CN114125312B - Method, device, equipment and storage medium for converging isp fast ae - Google Patents
Method, device, equipment and storage medium for converging isp fast ae Download PDFInfo
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Abstract
The application relates to a quick ae convergence method, a device, equipment and a storage medium of isp, wherein the method comprises the steps of acquiring a photosensitive value and a current ae parameter value when a network camera is electrified to run; judging whether the photosensitive numerical value at the moment is in a mapping interval of a preset mapping table or not; when the value is positioned in the mapping interval of the mapping table, judging whether the current ae parameter value is in a convergence stage or a stabilization stage; if the current ae parameter value is in the convergence stage, storing the ae parameter value mapped with the photosensitive value at the moment in the mapping table; and taking the stored ae parameter value as a preset current convergence value of the automatic ae algorithm, and starting from the current convergence value, converging the automatic ae algorithm until the network camera acquires the first frame of stable image. The method solves the problem that the isp can hardly acquire the matched ae parameters rapidly in a low-light environment. The method has the effect of quickly acquiring the matching ae parameters in the low-light environment.
Description
Technical Field
The present application relates to the field of image capturing devices, and in particular, to an isp fast ae convergence method, apparatus, device, and storage medium.
Background
Currently, a battery ipc (ip camera) has an increasing demand for quick start of a capture image. The main working principle of the cmos sensor module applied to the scene is to enter a small window mode, namely a high frame rate and small resolution mode, strive for calculating stable exposure gain in a short time, and then linearly convert into ae parameters of normal resolution so as to achieve the effects of rapid drawing and ae convergence stabilization.
However, in the low-illumination environment, the matching ae parameters are difficult to obtain quickly, and the expression effect of the ipc is general.
With respect to the related art, the inventor considers that the existing isp has the defect that it is difficult to quickly obtain the matched ae parameter under the low-light environment.
Disclosure of Invention
In order to quickly acquire matched ae parameters in a low-light environment, the application provides an isp quick ae convergence method, an isp quick ae convergence device, an isp quick ae convergence equipment and a storage medium.
In a first aspect, the present application provides an isp fast ae convergence method, which has the characteristic of fast obtaining a matched ae parameter in a low-light environment.
The application is realized by the following technical scheme:
an isp rapid ae convergence method comprises the following steps:
when the network camera is powered on and operates, the value of the photosensitive digital-to-analog conversion module and the current ae parameter value are obtained;
judging whether the numerical value of the photosensitive digital-to-analog conversion module at the moment is in a mapping interval of a preset mapping table or not;
when the numerical value of the photosensitive digital-to-analog conversion module at the moment is positioned in the mapping interval of the mapping table, judging whether the current ae parameter value is in a convergence stage or a stable stage;
if the current ae parameter value is in the convergence stage, storing the ae parameter value mapped with the numerical value of the photosensitive digital-to-analog conversion module in the mapping table;
and taking the stored ae parameter value as a preset current convergence value of the automatic ae algorithm, and starting from the current convergence value, converging the automatic ae algorithm until the network camera acquires a first frame of stable image.
By adopting the technical scheme, the isp (image signal processing, image processing unit) acquires the value of the photosensitive digital-to-analog conversion module and the current ae parameter value when the network camera is powered on to run, so as to serve as the data base of the processing flow; judging whether the numerical value of the photosensitive digital-to-analog conversion module at the moment is in a mapping interval of a preset mapping table or not so as to acquire required data from the mapping interval of the mapping table; because the analog gain and the exposure time are maximum when the ambient brightness is darkest, i.e. the current ae parameter value is in a stable stage, the current ae parameter can be not regulated; when the ambient brightness becomes dark gradually, namely the current ae parameter value is in a convergence stage, the current ae parameter needs to be adjusted; judging whether the current ae parameter value is in a convergence stage or a stabilization stage or not so as to judge the brightness condition of the current environment, and adjusting the ae parameter based on the brightness condition of the actual environment; when the photosensitive value is positioned in the mapping interval of the mapping table and the current ae parameter value is in the convergence stage, the ae parameter value mapped with the photosensitive value at the moment in the mapping table is obtained, so that the ae parameter value close to the target brightness is obtained from the mapping table quickly and directly, the stored ae parameter value is close to the target brightness as much as possible, and quick adjustment is facilitated; taking the stored ae parameter value as a preset current convergence value of the automatic ae algorithm, starting from the current convergence value, converging the automatic ae algorithm until the network camera acquires a first frame of stable image, so that the current convergence value is regulated to be close to target brightness, the aim that the network camera can basically acquire stable images in one to two configured frames is fulfilled, and meanwhile, the performance effect of isp in a low-illumination environment is improved; therefore, the fast ae convergence method of the isp can enable the isp to quickly acquire the matched ae parameters and improve the performance effect of the isp under the low-illumination environment.
