CN112333903B - Focusing method and device under light scene - Google Patents
Focusing method and device under light scene Download PDFInfo
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- CN112333903B CN112333903B CN202011174371.3A CN202011174371A CN112333903B CN 112333903 B CN112333903 B CN 112333903B CN 202011174371 A CN202011174371 A CN 202011174371A CN 112333903 B CN112333903 B CN 112333903B
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- H—ELECTRICITY
- H05—ELECTRIC TECHNIQUES NOT OTHERWISE PROVIDED FOR
- H05B—ELECTRIC HEATING; ELECTRIC LIGHT SOURCES NOT OTHERWISE PROVIDED FOR; CIRCUIT ARRANGEMENTS FOR ELECTRIC LIGHT SOURCES, IN GENERAL
- H05B47/00—Circuit arrangements for operating light sources in general, i.e. where the type of light source is not relevant
- H05B47/10—Controlling the light source
- H05B47/165—Controlling the light source following a pre-assigned programmed sequence; Logic control [LC]
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
- H02P29/00—Arrangements for regulating or controlling electric motors, appropriate for both AC and DC motors
Abstract
The embodiment of the invention provides a focusing method and device in a lamplight scene. The method comprises the following steps: controlling a focusing motor to move, and recording a corresponding data set when the focusing motor moves to different motor positions, wherein the data set comprises the motor positions and highlight points when the focusing motor moves to the motor positions, and the highlight points are the number of points of which the pixel brightness value exceeds a highlight point judgment threshold; determining the position of a target motor according to the corresponding data group when the target motor moves to different motor positions; and carrying out micro focusing based on the target motor position. The invention solves the focusing problem in the light scene, can accurately find out the parameters of the position of the clear point to focus the light scene, and has higher focusing precision.
Description
Technical Field
The embodiment of the invention relates to the technical field of automatic focusing, in particular to a focusing method and device in a lamplight scene.
Background
Focusing of an automatic focusing device under a night light scene is always a difficult point in the industry at present, particularly a large telephoto lens in the monitoring field. As the focal length increases day by day, the focusing of the object distances beyond the distance causes the lighting scene to become more and more extreme. For example, if facing a long distance overhead, the picture is almost "overlooked" by street lamps, i.e. a multi-light scene; or facing to a remote mountain, except a few sparse lights, other scenes are all low-light scenes, which belong to the low-light scenes, and fig. 1 is a photo effect schematic diagram under the low-light scenes, so that the photo effect is not satisfactory at the moment. At present, lighting scenes, such as multiple lighting scenes and low lighting scenes, make traditional focusing strategies increasingly difficult to cope with.
Disclosure of Invention
The embodiment of the invention provides a focusing method and device in a light scene, and aims to solve the problem of focusing in the light scene.
According to an embodiment of the present invention, there is provided a focusing method in a lighting scene, including: controlling a focusing motor to move, and recording a corresponding data set when the focusing motor moves to different motor positions, wherein the data set comprises the motor positions and highlight points when the focusing motor moves to the motor positions, and the highlight points are the number of points of which the pixel brightness value exceeds a highlight point judgment threshold value; determining the position of a target motor according to the corresponding data group when the target motor moves to different motor positions; and carrying out micro-focusing based on the target motor position.
In at least one exemplary embodiment, controlling the focus motor to move and recording the corresponding data set when the focus motor moves to a different motor position comprises: and controlling the focusing motor to move according to a preset step length according to preset parameters, and recording the corresponding data group after the focusing motor moves every time, wherein the preset parameters comprise brightness values or definition evaluation values, and the preset step length comprises a dynamic step length or a fixed step length.
In at least one exemplary embodiment, controlling the focus motor to move by a predetermined step size according to a predetermined parameter includes: determining a moving direction of the focusing motor; and controlling the focusing motor to move in the determined moving direction according to the predetermined step length until the focusing motor is determined to move to a first motor position, controlling the focusing motor to move to a motor position corresponding to the minimum value of the predetermined parameter and then move in the direction opposite to the determined moving direction according to the predetermined step length, and controlling the focusing motor to stop moving until the focusing motor is determined to move to a second motor position, wherein the first motor position is a motor position in which the value of the corresponding predetermined parameter is higher than the minimum value of the predetermined parameter by a predetermined ratio threshold when the focusing motor moves in the moving direction determined according to the predetermined step length, and the second motor position is a motor position in which the value of the corresponding predetermined parameter is higher than the minimum value of the predetermined parameter by the predetermined ratio threshold when the focusing motor moves in the direction opposite to the determined moving direction according to the predetermined step length.
In at least one exemplary embodiment, the method further comprises at least one of: before controlling the focusing motor to move to the determined moving direction according to the preset step length, obtaining a value of the preset parameter corresponding to the motor position where the focusing motor is located, and initializing a minimum value of the preset parameter according to the obtained value of the preset parameter; after the focusing motor moves every time, if the value of the preset parameter corresponding to the current motor position is smaller than the minimum value of the preset parameter, updating the minimum value of the preset parameter according to the value of the preset parameter corresponding to the current motor position; and after the focusing motor moves to the motor position corresponding to the minimum value of the preset parameter, acquiring the value of the preset parameter corresponding to the current motor position, and updating the minimum value of the preset parameter according to the acquired value of the preset parameter.
In at least one exemplary embodiment, determining the target motor position from the corresponding data sets when moved to the different motor positions comprises: performing unidirectional sequencing on the data sets according to the motor positions; determining all extreme points of the highlight points based on the data group subjected to unidirectional sorting; removing invalid extreme points from all the determined extreme points so that the number of the remaining valid extreme points does not exceed a predetermined number; and determining the position of the target motor according to the position of the motor corresponding to the effective extreme point.
In at least one exemplary embodiment, before unidirectionally sorting the data sets by the motor positions, the method further comprises: and removing the data group with the highlight point number of 0 from the corresponding data group when the motor moves to different motor positions.
