specifically includes the following steps:
In the embodiment of the invention, the imaging device acquires the optimization parameter information provided according to the preset data transmission rule, and the initial optimization parameter information is stored in the imaging device. A correspondence between the optimization parameter information and the initial optimization parameter information may be determined.
In an optional embodiment, the imaging device has a first functional interface, and before determining target initial optimization parameter information corresponding to the optimization parameter information, the method further includes:
searching a data stream for transmitting the initial optimization parameter information through the first functional interface in a hardware abstraction layer and an application framework layer of the imaging device; judging whether the data storage capacity of all the optimization parameter information is far greater than that of all the initial optimization parameter information; and if so, executing the step of determining the target initial optimization parameter information corresponding to the optimization parameter information.
In the embodiment of the present invention, with the current image forming apparatus,in a layer of the CAM HAL and OEM Camera (belonging to the application framework layer), a data stream for transmitting the Tuning parameter may be found through the first functional interface, a data storage size of the Tuning parameter may be determined, which is denoted as L, and after hijacking to the memory, a start address d of the Tuning parameter in a corresponding memory data segment may be determinedsEnd address deAnd L ═ de-ds. Assuming that the data storage size of the aggregate model containing all the optimization parameter information is LmWhen L is presentm>>During the L, it can be considered that the optimization parameter information in the set model can cover the initial optimization parameter information of the current imaging device, and it is only required to continue to use the set model; when the requirements are not met, the optimization parameter information of the set model is considered to be insufficient, and the imaging device writes the information with insufficient optimization parameter information into a log and exits. The developer may reconstruct the set model M 'in the server side, and update the current set model M ═ muu M', and update the corresponding data transfer rule at the same time.
In an optional embodiment, the optimization parameter information carries corresponding tuning module function description information, and for step 201, the following steps may be performed:
and a substep S21, performing keyword matching on the function description information of the tuning module and the function description information in the initial optimization parameter information to obtain a corresponding matching degree.
And a substep S22, determining the initial optimization parameter information corresponding to the matching degree as the target initial optimization parameter information of the optimization parameter information if the matching degree is greater than a preset matching threshold value.
In the embodiment of the invention, the target initial optimization parameter information corresponding to the optimization parameter information can be sequentially determined according to the sequence of the identification information of the tuning module. For example, the function description of the optimized parameter information of the tth tuning module is taken to be matched with the function description of the current initial optimized parameter for keywords, if the initial optimized parameter information with higher matching degree (for example, more than 90%) does not exist, the imaging device is considered to have no function module corresponding to the optimized parameter information, and keyword matching aiming at the optimized parameter information of the t +1 th tuning module is performed; otherwise, the target initial optimization parameter information matched with the optimization parameter information is considered to exist.
In the embodiment of the present invention, the memory data segments corresponding to the initial optimization parameter information in the imaging device are sequentially arranged, and the memory data segments may be defined as a column vector v. Hijacking the optimized parameter information to the memory data segment of the corresponding target initial optimized parameter information, wherein the arrangement position or the dimension difference may exist.
With respect to step 202, the following steps may be performed:
and a substep S31 of determining to hijack the optimized parameter information to the start position in the memory data segment.
The initial position of hijacking the optimization parameter information into the memory data segment can be determined first.
For sub-step S31, the following steps may be performed:
determining a cross-correlation function between the optimization parameter information and the target initial optimization parameter information, and determining a maximum value position of the cross-correlation function; and hijacking the optimization parameter information to the initial position in the memory data segment by using the maximum position.
And the optimization parameter information and the target initial optimization parameter information are both column vector parameter information.
In one example, assume that the optimization parameter information is m'tAccording to the data precision required by the transfer example and v at the same precision, calculating a cross-correlation function between the two, and determining the maximum value position of the cross-correlation function as ktAnd hijacking the optimized parameter information to the initial position in the memory data segment by using the position as the initial position.
A substep S32, determining a data conversion relationship between the optimization parameter information and the target initial optimization parameter information;
and determining a data conversion relation between the corresponding optimization parameter information and the target initial optimization parameter information.