The present application may be further configured in a preferred example to: after the step of judging whether the current ae parameter value is in the convergence stage or the stabilization stage, the method further comprises the following steps:
and if the current ae parameter value is in the stable phase, storing the current ae parameter value.
By adopting the technical scheme, if the current ae parameter value is in a stable stage, namely the current ambient brightness is darkest, and the analog gain and the exposure time are maximum, the current ae parameter value is stored, and the current ae parameter is not required to be regulated and processed, so that the ae parameter value close to the target brightness can be obtained more quickly, and the regulation can be realized more quickly.
The present application may be further configured in a preferred example to: the method also comprises the following steps:
and when the network camera is powered off and dormant, automatically learning based on the acquired numerical value of the photosensitive digital-to-analog conversion module and the current ae parameter value, and updating the mapping table.
By adopting the technical scheme, when the network camera is powered off and dormant, the mapping table is automatically learned and updated based on the obtained numerical value of the photosensitive digital-to-analog conversion module and the current ae parameter value, so that the preset mapping table has more comprehensive content, more photosensitive numerical values can be positioned in the mapping interval of the mapping table, the influence of various environmental changes can be adapted, the applicability is stronger, and the popularization is facilitated; meanwhile, the content data in the preset mapping table is more accurate, and the acquired ae parameter value can be closer to the ae parameter value of the target brightness, so that the quick adjustment is facilitated; and study and update when the network camera is powered off and dormant, and working performance of the network camera in power-on operation is not affected.
The present application may be further configured in a preferred example to: the step of automatically learning based on the acquired numerical value of the photosensitive digital-to-analog conversion module and the current ae parameter value comprises the following steps:
judging whether an ae parameter value of an automatic ae algorithm is in a stable state or not;
if the ae parameter value is stable, acquiring the current ae parameter value;
judging whether the numerical value of the photosensitive digital-to-analog conversion module in the current environment is in a mapping interval of a preset mapping table or not;
when the numerical value of the photosensitive digital-to-analog conversion module at the moment is positioned in the mapping interval of the mapping table, the acquired ae parameter value is stored in the corresponding mapping interval of the mapping table.
By adopting the technical scheme, judging whether the ae parameter value of the automatic ae algorithm is in a stable state or not so as to judge whether the ae parameter value at the moment can improve the performance effect of the isp in a low-illumination environment or not; if the ae parameter value is stable, acquiring the current ae parameter value to be used as a storage value of the mapping table; judging whether the photosensitive value of the current environment is in a mapping interval of a preset mapping table or not so as to judge whether the mapping interval needs to be newly established or not; when the photosensitive value is located in the mapping interval of the mapping table, the acquired ae parameter value is stored in the corresponding mapping interval of the mapping table, so that the ae parameter value of the mapping table can be closer to the ae parameter value of the target brightness, the ae parameter value of the mapping table is more accurate and more consistent with the actual photosensitive value condition, and quick adjustment is facilitated.
The present application may be further configured in a preferred example to: after the step of judging whether the value of the photosensitive digital-to-analog conversion module in the current environment is in the mapping interval of the preset mapping table, the method further comprises the following steps:
when the value of the photosensitive digital-to-analog conversion module is located outside the mapping interval of the mapping table, a mapping interval is newly created, and the obtained ae parameter value and the value of the photosensitive digital-to-analog conversion module in the current environment are stored into the newly created mapping interval.
By adopting the technical scheme, when the photosensitive value at the moment is positioned outside the mapping interval of the mapping table, a mapping interval is newly created, and the acquired ae parameter value and the photosensitive value of the current environment are stored into the newly created mapping interval, so that the preset mapping table has more comprehensive content, more photosensitive values can be positioned in the mapping interval of the mapping table, the applicability is stronger, and the popularization is facilitated.
The present application may be further configured in a preferred example to: the ae parameter values include analog gain and exposure time.
By adopting the technical scheme, the general ae parameter value is controlled by the analog gain, the exposure time, the internal digital gain of the isp and the total digital gain, and the ae parameter of the network camera is regulated and controlled only by the analog gain and the exposure time, so that the regulation speed of the ae parameter is further accelerated, and the matched ae parameter can be obtained more quickly in a low-illumination environment.