In at least one exemplary embodiment, before determining all extreme points of the highlight point number based on the data set after one-way sorting, the method further includes: determining whether the number of sets of the data set is less than the predetermined number; when the number of the data groups is smaller than the preset number and larger than 0, taking the motor position in the data group with the minimum value of the high-brightness points in the data groups as the target motor position, and finishing the process of determining the target motor position according to the corresponding data group when the data groups move to different motor positions; and under the condition that the number of the data groups is not less than the preset number, continuously executing the step of determining all extreme points of the highlight points based on the data groups after one-way sorting.
In at least one exemplary embodiment, determining all extreme points of the highlight point number based on the data set after one-way sorting comprises: in the data groups after the unidirectional sorting, a first judgment operation is executed on every three consecutive data groups n, n +1, n +2, wherein 1 is less than or equal to n, n +2 is less than or equal to m, the initial value of n is 1, and the self increment 1,m is the number of the data groups after the first judgment operation is executed, and the first judgment operation comprises: judging whether the number of highlight points of the middle data set n +1 in the three continuous data sets n, n +1, n +2 is simultaneously larger than the number of highlight points of the data sets n and n +2 at two ends or is simultaneously smaller than the number of highlight points of the data sets n and n +2 at two ends, if so, determining the number of highlight points of the middle data set n +1 as an extreme point, and updating the number of the extreme points, otherwise, assigning the motor position and the number of highlight points included by the data set with the highest or the lowest highlight points in the data sets n and n +2 at two ends to the motor position and the number of highlight points included by the middle data set n + 1.
In at least one exemplary embodiment, the method further comprises: performing a second judgment operation on the first two consecutive data groups in the data groups after the unidirectional sorting, wherein the second judgment operation comprises: and judging whether the number of the highlight points of the second data group is smaller than that of the highlight points of the first data group, if so, setting the initial value of the number of the extreme points to be 1, and otherwise, setting the initial value of the number of the extreme points to be 0.
In at least one exemplary embodiment, before removing the invalid extreme point from all the determined extreme points so that the number of remaining valid extreme points does not exceed a predetermined number, further comprising: and deleting all data sets with the same motor position and/or the same highlight point number in the adjacent data sets into one data set.
In at least one exemplary embodiment, removing invalid extreme points from all the determined extreme points such that the number of remaining valid extreme points does not exceed a predetermined number comprises: removing, as invalid extreme points, of which the absolute value of the difference from the number of highlight points in the adjacent data group is less than or equal to a predetermined difference threshold, among all the determined extreme points, wherein the predetermined difference threshold is: fixing a difference threshold value, or the minimum value of the absolute values of the differences between all the extreme points and the number of the highlight points in the adjacent data set; and returning to the step of determining all extreme points of the highlight points on the basis of the filtered data set in the case that the number of the remaining effective extreme points still exceeds the predetermined number until the number of the remaining effective extreme points does not exceed the predetermined number.
In at least one exemplary embodiment, determining the target motor position based on the motor position corresponding to the valid extremum point comprises: determining whether a first descending point can be found in all the effective extreme points, and if so, taking the motor position corresponding to the first descending point as the target motor position; and otherwise, taking the motor position corresponding to the first effective extreme point as the target motor position.
In at least one exemplary embodiment, after removing, as the invalid extremum, an extremum point where an absolute value of a difference from the number of highlight points in the adjacent data group is less than or equal to a predetermined difference threshold, the method further includes: and deleting the middle data group in the three continuous data groups when the number of the highlight points in the three continuous data groups is monotonously changed in all the data groups.
In at least one exemplary embodiment, the micro-focusing based on the target motor position includes: controlling the focusing motor to move to the target motor position; and controlling the focusing motor to move in a preset range of the target motor position, searching a motor position with the minimum corresponding highlight point number, and controlling the focusing motor to move to the searched motor position with the minimum corresponding highlight point number.
In at least one exemplary embodiment, before controlling the movement of the focus motor and recording the corresponding data set when the focus motor moves to a different motor position, the method further includes: in the case that a light scene is identified, focusing of the light scene is started, and Automatic Exposure (AE) Exposure locking is performed.
According to another embodiment of the present invention, there is provided a focusing device in a lighting scene, comprising a memory in which a computer program is stored and a processor configured to execute the computer program to perform the steps of any of the above method embodiments.
According to a further embodiment of the present invention, there is also provided a computer-readable storage medium having a computer program stored thereon, wherein the computer program is arranged to perform the steps of any of the above method embodiments when executed.
According to the invention, the target motor position is determined according to the number of corresponding highlight points when the motor moves to different motor positions, and the micro-focusing is carried out based on the target motor position, so that the position of a clear point can be more accurately found, the focusing problem in a lighting scene can be solved, and the focusing precision is higher.
Drawings
FIG. 1 is a schematic view of a photo effect in a low-light scene;
FIG. 2 is a flow chart of a focusing method in a lighting scene according to an embodiment of the invention;
FIG. 3 is a block diagram of a focusing assembly in a lighting scene according to an embodiment of the invention;
FIG. 4 is a graph of brightness versus motor position (ordinate-brightness value; abscissa-focus motor position) collected for a certain lighting scene;
FIG. 5 is a graph showing the relationship between the number of highlight points and the position of the motor (ordinate-highlight point value; abscissa-focusing motor position) collected for the same lighting scene of FIG. 4;
FIG. 6 is a main flowchart of a method for improving the focusing effect of a light scene based on the number of highlight points according to an embodiment of the present invention;
FIG. 7 is a flow diagram of obtaining highlight point data according to an embodiment of the present invention;
fig. 8 is a flowchart of acquiring a target location according to an embodiment of the present invention.
Detailed Description
Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings in conjunction with the embodiments.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order.