For sub-step S32, the following steps may be performed:
taking the initial position as an initial point, taking the length of the data segment of the optimized parameter information as a step length, and extracting a first data segment from the memory data segment; taking the data segment corresponding to the optimization parameter information as a second data segment; and fitting the transformation equations of the first data segment and the second data segment by a least square method to obtain the corresponding data conversion relation.
In one example, from memory data segment v, fetch slave ktTo kt+dmData segment (d) ofmRepresents m'tLength of) vtFitting v by least squarestAnd m'tTransformation equation v oft＝αtm′t+βtMay be represented byt,βtAnd the optimization parameter information is used as a conversion reference of the optimization parameter information corresponding to the tuning module in the memory.
And a substep S33, after the optimized parameter information performs data conversion according to the data conversion relationship, hijacking the optimized parameter information after data conversion into the memory data segment from the initial position.
In the embodiment of the invention, when all the optimized parameter information is searched for the corresponding storage position in the memory data segment and the corresponding data conversion relation is determined, the hijacking action aiming at the optimized parameter information can be completed. In addition, the corresponding storage position of the optimized parameter information and the data conversion relation can be stored.
In summary, in the embodiment of the present invention, the server may provide the optimized parameter information to the imaging device in a data stream manner by using a preset data transmission rule, and the imaging device may hijack the optimized parameter information directly into the memory data segment of the corresponding target initial optimized parameter information. By adopting the method, the correlation between the compiler and the Tuning XML data is bypassed in a memory hijack mode, and the problems of cost and efficiency caused by different compilers adopted by different processing chips are solved. By adopting the mode of the set model, downward compatibility can be supported without exhaustion.
Referring to fig. 3, a flowchart illustrating steps of a processing system for optimizing parameters of image quality according to an embodiment of the present invention is shown, in this embodiment, the processing system includes a server and an imaging device, and the imaging device stores initial optimization parameter information;
the server is used for determining the optimization parameter information output by each tuning module after the image quality tuning is finished; providing the optimized parameter information to corresponding imaging equipment in a data flow mode by adopting a preset data transmission rule;
the imaging device is used for acquiring optimization parameter information provided according to a preset data transmission rule and determining target initial optimization parameter information corresponding to the optimization parameter information; hijacking the optimized parameter information to a memory data segment corresponding to the target initial optimized parameter information.
The workflow of the processing system may specifically include the following steps:
303, the imaging device acquires optimization parameter information provided according to a preset data transmission rule, and determines target initial optimization parameter information corresponding to the optimization parameter information;
and step 304, hijacking the optimized parameter information to a memory data segment corresponding to the target initial optimized parameter information by the imaging device.
It should be noted that, for the detailed operation process of the image quality optimization parameter processing system according to the embodiment of the present invention, reference may be made to the description of the image quality optimization parameter processing process at the server side or the imaging device side, and for avoiding repetition, only a brief description is made here.
In order to enable those skilled in the art to better understand steps 301 to 304 of the embodiment of the present invention, the following description is provided by way of an example:
1. the server determines the optimization parameter information respectively output by each tuning module, and sets a model M containing all the optimization parameter information according to the data transmission rulepProviding the image data to a corresponding imaging device (particularly a processing chip in the imaging device);
2. respectively determining target initial optimization parameter information corresponding to each optimization parameter information, and determining the data conversion relation between the two in the memory data segment to obtain the vector corresponding to the memory data segment
3. Respectively determining the storage position (the initial position is k) of each optimized parameter information in the memory data segment of the corresponding target initial optimized parameter informationt)；
4. For the memory data segment of the hijacked initial optimization parameter information, ktB, v istAnd copying the data into the corresponding memory segment to complete the compiling difference optimization process.