The present application may be further configured in a preferred example to: and the automatic ae algorithm calculates the difference value between the current ambient brightness and the target brightness according to the brightness component of the pixel data, so that the current convergence value is regulated to be close to the target brightness, and the ae parameter value is dynamically updated.
By adopting the technical scheme, the automatic ae algorithm calculates the difference value between the current ambient brightness and the target brightness according to the brightness component of the pixel data, so that the current convergence value is regulated to be close to the target brightness, the ae parameter value is dynamically updated, and the performance effect of the isp under the low-illumination environment is improved.
The present application may be further configured in a preferred example to: the step of adjusting the current convergence value to approach the target brightness includes:
when the ambient brightness becomes dark gradually, the analog gain is made to become smaller gradually in multiple;
when the analog gain is reduced to the minimum value, if the ambient brightness continues to darken, adjusting the exposure time to continuously reduce the exposure time by a step size;
when the exposure time is less than the minimum value, the exposure time is decremented by the bit size.
By adopting the technical scheme, the simulation gain and the exposure time are adjusted according to the darkening degree of the environment, so that the current convergence value is adjusted to be close to the target brightness, the ae parameter value is dynamically updated, and the performance effect of the isp under the low-illumination environment is improved.
In a second aspect, the application provides an isp fast ae convergence device, which has the characteristic of fast obtaining matched ae parameters in a low-light environment.
The application is realized by the following technical scheme:
an isp fast ae convergence device comprising:
the data acquisition module is used for acquiring the value of the photosensitive digital-to-analog conversion module and the current ae parameter value when the network camera is powered on to run;
the first judging module is used for judging whether the numerical value of the photosensitive digital-to-analog conversion module at the moment is in a mapping interval of a preset mapping table;
the second judging module is used for judging whether the current ae parameter value is in a convergence stage or a stabilization stage when the numerical value of the photosensitive digital-to-analog conversion module at the moment is positioned in the mapping interval of the mapping table;
the parameter module is used for storing the ae parameter value mapped with the numerical value of the photosensitive digital-to-analog conversion module in the mapping table when the current ae parameter value is in a convergence stage;
and the convergence module is used for taking the stored ae parameter value as a preset current convergence value of the automatic ae algorithm, starting from the current convergence value, and converging the automatic ae algorithm until the network camera acquires a first frame of stable image.
In a third aspect, the present application provides a computer device, which has the feature of quickly obtaining a matched ae parameter in a low-light environment.
The application is realized by the following technical scheme:
a computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the above-described isp fast ae convergence method when the computer program is executed by the processor.
In a fourth aspect, the present application provides a computer readable storage medium having the feature of fast obtaining a matched ae parameter in a low-light environment.
The application is realized by the following technical scheme:
a computer readable storage medium storing a computer program which, when executed by a processor, performs the steps of the above-described isp fast ae convergence method.
In summary, the present application includes at least one of the following beneficial technical effects:
1. the fast ae convergence method of the isp can enable the isp to acquire matched ae parameters fast in a low-illumination environment, and improve the expression effect of the isp;
2. if the current ambient brightness is darkest, the current ae parameter does not need to be regulated and processed, so that the ae parameter value close to the target brightness can be obtained more quickly, and the regulation can be realized more quickly;
3. when the network camera is powered off and dormant, the preset mapping table is more comprehensive in content and higher in applicability based on the acquired numerical value of the photosensitive digital-to-analog conversion module and the current ae parameter value, and the popularization is facilitated; meanwhile, the obtained ae parameter value can be closer to the ae parameter value of the target brightness, and is more beneficial to quick adjustment; the working performance of the network camera during power-on operation is not affected;
4. only two parameter values of the analog gain and the exposure time are used for regulating and controlling the ae parameters, so that the regulating speed of the ae parameters is further accelerated, and the matched ae parameters can be obtained more quickly in a low-illumination environment;
5. the automatic ae algorithm adjusts the analog gain and exposure time according to the darkening degree of the environment, dynamically updates ae parameter values, and adjusts the current convergence value to be close to the target brightness so as to improve the performance effect of the isp in the low-illumination environment.
Drawings
Fig. 1 is a flow chart of an isp fast ae convergence method according to an embodiment of the application.
Fig. 2 is a flow chart of ae parameter learning during sleep.
Fig. 3 is a graph showing the trend of the light-sensitive value with the ambient brightness value.
Fig. 4 is a plot of exposure time and analog gain as a function of light sensitivity values.