The method embodiments provided in the embodiments of the present application may be executed in any image capturing device or remote server having an arithmetic capability. In the present embodiment, a focusing method in a lighting scene running on an image capturing device or a remote server thereof is provided, and fig. 2 is a flowchart of the focusing method in the lighting scene according to the embodiment of the present invention, as shown in fig. 2, the flowchart includes the following steps S202 to S206.
Step S202, controlling a focusing motor to move, and recording a corresponding data set when the focusing motor moves to different motor positions, wherein the data set comprises the motor positions and highlight points when the focusing motor moves to the motor positions, and the highlight points are the number of points of which the pixel brightness values exceed a highlight point judgment threshold value.
In order to obtain the highlight point data corresponding to different motor positions accurately and quickly, step S202 may be implemented by moving the focusing motor according to a predetermined step length and collecting the highlight point data when stopping. Thus, in at least one exemplary embodiment, step S202 may comprise:
and controlling the focusing motor to move according to a preset step length according to preset parameters, and recording the corresponding data group after the focusing motor moves every time, wherein the preset parameters comprise brightness values or definition evaluation values, and the preset step length comprises a dynamic step length or a fixed step length.
In practical applications, the dynamic step size may be dynamically determined according to the focal length and/or the focusing range. The dynamic step size or the fixed step size is not suggested to be selected to be too large so as to avoid the trend of highlight points being ignored and covered.
In at least one exemplary embodiment, controlling the focus motor to move by a predetermined step size according to a predetermined parameter may include:
determining a moving direction of the focus motor, which may be determined based on various factors (including a position of the focus motor within a focus range, a last focus moving direction, etc.) in practical applications;
controlling the focusing motor to move to the determined moving direction according to the predetermined step length until the focusing motor is determined to move to the first motor position, controlling the focusing motor to move to the motor position corresponding to the minimum value of the predetermined parameter and then to move to the opposite direction of the determined moving direction according to the predetermined step length until the focusing motor is determined to move to the second motor position, and controlling the focusing motor to stop moving,
the first motor position is a motor position where a value of the corresponding predetermined parameter is higher than a minimum value of the predetermined parameter by a predetermined ratio threshold when the focusing motor moves in the determined moving direction according to the predetermined step length, and the second motor position is a motor position where a value of the corresponding predetermined parameter is higher than the minimum value of the predetermined parameter by the predetermined ratio threshold when the focusing motor moves in the opposite direction of the determined moving direction according to the predetermined step length.
In brief, the focusing motor is controlled to move in two directions to collect high-brightness point data in the process, and the reverse or stop operation is realized by judging the position of the first motor and the position of the second motor, so that the focusing range can be effectively converged, and the overlarge focusing range is avoided.
The minimum value of the predetermined parameter can be initialized before the process is started, updated continuously during the moving process, and reassigned in the reverse direction. For example, in at least one exemplary embodiment, the method further comprises at least one of:
before controlling the focusing motor to move to the determined moving direction according to the preset step length, obtaining a value of the preset parameter corresponding to the motor position where the focusing motor is located, and initializing a minimum value of the preset parameter according to the obtained value of the preset parameter;
after the focusing motor moves every time, if the value of the preset parameter corresponding to the current motor position is smaller than the minimum value of the preset parameter, updating the minimum value of the preset parameter according to the value of the preset parameter corresponding to the current motor position;
and after the focusing motor moves to the motor position corresponding to the minimum value of the preset parameter, acquiring the value of the preset parameter corresponding to the current motor position, and updating the minimum value of the preset parameter according to the acquired value of the preset parameter.
In at least one exemplary embodiment, before step S202, the method may further include: and starting the focusing of the light scene under the condition that the light scene is identified, and carrying out automatic exposure AE exposure locking. The AE exposure locking operation comprises fixing related parameters of the current adjusted AE, such as aperture, shutter, gain, angle and intensity of a light supplement lamp.
And step S204, determining the target motor position according to the corresponding data set when the motor moves to different motor positions.
In at least one exemplary embodiment, step S204 may include the following processes:
performing unidirectional sequencing on the data sets according to the motor positions;
determining all extreme points of the highlight points based on the data group subjected to unidirectional sorting;
removing the invalid extreme points from all the determined extreme points so that the number of remaining valid extreme points does not exceed a predetermined number (in the curve rule exemplified in the embodiment of the present invention, the number of extreme points in the shape of the curve M is 3, so that the predetermined number is preferably equal to 3 in the embodiment);
and determining the position of the target motor according to the position of the motor corresponding to the effective extreme point.
Since the distribution of the number of highlight points corresponding to different motor positions follows a certain curve law (see, for example, fig. 4 and 5), and the central extreme point of the shape of the curve M corresponds to the distinct point, if all valid extreme points can be found and the target motor position is determined based on the motor position corresponding to the valid extreme point, the position of the distinct point can be basically found, because the final distinct point must be within a small range of the target motor position.
Before the data processing screening is carried out, the 0 value data of the highlight points can be removed, because the 0 value data has no reference meaning for the result analysis. Therefore, in at least one exemplary embodiment, before unidirectionally sorting the data sets according to the motor positions, the method may further include: and removing the data group with the highlight point number of 0 from the corresponding data group when the motor moves to different motor positions.
If the number of data sets is small, for example 0-2, the determination can be made directly without complicated model refinement. Therefore, in at least one exemplary embodiment, before determining all extreme points of the highlight point number based on the data set after one-way sorting, the method may further include:
determining whether the number of sets of the data set is less than the predetermined number;
when the number of the data sets is smaller than the predetermined number and greater than 0, taking the motor position in the data set with the smallest value of the number of the highlight points in the data sets as the target motor position, and ending the processing of step S204;
and under the condition that the number of the data groups is not less than the preset number, continuously executing the step of determining all extreme points of the highlight points based on the data groups after one-way sorting.
It is also possible that the number of groups of the data sets is less than the predetermined number and equal to 0, which indicates that no non-0 highlight point is detected at any one of the motor positions, which indicates that the current scene is not suitable for the current method, and that other methods may be used for focusing.