In summary, in the embodiment of the present invention, the server may provide the optimized parameter information to the imaging device in a data stream manner by using a preset data transmission rule, and the imaging device may hijack the optimized parameter information directly into the memory data segment of the corresponding target initial optimized parameter information. By adopting the method, the correlation between the compiler and the Tuning XML data is bypassed in a memory hijack mode, and the problems of cost and efficiency caused by different compilers adopted by different processing chips are solved. By adopting the mode of the set model, downward compatibility can be supported without exhaustion.
It should be noted that, for simplicity of description, the method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present invention is not limited by the illustrated order of acts, as some steps may occur in other orders or concurrently in accordance with the embodiments of the present invention. Further, those skilled in the art will appreciate that the embodiments described in the specification are presently preferred and that no particular act is required to implement the invention.
Referring to fig. 4, a block diagram of a structure of a processing apparatus for optimizing an image quality according to an embodiment of the present invention is shown, and the processing apparatus is applied to a server, and may specifically include the following modules:
a determining module 401, configured to determine, after the image quality tuning is completed, optimization parameter information output by each tuning module;
a providing module 402, configured to provide the optimized parameter information to a corresponding imaging device in a data stream manner by using a preset data transmission rule, so that the imaging device hijacks the optimized parameter information to a memory data segment of corresponding target initial optimized parameter information; the preset data transfer rules enable the imaging device to access the optimization parameter information.
In an embodiment of the present invention, the providing module includes:
and the providing sub-module is used for providing the optimization parameter information carrying the corresponding data storage information, the corresponding tuning module identification information and the corresponding tuning module function description information to the imaging equipment in a data flow mode.
In summary, in the embodiment of the present invention, the server may provide the optimized parameter information to the imaging device in a data stream manner by using a preset data transmission rule, and the imaging device may hijack the optimized parameter information directly into the memory data segment of the corresponding target initial optimized parameter information. By adopting the method, the correlation between the compiler and the Tuning XML data is bypassed in a memory hijack mode, and the problems of cost and efficiency caused by different compilers adopted by different processing chips are solved.
Referring to fig. 5, a block diagram of another structure of a processing apparatus for optimizing image quality according to an embodiment of the present invention is shown, and is applied to an imaging device, where the imaging device stores initial optimization parameter information, and the processing apparatus specifically includes the following modules:
an obtaining module 501, configured to obtain optimization parameter information provided according to a preset data transmission rule, and determine target initial optimization parameter information corresponding to the optimization parameter information;
a hijacking module 502, configured to hijack the optimized parameter information to a memory data segment corresponding to the target initial optimized parameter information.
In an embodiment of the present invention, the imaging device has a first functional interface, and the apparatus further includes:
a searching module, configured to search, in a hardware abstraction layer and an application framework layer of the imaging device, a data stream that transmits the initial optimization parameter information through the first functional interface;
the judging module is used for judging whether the data storage capacity of all the optimized parameter information is far greater than that of all the initial optimized parameter information;
and the execution module is used for executing the step of determining the target initial optimization parameter information corresponding to the optimization parameter information if the target initial optimization parameter information is the same as the optimization parameter information.
In this embodiment of the present invention, the optimization parameter information carries corresponding tuning module function description information, and the obtaining module includes:
the matching sub-module is used for performing keyword matching on the function description information of the tuning module and the function description information in the initial optimization parameter information to obtain a corresponding matching degree;
a first determining submodule, configured to determine, if the matching degree is greater than a preset matching threshold, the initial optimization parameter information corresponding to the matching degree as the target initial optimization parameter information of the optimization parameter information.
In an embodiment of the present invention, the hijacking module includes:
the second determining submodule is used for determining that the optimized parameter information is hijacked to the initial position in the memory data segment;
a third determining submodule, configured to determine a data conversion relationship between the optimization parameter information and the target initial optimization parameter information;
and the hijacking sub-module is used for hijacking the optimized parameter information after data conversion into the memory data segment from the initial position after the optimized parameter information performs data conversion according to the data conversion relation.