Fig. 5 is a substantially stable image of a first frame acquired in accordance with the present application.
Fig. 6 is a block diagram of an isp fast ae convergence device according to an embodiment of the application.
Detailed Description
The present embodiment is only for explanation of the present application and is not to be construed as limiting the present application, and modifications to the present embodiment, which may not creatively contribute to the present application as required by those skilled in the art after reading the present specification, are all protected by patent laws within the scope of claims of the present application.
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
In addition, the term "and/or" herein is merely an association relationship describing an association object, and means that three relationships may exist, for example, a and/or B may mean: a exists alone, A and B exist together, and B exists alone. In this context, unless otherwise specified, the term "/" generally indicates that the associated object is an "or" relationship.
As the demand of the battery ipc for the quick start of the capture is higher and higher, a special quick start cmos sensor scheme is used, firstly, when the main control and the cmos sensor are powered on for the first time, a small window ae is opened to quickly converge, and the initialization configuration of the cmos sensor of the small window is written; then, polling a small window ae stable marker bit, and judging whether the internal adc value of the cmos sensor is in a stable state or not; when the internal adc value of the cmos sensor is in a stable state, linearly converting the exposure time and gain value into 1080P window exposure time and gain multiple value, reading the linearly converted exposure time and gain value, and writing into a register; finally, writing the read exposure time and gain value, opening a large window to enable the cmos sensor to be mapped, and powering off the main control; so as to achieve the effects of rapid drawing and ae convergence and stability.
However, the disadvantage of the above scheme is that when the ae stable flag bit is polled, the flag bit is blocked for a long time when the light is dark, about tens to hundreds of milliseconds, and under the low illumination environment, after the quick start parameter is correspondingly effective, the effect is not ideal and is darker, the performance is general, and the matched ae parameter is difficult to obtain; meanwhile, the model of the quick-start cmos sensor device is special, the cost is much higher than that of a common cmos sensor, and the type selection range is limited.
Therefore, the application provides a new ipc-based isp ae rapid convergence starting scheme, according to the adc value read by a peripheral photosensitive adc (digital-to-analog conversion module) device, generating a mapping table of the photosensitive adc value of the current environment, the current environment a-gain (analog gain) and exp_time (exposure time) according to a corresponding learning algorithm when in dormancy each time; meanwhile, stable ae parameters are obtained according to the mapping table when each starting is performed, and the stable ae parameters are configured into a register of a cmos sensor and an automatic ae algorithm preset by an isp algorithm library, so that the effect of enabling the isp to quickly obtain matched ae parameters under a low-illumination environment and improving the performance of the isp is achieved.
Embodiments of the application are described in further detail below with reference to the drawings.
Referring to fig. 1, an embodiment of the present application provides an isp fast ae convergence method, and main steps of the method are described as follows.
S11, when the network camera is powered on and operates, acquiring the value of the photosensitive digital-to-analog conversion module and the current ae parameter value;
s12, judging whether the numerical value of the photosensitive digital-to-analog conversion module at the moment is in a mapping interval of a preset mapping table;
s13, judging whether the current ae parameter value is in a convergence stage or a stabilization stage when the numerical value of the photosensitive digital-to-analog conversion module is positioned in a mapping interval of the mapping table;
s141, if the current ae parameter value is in a convergence stage, storing the ae parameter value mapped with the numerical value of the photosensitive digital-to-analog conversion module in the mapping table;
s15, taking the stored ae parameter value as a preset current convergence value of the automatic ae algorithm, and starting from the current convergence value, converging the automatic ae algorithm until the network camera acquires the first frame of stable image.
S13, after the step of judging whether the current ae parameter value is in a convergence stage or a stabilization stage, the method further comprises the following steps:
and S142, if the current ae parameter value is in a stable stage, storing the current ae parameter value. At this time, the current ae parameter value is in a non-convergence phase.
In the present application, ae parameter values are analog gain and exposure time. The values of the ae parameters are typically controlled by a-gain, exp_time, isp_d_gain, and d-gain. According to the application, the ae parameters of the network camera are regulated and controlled only by the analog gain and the exposure time, so that the regulation speed of the ae parameters is further accelerated, and the matched ae parameters can be obtained more quickly in a low-illumination environment.
In the actual setting process, the application ensures that exp_time and again play a main control role to be configured preferentially, the smoothing role in the convergence process of isp_d_gain can be firstly unconfigured, and dgain can be firstly unconfigured in the quick start, and specifically, the minimum gain multiple 1x is set by default.