In at least one exemplary embodiment, determining all extreme points of the highlight point number based on the data set after one-way sorting may include:
performing a first judgment operation on each three consecutive data groups n, n +1, n +2 in the data groups after the unidirectional sorting, wherein 1 is less than or equal to n, n +2 is less than or equal to m, the initial value of n is 1, and the self increment 1,m is the number of the data groups after the completion of the first judgment operation,
the first judgment operation includes:
judging whether the highlight point number of the middle data set n +1 in the three continuous data sets n, n +1, n +2 is simultaneously larger than the highlight point number of the data sets n and n +2 at the two ends or simultaneously smaller than the highlight point number of the data sets n and n +2 at the two ends,
if yes, determining the number of the highlight points of the intermediate data set n +1 as an extreme point, updating the number of the extreme points,
otherwise, assigning the motor position and the highlight point number included in the data group with the highest or lowest highlight point number in the two-end data group n and n +2 to the motor position and the highlight point number included in the middle data group n +1, wherein the highlight point numbers of the three data groups are monotonously changed, the middle data group can be simplified, and the middle redundant point is actually removed by covering the value of the middle data group with the value of the data group with the lower (or higher) highlight point number in the two-end data group.
In at least one exemplary embodiment, the method further comprises: performing a second judgment operation on the first two consecutive data groups in the data groups after the unidirectional sorting, wherein the second judgment operation comprises: and judging whether the number of the highlight points of the second data group is smaller than that of the highlight points of the first data group, if so, setting the initial value of the number of the extreme points to be 1, and otherwise, setting the initial value of the number of the extreme points to be 0. When the data initially appears to fall, it can be considered to occupy the first inflection point, and therefore, when the number of highlight points of the second data group is smaller than that of the first data group, the initial value of the number of extreme points is set to 1, and otherwise, to 0.
In at least one exemplary embodiment, before removing the invalid extreme points from all the determined extreme points so that the number of remaining valid extreme points does not exceed the predetermined number, the method may further include: and deleting all data sets with the same motor position and/or the same highlight point number in the adjacent data sets into one data set. Through the scheme, the same highlight point number and/or the same motor position value are/is simplified, redundant data are removed, and finally the final target position is screened out from the simplified data by matching with other simplification steps.
In at least one exemplary embodiment, removing the invalid extreme points from all the determined extreme points such that the number of remaining valid extreme points does not exceed a predetermined number may include: removing, as an invalid extreme point, an extreme point, of which the absolute value of the difference value from the number of highlight points in the adjacent data group is less than or equal to a predetermined difference threshold value, from among all the determined extreme points (the specific implementation of the removal may be that the adjacent point covers the value of the data group at the extreme point, and the removal may be achieved by matching with a reduction step), where the predetermined difference threshold value is: fixing a difference threshold value, or the minimum value of the absolute values of the differences between all the extreme points and the number of the highlight points in the adjacent data set; and returning to the step of determining all extreme points of the highlight points on the basis of the filtered data set in the case that the number of the remaining effective extreme points still exceeds the predetermined number until the number of the remaining effective extreme points does not exceed the predetermined number.
In at least one exemplary embodiment, determining the target motor position according to the motor position corresponding to the valid extremum point may include: determining whether a first descending point can be found in all the effective extreme points, and if so, taking the motor position corresponding to the first descending point as the target motor position; and otherwise, taking the motor position corresponding to the first effective extreme point as the target motor position.
In at least one exemplary embodiment, after removing, as the invalid extreme point, an extreme point whose absolute value of a difference from the number of highlight points in the adjacent data group is less than or equal to a predetermined difference threshold, the method may further include: in all the data sets, deleting the middle data set in the three continuous data sets under the condition that the number of the highlight points in the three continuous data sets is monotonously changed. This step is also a reduction step for a single change of three consecutive values.
Step S206, carrying out micro focusing based on the target motor position.
In at least one exemplary embodiment, step S206 may include:
controlling the focusing motor to move to the target motor position;
and controlling the focusing motor to move in a preset range of the target motor position, searching a motor position with the minimum corresponding highlight point number, and controlling the focusing motor to move to the searched motor position with the minimum corresponding highlight point number.
In practical application, the highlight point number can be compared based on the target position, once the highlight point number is increased, the direction is reversed, the minimum highlight point number can be found by reversing twice, and the user only needs to walk to the corresponding position. Furthermore, the advancing step length of the motor in two directions can be synchronously recorded when the highlight point data are recorded, the focusing range is set based on the advancing step length, the minimum highlight point in the range is gradually found, and the motor moves to the corresponding position.
By the method, the target motor position is determined according to the number of the corresponding high-brightness points when the motor moves to different motor positions, and micro focusing is performed based on the target motor position, so that the position of a clear point can be found out more accurately, the focusing problem in a lighting scene can be solved, and higher focusing precision is achieved.
Through the description of the foregoing embodiments, it is clear to those skilled in the art that the method according to the foregoing embodiments may be implemented by software plus a necessary general hardware platform, and certainly may also be implemented by hardware, but the former is a better implementation mode in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present invention.
In this embodiment, a focusing device in a light scene is further provided, where the focusing device is used to implement the foregoing embodiments and preferred embodiments, and details are not described again. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. Although the means described in the embodiments below are preferably implemented in software, an implementation in hardware, or a combination of software and hardware is also possible and contemplated.
Fig. 3 is a block diagram of a focusing device in a lighting scene according to an embodiment of the present invention, and as shown in fig. 3, the device includes a memory 32 and a processor 34, the memory 32 stores a computer program, and the processor 34 is configured to execute the computer program to perform the steps in any one of the above method embodiments.
It should be noted that, the above modules may be implemented by software or hardware, and for the latter, the following may be implemented, but not limited to: the modules are all positioned in the same processor; alternatively, the modules are respectively located in different processors in any combination.