In an embodiment of the present invention, the second determining sub-module includes:
a first determining unit, configured to determine a cross-correlation function between the optimization parameter information and the target initial optimization parameter information, and determine a maximum position of the cross-correlation function; the optimization parameter information and the target initial optimization parameter information are both column vector parameter information;
a second determining unit, configured to hijack the optimized parameter information to the start position in the memory data segment using the maximum position as the start position.
In an embodiment of the present invention, the third determining sub-module includes:
an extracting unit, configured to extract a first data segment from the memory data segment by using the start position as a start point and using a data segment length of the optimized parameter information as a step length;
a third determining unit, configured to use a data segment corresponding to the optimization parameter information as a second data segment;
and the fitting unit is used for fitting the transformation equations of the first data segment and the second data segment by a least square method to obtain the corresponding data conversion relation.
In summary, in the embodiment of the present invention, the server may provide the optimized parameter information to the imaging device in a data stream manner by using a preset data transmission rule, and the imaging device may hijack the optimized parameter information directly into the memory data segment of the corresponding target initial optimized parameter information. By adopting the method, the correlation between the compiler and the Tuning XML data is bypassed in a memory hijack mode, and the problems of cost and efficiency caused by different compilers adopted by different processing chips are solved. By adopting the mode of the set model, downward compatibility can be supported without exhaustion.
For the device embodiment, since it is basically similar to the method embodiment, the description is simple, and for the relevant points, refer to the partial description of the method embodiment.
An embodiment of the present invention further provides an electronic device, including: the image quality optimization parameter processing method comprises a processor, a memory and a computer program which is stored in the memory and can run on the processor, wherein when the computer program is executed by the processor, each process of the image quality optimization parameter processing method embodiment is realized, the same technical effect can be achieved, and the details are not repeated here to avoid repetition.
The embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program implements each process of the above-mentioned embodiment of the processing method for image quality optimization parameters, and can achieve the same technical effect, and is not described herein again to avoid repetition.
The embodiments in the present specification are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, apparatus, or computer program product. Accordingly, embodiments of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
Embodiments of the present invention are described with reference to flowchart illustrations and/or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing terminal to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing terminal to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing terminal to cause a series of operational steps to be performed on the computer or other programmable terminal to produce a computer implemented process such that the instructions which execute on the computer or other programmable terminal provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications of these embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the embodiments of the invention.
Finally, it should also be noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or terminal that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or terminal. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or terminal that comprises the element.
The present invention provides a method for processing image quality optimization parameters, a device for processing image quality optimization parameters, a system for processing image quality optimization parameters, an electronic device, and a computer-readable storage medium, which have been described in detail above, and the present invention is described in detail herein by applying specific examples to explain the principles and embodiments of the present invention, and the above descriptions of the examples are only used to help understand the method and the core ideas of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (13)
1. A processing method for image quality optimization parameters is applied to a server, and the method comprises the following steps:
after finishing the image quality tuning, determining optimization parameter information output by each tuning module;
providing the optimized parameter information to corresponding imaging equipment in a data flow mode by adopting a preset data transmission rule so that the imaging equipment hijacks the optimized parameter information to a memory data segment of corresponding target initial optimized parameter information; the preset data transfer rules enable the imaging device to access the optimization parameter information.
2. The method according to claim 1, wherein the providing the optimized parameter information to the corresponding imaging device by means of data stream using a preset data transfer rule includes:
and providing the optimization parameter information carrying the corresponding data storage information, the corresponding tuning module identification information and the corresponding tuning module function description information to the imaging equipment in a data flow mode.
3. The processing method of the image quality optimization parameter is applied to an imaging device, the imaging device stores initial optimization parameter information, and the method comprises the following steps:
acquiring optimization parameter information provided according to a preset data transmission rule, and determining target initial optimization parameter information corresponding to the optimization parameter information;
hijacking the optimized parameter information to a memory data segment corresponding to the target initial optimized parameter information.