Specifically, in the isp fast ae convergence method, when a network camera is powered on, the value of a photosensitive digital-to-analog conversion module and the current ae parameter value are firstly obtained to serve as the data base of a processing flow.
And judging whether the numerical value of the photosensitive digital-to-analog conversion module is in a mapping interval of a preset mapping table or not at the moment so as to acquire required data from the mapping interval of the mapping table directly and quickly.
Examples of the preset adc-ae value mapping table are shown in table 1:
TABLE 1
The mapping relation of the mapping table is: according to the adc multiple relation between the actual adc value and the mapping interval threshold, calculating the current exp value and the a-gain value, and writing the current exp value and the a-gain value into a register to generate a mapping table of the current environment photosensitive adc value and the current environment again value and the exp value.
When the ambient brightness is darkest, the analog gain and the exposure time are maximum, namely the current ae parameter value is in a stable stage, and the current ae parameter can be not regulated; when the ambient brightness becomes dark gradually, namely the current ae parameter value is in a convergence stage, the current ae parameter needs to be adjusted; the brightness condition of the current environment is judged by judging whether the current ae parameter value is in a convergence stage or a stable stage, and ae parameter adjustment is carried out based on the actual environment brightness condition.
When the photosensitive value is located in the mapping interval of the mapping table and the current ae parameter value is in the convergence stage, the ae parameter value mapped with the photosensitive value at the moment in the mapping table is obtained, so that the ae parameter value close to the target brightness is obtained from the mapping table quickly and directly, the stored ae parameter value is close to the target brightness as much as possible, and quick adjustment is facilitated.
When the photosensitive value is located in the mapping interval of the mapping table and the current ae parameter value is in a stable stage, namely the current ambient brightness is darkest, and the analog gain and the exposure time are maximum, the current ae parameter value is stored, and the current ae parameter is not required to be regulated and processed, so that the ae parameter value close to the target brightness can be obtained more quickly, and the regulation can be realized more quickly.
And finally, taking the stored ae parameter value as a preset current convergence value of the automatic ae algorithm, starting from the current convergence value, converging the automatic ae algorithm until the network camera acquires the first frame of stable image, so that the current convergence value is regulated to be close to the target brightness, the aim that the network camera can basically acquire the stable image in one to two configured frames is fulfilled, and meanwhile, the performance effect of the isp in a low-illumination environment is improved.
The preset automatic ae algorithm is located in an isp 3a algorithm library, and the automatic ae algorithm is also called an automatic exposure gain algorithm.
Specifically, S15, a preset automatic ae algorithm calculates the difference value between the current ambient brightness and the target brightness according to the brightness component of the pixel data, so that the current convergence value is adjusted to be close to the target brightness, and the ae parameter value is dynamically updated.
Further, the step of adjusting the current convergence value to be close to the target brightness includes:
when the ambient brightness becomes dark gradually, the analog gain is made to become smaller gradually in multiple;
when the analog gain is reduced to the minimum value, if the ambient brightness continues to darken, adjusting the exposure time to continuously reduce the exposure time by a step size;
when the exposure time is less than the minimum value, the exposure time is decremented by the bit size.
Specifically, as the brightness gradually becomes darker, a_gain is first adjusted to become smaller gradually and is reduced by a multiple of 256; when the brightness is reduced to the minimum value 256, if the brightness continues to darken, the exp_time is adjusted instead; step is adjusted by step, which is determined by anti-strobe, and exp_step=maxexp frame rate/100, where maxEXP refers to the maximum exposure value; the exp_time is continuously reduced in step size when the brightness becomes dark; when exp_time is less than the minimum step, then the decreasing granule of exp_time changes to a bit.
Specifically, taking a 50HZ power supply as an example:
50HZ ac power cycle: t=1/(50×2);
time t_frame=1/FPS for sensor to expose one frame;
time t_row=t_frame/line_max (line_max=exp_max) taken for sensor to expose a Line;
to avoid flickers, it is necessary to satisfy that the energy obtained from each line is an integer multiple of the period of ac energy, otherwise, the obtained energy should be inconsistent, resulting in the generation of water ripple phenomenon. Namely:
T_row*Step＝n*T；
therefore: step= (n×t)/t_row=n× (fps×exp_max)/100; (n is a positive integer) n=1, and the calculated exposure time adjustment step corresponding to the anti-stroboscopic effect is obtained.
If the brightness is changed from dark to bright, the above change trend is reversed, and exp_time is increased first, and then a_gain is increased.