Embodiments of the present invention also provide a computer-readable storage medium having a computer program stored thereon, wherein the computer program is arranged to perform the steps of any of the above-mentioned method embodiments when executed.
In the present embodiment, the above-mentioned computer-readable storage medium may be configured to store a computer program for executing the steps of:
s1, controlling a focusing motor to move, and recording a corresponding data set when the focusing motor moves to different motor positions, wherein the data set comprises the motor positions and highlight points when the focusing motor moves to the motor positions, and the highlight points are the number of points of which pixel brightness values exceed a highlight point judgment threshold value;
s2, determining the position of a target motor according to the corresponding data set when the target motor moves to different motor positions;
and S3, carrying out micro-focusing based on the position of the target motor.
In an exemplary embodiment, the computer-readable storage medium may include, but is not limited to: various media capable of storing computer programs, such as a usb disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic disk, or an optical disk.
Embodiments of the present invention also provide an electronic device comprising a memory having a computer program stored therein and a processor arranged to run the computer program to perform the steps of any of the above method embodiments.
In an exemplary embodiment, the electronic apparatus may further include a transmission device and an input/output device, wherein the transmission device is connected to the processor, and the input/output device is connected to the processor.
In an exemplary embodiment, the processor may be configured to execute the following steps by a computer program:
s1, controlling a focusing motor to move, and recording a corresponding data set when the focusing motor moves to different motor positions, wherein the data set comprises the motor positions and highlight points when the focusing motor moves to the motor positions, and the highlight points are the number of points of which pixel brightness values exceed a highlight point judgment threshold value;
s2, determining the position of a target motor according to the corresponding data set when the target motor moves to different motor positions;
and S3, carrying out micro-focusing based on the position of the target motor.
For specific examples in this embodiment, reference may be made to the examples described in the above embodiments and exemplary embodiments, and details of this embodiment are not repeated herein.
To facilitate understanding of the scheme, the following exemplary embodiments give a principle analysis of the focus method based on the number of highlight points, and examples of specific implementations.
Fig. 4 is a graph of brightness versus motor position (ordinate-brightness value; abscissa-focus motor position) collected for a certain lighting scene. As shown in fig. 4, there is a feature for a lighting scene that when the lighting scene is focused clearly, the lighting is generally in or close to the least divergent state, and the overall brightness of the picture is close to the lowest.
In addition, if a threshold is set, and the luminance value of each pixel exceeds this value, we regard it as a highlight. The sum of the numbers of the highlight points of the picture, namely, the commonly used concept of the number of the highlight points in the monitoring field, can be used as a basis for judging whether the scene is a light scene. Fig. 5 is a diagram of the relationship between the number of highlight points and the position of the motor (ordinate-highlight point value; abscissa-focusing motor position) collected for the same lighting scene of fig. 4. As shown in fig. 5, in the coordinate relationship diagram of the number of the highlight dots and the position of the focusing motor, the position 791 is the actual clear point position, that is, the number of the highlight dots becomes convergent as it goes to the clear point near the clear point, and it becomes 0 as it goes from the clear point to any direction of the motor, and it becomes ascending first and then descending. The 'M' shape is a classic highlight point shape, and actually, in consideration of the set range of a focusing motor, the setting of a highlight point judgment threshold and the intensity of light of an actual scene, the 'M' shape may show various defects, such as loss of a part of a left rising edge and even loss of all the left rising edge, and only the 'M' shape remains; the lifting and the falling are lost, and only the shape of 'inverted V' is left; also inferred are the shapes of a 'V-V', '/', '\ and even'. Lambda.. In a deeper consideration, in any ascending and descending process of the highlight points, due to factors such as light flicker and the like, monotonicity may not be perfectly presented, and a plurality of wave crests with smaller amplitude may exist in the middle.
Based on the model, the position of the clear point can be found through the brightness and the number of the high points, but in the actual scene, particularly a low-light scene and a multi-light scene, the clear point found through the brightness has larger deviation with the actual clear point, and the clear point can be found more accurately by using the number of the high points. And clear points are found through the number of the high-brightness points, and compared with monotonicity of brightness, the interference of various 'defect' models needs to be solved through an algorithm.
Therefore, for the focusing problem in the actual lighting scene, based on the above analysis, the present exemplary embodiment provides a lighting focusing scheme based on the number of highlight points, which is used to improve the focusing effect of the lighting scene of the zooming device.
Fig. 6 is a main flowchart of a method for improving the focusing effect of a light scene based on the number of highlight points according to an embodiment of the present invention. As shown in fig. 6, the method includes the steps of:
step S601, after the light scene focusing is started, AE exposure lock is performed.
The identification of the lighting scene is a mature technology, and can be obtained through judgment of exposure parameters such as gain and highlight points, and the details are not described here. The AE exposure locking is also a mature technology, namely relevant parameters of current adjustment AE, such as aperture, shutter, gain, angle and intensity of a light supplement lamp, are fixed, and the purpose of the AE exposure locking is to avoid the change of highlight points caused by the change of exposure parameters and influence the final result. After this step, step S602 is executed;
and step S602, moving the focusing motor according to the brightness value, and simultaneously collecting data of highlight points. Fig. 7 is a flowchart of acquiring data of highlight points according to an embodiment of the present invention, and a specific process of step S602 is shown in fig. 7 and will be separately described in detail below.
And step S603, acquiring the target motor position according to the highlight point data, wherein the step relates to data simplification and extraction. Fig. 8 is a flowchart of acquiring a target location according to an embodiment of the present invention, and a specific process of step S603 is shown in fig. 8 and will be separately described in detail below.