4. The method of claim 3, wherein the imaging device has a first functional interface, and before determining the target initial optimization parameter information corresponding to the optimization parameter information, the method further comprises:
searching a data stream for transmitting the initial optimization parameter information through the first functional interface in a hardware abstraction layer and an application framework layer of the imaging device;
judging whether the data storage capacity of all the optimization parameter information is far greater than that of all the initial optimization parameter information;
and if so, executing the step of determining the target initial optimization parameter information corresponding to the optimization parameter information.
5. The method according to claim 3, wherein the optimization parameter information carries corresponding tuning module function description information, and the determining of the target initial optimization parameter information corresponding to the optimization parameter information includes:
performing keyword matching on the function description information of the tuning and optimizing module and the function description information in the initial optimization parameter information to obtain corresponding matching degree;
and if the matching degree is greater than a preset matching threshold, determining the initial optimization parameter information corresponding to the matching degree as the target initial optimization parameter information of the optimization parameter information.
6. The method according to claim 3, wherein hijacking the optimized parameter information into the memory data segment corresponding to the target initial optimized parameter information comprises:
determining the initial position of hijacking the optimized parameter information to the memory data segment;
determining a data conversion relation between the optimization parameter information and the target initial optimization parameter information;
and after the optimized parameter information is subjected to data conversion according to the data conversion relation, hijacking the optimized parameter information subjected to data conversion into the memory data segment from the initial position.
7. The method of claim 6, wherein the determining to hijack the optimization parameter information to a starting location in the in-memory data segment comprises:
determining a cross-correlation function between the optimization parameter information and the target initial optimization parameter information, and determining a maximum value position of the cross-correlation function; the optimization parameter information and the target initial optimization parameter information are both column vector parameter information;
and hijacking the optimization parameter information to the initial position in the memory data segment by using the maximum position.
8. The method of claim 6, wherein the determining the data transformation relationship between the optimization parameter information and the target initial optimization parameter information comprises:
taking the initial position as an initial point, taking the length of the data segment of the optimized parameter information as a step length, and extracting a first data segment from the memory data segment;
taking the data segment corresponding to the optimization parameter information as a second data segment;
and fitting the transformation equations of the first data segment and the second data segment by a least square method to obtain the corresponding data conversion relation.
9. An apparatus for processing image quality optimization parameters, applied to a server, the apparatus comprising:
the determining module is used for determining the optimization parameter information output by each adjusting and optimizing module after the image quality adjustment and optimization are finished;
the providing module is used for providing the optimized parameter information to the corresponding imaging equipment in a data flow mode by adopting a preset data transmission rule so that the imaging equipment hijacks the optimized parameter information to a memory data segment of the corresponding target initial optimized parameter information; the preset data transfer rules enable the imaging device to access the optimization parameter information.
10. An apparatus for processing image quality optimization parameters, applied to an imaging device, the imaging device storing initial optimization parameter information, the apparatus comprising:
the system comprises an acquisition module, a data transmission module and a data transmission module, wherein the acquisition module is used for acquiring optimization parameter information provided according to a preset data transmission rule and determining target initial optimization parameter information corresponding to the optimization parameter information;
and the hijacking module is used for hijacking the optimized parameter information into the memory data segment corresponding to the target initial optimized parameter information.
11. The processing system of the image quality optimization parameter is characterized by comprising a server and an imaging device, wherein the imaging device stores initial optimization parameter information;
the server is used for determining the optimization parameter information output by each tuning module after the image quality tuning is finished; providing the optimized parameter information to corresponding imaging equipment in a data flow mode by adopting a preset data transmission rule;
the imaging device is used for acquiring optimization parameter information provided according to a preset data transmission rule and determining target initial optimization parameter information corresponding to the optimization parameter information; hijacking the optimized parameter information to a memory data segment corresponding to the target initial optimized parameter information.
12. An electronic device, comprising: processor, memory and computer program stored on the memory and capable of running on the processor, the computer program when executed by the processor implementing the steps of a method of processing image quality optimization parameters as claimed in any one of claims 1-2 or 3-8.
13. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of a method of processing image quality optimization parameters according to any one of claims 1-2 or 3-8.
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