Whether the brightness changes from dark to bright or from bright to dark, only one parameter of the agan and the exp_time changes at the same time, so that when the ae parameter is mapped through the photosensitive adc, whether the exp and again mapped at present are in a stable stage, namely whether the exp and again are in a maximum or minimum value or gain multiple can be judged firstly; if the phase is in the stable phase, writing the maximum and minimum values or gain factors; and if the mapping is in the convergence stage, writing the mapped ae value.
In the application, the current convergence value is adjusted to be close to the target brightness, namely, the brightness in a preset brightness range, such as a range of targetLumina+/-StableRange, is used as the target brightness, when the current convergence value is close to the preset brightness range, the current convergence value is considered to be close to the target brightness, and AE adjustment is not performed at the moment.
Therefore, the automatic ae algorithm adjusts the analog gain and the exposure time according to the darkening degree of the environment, dynamically updates the ae parameter value, and adjusts the current convergence value to be close to the target brightness so as to improve the performance effect of the isp in the low-illumination environment.
Referring to fig. 2, S21, when the network camera is powered off and dormant, the mapping table is automatically learned and updated based on the obtained value of the photosensitive digital-to-analog conversion module and the current ae parameter value.
The step of automatically learning based on the acquired numerical value of the photosensitive digital-to-analog conversion module and the current ae parameter value comprises the following steps:
s211, judging whether an ae parameter value of an automatic ae algorithm is in a stable state or not;
s212, if the ae parameter value is stable, acquiring the current ae parameter value;
s213, judging whether the numerical value of the photosensitive digital-to-analog conversion module in the current environment is in a mapping interval of a preset mapping table;
s2141, when the value of the photosensitive digital-to-analog conversion module is located in the mapping interval of the mapping table, the obtained ae parameter value is stored in the corresponding mapping interval of the mapping table.
Further, when the value of the photosensitive digital-to-analog conversion module at this time is located outside the mapping interval of the mapping table, a mapping interval is newly created, and the obtained ae parameter value and the value of the photosensitive digital-to-analog conversion module in the current environment are stored into the newly created mapping interval.
Specifically, judging whether the ae parameter value of the automatic ae algorithm is in a stable state or not so as to judge whether the ae parameter value at the moment can improve the performance effect of the isp in a low-illumination environment or not; if the ae parameter value is stable, the current ae parameter value is obtained and used as a storage value of the mapping table.
And judging whether the photosensitive value of the current environment is in a mapping interval of a preset mapping table or not so as to judge whether the mapping interval needs to be newly created or not.
When the photosensitive value is located in the mapping interval of the mapping table, the mapping interval is not required to be created, and the acquired ae parameter value is stored in the corresponding mapping interval of the mapping table, so that the ae parameter value of the mapping table can be closer to the ae parameter value of the target brightness, the ae parameter value of the mapping table is more accurate and more consistent with the actual photosensitive value condition, and quick adjustment is facilitated.
When the photosensitive value is located outside the mapping interval of the mapping table, a mapping interval is required to be newly created, and the acquired ae parameter value and the photosensitive value of the current environment are stored into the newly created mapping interval, so that the content of the preset mapping table is more comprehensive, more photosensitive values can be located in the mapping interval of the mapping table, the applicability is stronger, and popularization is facilitated.
In the process of power off dormancy, the adc-ae value is self-adaptive according to the current environment, so that parameter adaptation of various different environments is met, the preset mapping table is more comprehensive in content, more photosensitive values can be located in the mapping interval of the mapping table, the influence of various environment changes can be adapted, the applicability is stronger, and popularization is facilitated; meanwhile, the content data in the preset mapping table is more accurate, and the acquired ae parameter value can be closer to the ae parameter value of the target brightness, so that the quick adjustment is facilitated; and study and update when the network camera is powered off and dormant, and working performance of the network camera in power-on operation is not affected.
Referring to a trend graph of the variation trend of the adc value of the photosensitive device of fig. 3 with the variation of the ambient lx illuminance value, referring to a trend graph of the ae parameter of fig. 4 with the variation of the adc parameter.
Assuming that power is on at a certain time, reading an ae parameter which is mapped to the interval corresponding to the interval in the interval (a, b), writing the value into an isp algorithm library, and observing the convergence process of a plurality of frames after the sensor.
Specifically, the first frame:
cmos_updata_exp_time: the interval exposure time parameter (immediate configuration in effect);
cmos_updata_a_gain: the interval simulates gain factors (immediate configuration takes effect);
third frame: (the sensor adjusts ae) at intervals;
finely adjusting the exposure time and the analog gain multiple of the interval;
the third frame is followed by several frames, which do not trigger ae adjustment, indicating ae has reached steady state.