Step S604, performing micro focusing based on the target position. Namely, the valley position of the highlight point is found nearby. The method is simple, the highlight point number can be compared based on the target position, once the highlight point number is increased, the direction is reversed, the minimum highlight point number can be found by reversing twice, and the user only needs to walk to the corresponding position. Furthermore, the moving step length of the motor in two directions can be synchronously recorded when the highlight point number data are recorded, the focusing range is set based on the moving step length, the minimum highlight point number in the range is gradually found, and the user can walk to the corresponding position. And if the step is finished, the whole process is finished.
In the above main flow, step S602 involves moving the focus motor according to the brightness value and collecting data of the number of highlight dots at the same time, and the specific process of step S602 will be described in detail below with reference to fig. 7. As shown in fig. 7, an exemplary implementation of step S602 is as follows:
step 1, determining the moving direction of a focusing motor, and taking the current brightness value as the minimum brightness value. The determination of the motor moving direction is limited by a plurality of factors, such as the current motor position in the focusing range, the last focusing moving direction and the like, and can be determined according to actual conditions. Focusing can be started based on the current motor position, and step 2 is executed;
and 2, walking towards a determined direction by a certain step length strategy, updating the minimum brightness value and the corresponding motor position, and recording the number of highlight points at the stop position and the motor position data. The step length strategy is a common processing strategy of the current general focusing algorithm and is dynamically determined according to the focal length and the focusing range, the step length required by the proposal cannot be too large so as to avoid the trend of highlight points being covered, and the specific step length setting is not described. The data format is set as data i ＝(fp,cnt)。data i Indicating the ith recorded data, fp indicating the focus motor position, and cnt indicating the number of highlight dots. After the step is finished, executing a step 3;
and 3, judging whether the current brightness exceeds a certain threshold of the minimum brightness value, namely judging whether the difference value between the current brightness and the minimum brightness value exceeds the minimum brightness value and the threshold (the threshold can be in a percentage form), if so, executing the step 4, otherwise, continuously executing the step 2. The threshold value may be set according to actual requirements, and may be set to 5% for example. This step is used to converge the focus range, avoiding the focus range being too large;
step 4, has the moving direction of the focus motor changed (i.e., has changed to the opposite direction of the previously determined moving direction)? If yes, executing step 6, otherwise, executing step 5;
and 5, moving to the position of the motor corresponding to the minimum brightness value, updating the position of the motor corresponding to the minimum brightness value after moving, and changing the direction of the motor in the step 1 (converting to the opposite direction of the moving direction determined in the step 1). Continuing to execute the step 2;
and 6, ending.
Note that the acquisition of highlight point data is not limited to the method shown in fig. 7, and the highlight point data may be collected based on the sharpness evaluation value. After the highlight point number data is collected, step S603 is executed.
In the above main flow, step S603 involves acquiring the target motor position from the data of the highlight point number, which involves simplified refinement of the data, and the specific process of step S603 will be described in detail below with reference to fig. 8. As shown in fig. 8, an exemplary implementation of step S603 is as follows:
step 1, removing the data with the highlight points as 0 value, and sorting the data in a one-way mode according to the motor position. The data with the highlight point number of 0 has no reference significance for result analysis and can be directly deleted. The remaining valid data may be sorted and re-determined data index values from small to large or from large to small by motor position. After the step is finished, executing the step 2;
and 2, judging whether the number of the residual effective data is less than 3. If the number of the highlight points at the motor positions is less than 3, only 0-2 motor positions are not 0, the step 3 is directly executed without complex model extraction, and otherwise, the step 6 is executed;
step 4, focusing by other methods, and finishing after execution;
and 5, taking the motor position corresponding to the minimum value of the highlight number as a target position. This step is performed on the premise that only 1-2 motor positions have a high highlight point number, and is directly regarded as a model '/', '\\\ \ or' ·. Taking the position of the motor corresponding to the minimum value of the highlight number as a target position and finishing;
step 6, is the data initially present a downward trend? This step is intended to prepare for the subsequent determination of whether the extremum point data exceeds 3. According to the analysis of the highlight point model, the number of extreme points of the simplified model is at most 'M', namely three extreme points exist, so that the simplification of the data extreme points takes 3 (three extreme points) as a judgment basis, and when the data initially appears to be descending, the data can be considered to occupy the first extreme point. Therefore, if the initial presentation is decreased, step 7 is executed, otherwise step 8 is executed;
step 7, the number of extreme points is 1, the reason is as described in step 6, and step 9 is executed after the step is finished;
step 8, the number of the extreme points is 0, the reason is as described in step 6, and step 9 is executed after the step is finished;
step 9, end of traversal? The traversal refers to the step 10 judgment once for every three groups of data with the index value n, n +1, n +2, wherein n is increased by 1 every time of judgment, the data index value is set to start from 1, and the maximum value is m, the value range is 1-n, and n + 2-m. Executing step 13 when traversing is finished, and executing step 10 when traversing is not finished;
step 10, there is an extreme point in the current index three values? The basis of the judgment is
(cnt n -cnt n+1 )*(cnt n+1 -cnt n+2 )＜0
Namely, the number of highlight points of the middle data of the three data traversed at present is larger than or smaller than that of the highlight points on the two sides, and the extreme points are considered to exist. If the extreme point exists, executing step 11, otherwise executing step 12;
and 11, adding 1 to the number of the extreme points, and comparing and updating the absolute value of the difference value between the extreme points and the previous and next data with the minimum value of the extreme points. The judgment basis is as follows:
if abs (cnt) n -cnt n+1 )＜cnt min Then cnt min ＝abs(cnt n -cnt n+1 )；
If abs (cnt) n+1 -cnt n+2 )＜cnt min Then cnt min ＝abs(cnt n+1 -cnt n+2 )。
Wherein cnt min With the first poleAnd initializing the absolute value of the difference between the value point and the data before and after the value point. After this step is completed, step 13 is executed;
and step 12, processing the value of which the middle value is equal to the minimum highlight number in the three values. If there is no extreme point, the three data are monotonous, and the value with the middle value equal to the minimum highlight number in the three values can be processed. Namely:
if cnt n ＜cnt n+2 Then data n+1 ＝data n (ii) a Otherwise, data n+1 ＝data n+2 ；
After the step is executed, executing a step 13;