And storing the image captured by the application, and observing whether the picture is stable or not.
Referring to fig. 5, a first frame of a substantially stable image acquired using the present application is shown.
In summary, the method for mapping ae parameters according to the adc light sensitivity can quickly use hardware isp to automatically ae to reach a stable state, and meanwhile, the self-adaptive learning algorithm is added: the automatic ae algorithm can adapt to the influence of various environmental changes, the environmental suitability is strong, and the first frame effect is good; and immediately after starting the isp acquisition, the ae parameter is configured, that is, after the system initialization is completed, the isp interrupt is triggered, the automatic 3a algorithm is started, and meanwhile, a plurality of processes applied can be omitted, such as the step of initializing a sensor, the frame taking time is greatly advanced, and the first frame drawing speed is high.
The application only needs to adapt the central control software of the network camera, does not need to add a new peripheral device, even a co-processing chip singlechip, and has lower cost.
The application can meet the application of all the peripheral devices of the cmos sensor on the current market, does not need to use special sensor with a quick start function, and has higher portability.
Therefore, the fast ae convergence method of the isp optimizes the speed of acquiring the first frame stable image in the video camera scheme of the internet of things, namely, the isp is made to be an isp 3a algorithm after the internet of things is powered on until the exposure gain is stable, the requirement of capturing the first frame stable image for 200ms after the internet of things is powered on rapidly is met, and the effects of enabling the isp to acquire the matched ae parameters rapidly in a low-light environment and improving the isp expression are achieved.
It should be understood that the sequence number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic, and should not limit the implementation process of the embodiment of the present application.
Referring to fig. 6, the embodiment of the present application further provides an isp fast ae convergence device, where the isp fast ae convergence device corresponds to one of the above-mentioned isp fast ae convergence methods. The isp fast ae convergence device comprises:
the data acquisition module is used for acquiring the value of the photosensitive digital-to-analog conversion module and the current ae parameter value when the network camera is powered on to run;
the first judging module is used for judging whether the numerical value of the photosensitive digital-to-analog conversion module at the moment is in a mapping interval of a preset mapping table;
the second judging module is used for judging whether the current ae parameter value is in a convergence stage or a stabilization stage when the numerical value of the photosensitive digital-to-analog conversion module at the moment is positioned in the mapping interval of the mapping table;
the parameter module is used for storing the ae parameter value mapped with the numerical value of the photosensitive digital-to-analog conversion module in the mapping table when the current ae parameter value is in a convergence stage;
and the convergence module is used for taking the stored ae parameter value as a preset current convergence value of the automatic ae algorithm, starting from the current convergence value, and converging the automatic ae algorithm until the network camera acquires the first frame of stable image.
For specific limitations of an isp fast ae convergence device, reference may be made to the above limitation of an isp fast ae convergence method, which is not described herein. The modules in the above-mentioned isp fast ae convergence device may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a server. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program, when executed by a processor, implements an isp fast ae convergence method.
In one embodiment, a computer readable storage medium is provided, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the steps of when executing the computer program:
s11, when the network camera is powered on and operates, acquiring the value of the photosensitive digital-to-analog conversion module and the current ae parameter value;
s12, judging whether the numerical value of the photosensitive digital-to-analog conversion module at the moment is in a mapping interval of a preset mapping table;
s13, judging whether the current ae parameter value is in a convergence stage or a stabilization stage when the numerical value of the photosensitive digital-to-analog conversion module is positioned in a mapping interval of the mapping table;
s141, if the current ae parameter value is in a convergence stage, storing the ae parameter value mapped with the numerical value of the photosensitive digital-to-analog conversion module in the mapping table;
s15, taking the stored ae parameter value as a preset current convergence value of the automatic ae algorithm, and starting from the current convergence value, converging the automatic ae algorithm until the network camera acquires the first frame of stable image.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the system is divided into different functional units or modules to perform all or part of the above-described functions.
Claims (9)
1. The isp rapid ae convergence method is characterized by comprising the following steps:
when the network camera is powered on and operates, the value of the photosensitive digital-to-analog conversion module and the current ae parameter value are obtained;
judging whether the numerical value of the photosensitive digital-to-analog conversion module at the moment is in a mapping interval of a preset mapping table or not;
when the numerical value of the photosensitive digital-to-analog conversion module at the moment is positioned in the mapping interval of the mapping table, judging whether the current ae parameter value is in a convergence stage or a stable stage;
if the current ae parameter value is in the convergence stage, storing the ae parameter value mapped with the numerical value of the photosensitive digital-to-analog conversion module in the mapping table;
taking the stored ae parameter value as a preset current convergence value of the automatic ae algorithm, starting from the current convergence value, and converging the automatic ae algorithm until a network camera acquires a first frame of stable image;
the method also comprises the following steps:
when the network camera is powered off and dormant, automatically learning based on the acquired numerical value of the photosensitive digital-to-analog conversion module and the current ae parameter value, and updating the mapping table;
the step of automatically learning based on the acquired numerical value of the photosensitive digital-to-analog conversion module and the current ae parameter value comprises the following steps:
judging whether an ae parameter value of an automatic ae algorithm is in a stable state or not;
if the ae parameter value is stable, acquiring the current ae parameter value;
judging whether the numerical value of the photosensitive digital-to-analog conversion module in the current environment is in a mapping interval of a preset mapping table or not;
when the value of the photosensitive digital-to-analog conversion module is located outside the mapping interval of the mapping table, a mapping interval is newly created, and the obtained current ae parameter value and the value of the photosensitive digital-to-analog conversion module of the current environment are stored into the newly created mapping interval.
2. The isp fast ae convergence method of claim 1, wherein after the step of determining whether the current ae parameter value is in a convergence phase or a stabilization phase, further comprising the steps of:
and if the current ae parameter value is in the stable phase, storing the current ae parameter value.
3. The method of claim 1, wherein,
the method also comprises the following steps of,
when the numerical value of the photosensitive digital-to-analog conversion module at the moment is positioned in the mapping interval of the mapping table, the acquired current ae parameter value is stored in the corresponding mapping interval of the mapping table.
4. The isp fast ae convergence method of claim 1 wherein the ae parameter values comprise analog gain and exposure time.
5. The method of any one of claims 1-4, wherein the automatic ae algorithm calculates a difference between a current ambient brightness and a target brightness according to a brightness component of the pixel data, adjusts the current convergence value to be close to the target brightness, and dynamically updates the ae parameter value.
6. The isp fast ae convergence method of claim 5 wherein the step of adjusting the current convergence value to approach the target brightness comprises:
when the ambient brightness becomes dark gradually, the analog gain is made to become smaller gradually in multiple;
when the analog gain is reduced to the minimum value, if the ambient brightness continues to darken, adjusting the exposure time to continuously reduce the exposure time by a step size;
when the exposure time is less than the minimum value, the exposure time is decremented by the bit size.
7. An isp fast ae convergence device, comprising:
the data acquisition module is used for acquiring the value of the photosensitive digital-to-analog conversion module and the current ae parameter value when the network camera is powered on to run;
the first judging module is used for judging whether the numerical value of the photosensitive digital-to-analog conversion module at the moment is in a mapping interval of a preset mapping table;
the second judging module is used for judging whether the current ae parameter value is in a convergence stage or a stabilization stage when the numerical value of the photosensitive digital-to-analog conversion module at the moment is positioned in the mapping interval of the mapping table;
the parameter module is used for storing the ae parameter value mapped with the numerical value of the photosensitive digital-to-analog conversion module in the mapping table when the current ae parameter value is in a convergence stage;
the convergence module is used for taking the stored ae parameter value as a preset current convergence value of the automatic ae algorithm, starting from the current convergence value, and converging the automatic ae algorithm until the network camera acquires a first frame of stable image;
the learning module is used for automatically learning based on the acquired numerical value of the photosensitive digital-to-analog conversion module and the current ae parameter value when the network camera is powered off and dormant, and updating the mapping table; the step of automatically learning based on the acquired numerical value of the photosensitive digital-to-analog conversion module and the current ae parameter value comprises the following steps: judging whether an ae parameter value of an automatic ae algorithm is in a stable state or not; if the ae parameter value is stable, acquiring the current ae parameter value; judging whether the numerical value of the photosensitive digital-to-analog conversion module in the current environment is in a mapping interval of a preset mapping table or not; when the value of the photosensitive digital-to-analog conversion module is located outside the mapping interval of the mapping table, a mapping interval is newly created, and the obtained current ae parameter value and the value of the photosensitive digital-to-analog conversion module of the current environment are stored into the newly created mapping interval.
8. A computer device comprising a memory, a processor and a computer program stored on the memory, the processor executing the computer program to perform the steps of the method of any of claims 1-6.
9. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program which, when executed by a processor, implements the steps of the method of any of claims 1-6.
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