and step 13, adding 1 to the index value, and continuing to traverse the data after the n is increased by 1. After the step is finished, executing a step 9;
and 14, simplifying the same highlight point number or the same motor position value. In the step, as long as the number of highlight points exists in all adjacent data or the motor positions are the same, the same data is directly deleted to one part (which data is deleted has no special sorting requirement), and the data index numbers are sorted again; after the step is executed, executing step 15;
and step 15, the number of extreme points exceeds 3. If the number of extreme points exceeds 3, executing step 16, otherwise executing step 18;
and step 16, filtering the minimum value of the extreme point. The aim of the step is to reduce the number of extreme values, and the reduction method is to traverse all data and make the absolute value of the difference value of the highlight points of the adjacent data equal to cnt min And assigning the smaller value of the highlight point number to the larger value, wherein the assignment content comprises the motor position and the highlight point number, namely only the difference of the data index number is reserved. After the step is executed, executing step 17;
and step 17, simplifying the continuous three values in a one-way change mode. Because the minimum value filtering of the extreme points is carried out in the step 16, a plurality of values in the same direction may exist after the extreme points are filtered out (namely, a new continuous three-value single-item change is formed), the step is set to realize the simplification of data, and the step aims to remove redundant data in continuous rising or continuous falling, namely, directly delete the data and reorder the data index numbers. Continuing to execute the step 6 after the step is executed;
can the first descent point be found, step 18? Traversing the data to find the first adjacent data to be descended, if found, executing step 19, otherwise, executing step 20;
step 19, taking the position of the motor corresponding to the first descending point as a final target position and finishing;
and 20, taking the motor position corresponding to the first index value as a final target position and finishing.
The core idea of step S603 is to remove redundant data in the middle of equal or monotone changes, reduce the number of extremum points to within three according to the number quality of extremum points, and screen out a motor position from the final simplified data as a final target position. The above flow is not the only method for realizing the idea, and any data processing flow based on the idea should be in the protection scope.
The embodiment of the invention provides a scheme for focusing a light scene based on highlight points, which solves the problem of focusing effect of light scenes which are extremely difficult to focus (called as light scenes in the embodiment of the invention) such as multiple lights or low-light lights and the like by using the highlight points. According to the scheme, high-brightness point focusing motor position combined data collection is carried out based on brightness information, redundant data in the middle of adjacent high-brightness point equality or motor position equality or monotone change of the collected data are removed, extreme value points are reduced to be within three according to extreme value point quality, a motor position is selected as a final target position according to final simplified data, and a final clear point is found based on micro focusing of the target high-brightness point focusing motor position.
This scheme has the following advantages:
(1) The parameter of the highlight point, which can more accurately find the position of the clear point, is used for focusing the light scene. Compared with brightness focusing, the method has higher precision, and the method is more obvious under multiple lighting lights and low lighting light. Compared with a method for reducing the weight of the operator in the lighting area, the method has obvious advantages in the lighting scenes with multiple lights and low lighting lights.
(2) The scheme can obviously improve the focusing effect of the light scene, particularly the light scene with multiple lights and the light scene with a low lighting light, and has better practicability.
(3) The scheme innovatively uses a series of algorithms to solve the problem that highlight point data are difficult to process, so that highlight point focusing becomes possible;
(4) The processing steps and the algorithm idea in the scheme are suitable for almost all lighting scenes, and have wide applicability.
It will be apparent to those skilled in the art that the various modules or steps of the invention described above may be implemented using a general purpose computing device, they may be centralized on a single computing device or distributed across a network of computing devices, and they may be implemented using program code executable by the computing devices, such that they may be stored in a memory device and executed by the computing device, and in some cases, the steps shown or described may be performed in an order different than that described herein, or they may be separately fabricated into various integrated circuit modules, or multiple ones of them may be fabricated into a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the principle of the present invention should be included in the protection scope of the present invention.
Claims (13)
1. A focusing method under a lighting scene is characterized by comprising the following steps:
controlling a focusing motor to move, and recording a corresponding data set when the focusing motor moves to different motor positions, wherein the data set comprises the motor positions and highlight points when the focusing motor moves to the motor positions, and the highlight points are the number of points of which the pixel brightness value exceeds a highlight point judgment threshold value;
determining the position of a target motor according to the corresponding data group when the target motor moves to different motor positions;
performing micro-focusing based on the target motor position;
wherein the content of the first and second substances,
determining the target motor position from the corresponding data set when moving to the different motor positions comprises:
performing unidirectional sequencing on the data sets according to the motor positions;
determining all extreme points of the highlight points based on the data group subjected to unidirectional sorting;
removing invalid extreme points from all the determined extreme points such that the number of remaining valid extreme points does not exceed a predetermined number, wherein removing invalid extreme points from all the determined extreme points such that the number of remaining valid extreme points does not exceed the predetermined number comprises: removing, as invalid extreme points, of which the absolute value of the difference from the number of highlight points in the adjacent data group is less than or equal to a predetermined difference threshold, among all the determined extreme points, wherein the predetermined difference threshold is: the minimum value of the absolute values of the difference values between all the extreme points and the number of the highlight points in the adjacent data set; under the condition that the number of the remaining effective extreme points still exceeds the preset number, returning to the step of determining all the extreme points of the highlight points on the basis of the filtered data set until the number of the remaining effective extreme points does not exceed the preset number;
determining the target motor position according to the motor position corresponding to the effective extreme point, wherein determining the target motor position according to the motor position corresponding to the effective extreme point comprises: determining whether a first descending point can be found in all the effective extreme points, and if so, taking the motor position corresponding to the first descending point as the target motor position; and otherwise, taking the motor position corresponding to the first effective extreme point as the target motor position.
2. The method of claim 1, wherein controlling movement of a focus motor and recording a corresponding data set when the focus motor is moved to a different motor position comprises:
and controlling the focusing motor to move according to a preset step length according to preset parameters, and recording the corresponding data group after the focusing motor moves every time, wherein the preset parameters comprise brightness values or definition evaluation values, and the preset step length comprises a dynamic step length or a fixed step length.
3. The method of claim 2, wherein controlling the focus motor to move in predetermined steps based on predetermined parameters comprises:
determining a moving direction of the focusing motor; and controlling the focusing motor to move in the determined moving direction according to the predetermined step length until the focusing motor is determined to move to a first motor position, controlling the focusing motor to move to a motor position corresponding to the minimum value of the predetermined parameter and then move in the direction opposite to the determined moving direction according to the predetermined step length, and controlling the focusing motor to stop moving until the focusing motor is determined to move to a second motor position, wherein the first motor position is a motor position in which the value of the corresponding predetermined parameter is higher than the minimum value of the predetermined parameter by a predetermined ratio threshold when the focusing motor moves in the moving direction determined according to the predetermined step length, and the second motor position is a motor position in which the value of the corresponding predetermined parameter is higher than the minimum value of the predetermined parameter by the predetermined ratio threshold when the focusing motor moves in the direction opposite to the determined moving direction according to the predetermined step length.
4. The method of claim 3, further comprising at least one of:
before controlling the focusing motor to move to the determined moving direction according to the preset step length, obtaining a value of the preset parameter corresponding to the motor position where the focusing motor is located, and initializing a minimum value of the preset parameter according to the obtained value of the preset parameter;
after the focusing motor moves every time, if the value of the preset parameter corresponding to the current motor position is smaller than the minimum value of the preset parameter, updating the minimum value of the preset parameter according to the value of the preset parameter corresponding to the current motor position;
and after the focusing motor moves to the motor position corresponding to the minimum value of the preset parameter, acquiring the value of the preset parameter corresponding to the current motor position, and updating the minimum value of the preset parameter according to the acquired value of the preset parameter.
5. The method of claim 1, further comprising, prior to unidirectionally sorting the data sets by the motor position:
and removing the data group with the highlight point number of 0 from the corresponding data group when the motor moves to different motor positions.
6. The method of claim 1, further comprising, before determining all extreme points of the highlight point number based on the data set after one-way sorting:
determining whether the number of sets of the data set is less than the predetermined number;
when the number of the data groups is smaller than the preset number and larger than 0, taking the motor position in the data group with the minimum value of the high-brightness points in the data groups as the target motor position, and finishing the process of determining the target motor position according to the corresponding data group when the data groups move to different motor positions;
and under the condition that the number of the data groups is not less than the preset number, continuously executing the step of determining all extreme points of the highlight points based on the data groups after one-way sorting.
7. The method of claim 1, wherein determining all extreme points of the highlight point number based on the data set after one-way sorting comprises:
performing a first judgment operation on each three consecutive data groups n, n +1, n +2 in the data groups after the unidirectional sorting, wherein 1 is less than or equal to n, n +2 is less than or equal to m, the initial value of n is 1, and the self increment 1,m is the number of the data groups after the completion of the first judgment operation,
the first judgment operation includes:
judging whether the number of highlight points of the middle data set n +1 in the three continuous data sets n, n +1, n +2 is simultaneously larger than the number of highlight points of the data sets n and n +2 at two ends or is simultaneously smaller than the number of highlight points of the data sets n and n +2 at two ends, if so, determining the number of highlight points of the middle data set n +1 as an extreme point, and updating the number of the extreme points, otherwise, assigning the motor position and the number of highlight points included by the data set with the highest or the lowest highlight points in the data sets n and n +2 at two ends to the motor position and the number of highlight points included by the middle data set n + 1.
8. The method of claim 7, further comprising:
performing a second judgment operation on the first two consecutive data groups in the data groups after the unidirectional sorting, wherein the second judgment operation comprises:
and judging whether the number of the highlight points of the second data group is smaller than that of the highlight points of the first data group, if so, setting the initial value of the number of the extreme points to be 1, and otherwise, setting the initial value of the number of the extreme points to be 0.
9. The method of claim 1, further comprising, before removing invalid extreme points from all determined extreme points such that the number of remaining valid extreme points does not exceed a predetermined number:
and deleting all data sets with the same motor position and/or the same highlight point number in the adjacent data sets into one data set.
10. The method according to claim 1, further comprising, after removing, as invalid extrema, extrema having an absolute value of a difference from the number of highlight dots in the adjacent data group that is less than or equal to a predetermined difference threshold:
and deleting the middle data group in the three continuous data groups when the number of the highlight points in the three continuous data groups is monotonously changed in all the data groups.
11. The method of claim 1, wherein micro-focusing based on the target motor position comprises:
controlling the focusing motor to move to the target motor position;
and controlling the focusing motor to move in a preset range of the target motor position, searching a motor position with the minimum corresponding highlight point number, and controlling the focusing motor to move to the searched motor position with the minimum corresponding highlight point number.
12. The method of claim 1, further comprising, prior to controlling movement of a focus motor and recording a corresponding data set when the focus motor is moved to a different motor position:
and starting the focusing of the light scene under the condition that the light scene is identified, and carrying out automatic exposure AE exposure locking.
13. A focusing device in a light scene, comprising a memory and a processor, wherein the memory has stored therein a computer program, and the processor is configured to execute the computer program to perform the method according to any one of claims 1 to 12.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102473306A (en) * | 2010-05-24 | 2012-05-23 | 松下电器产业株式会社 | Image processing apparatus, image processing method, program and integrated circuit |
| CN111629143A (en) * | 2020-04-24 | 2020-09-04 | 江苏大学 | Target searching system and method based on combination of specific light source identification and sound source positioning |
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