CN108200421B - White balance processing method, terminal and computer readable storage medium - Google Patents

White balance processing method, terminal and computer readable storage medium Download PDF

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CN108200421B
CN108200421B CN201711459257.3A CN201711459257A CN108200421B CN 108200421 B CN108200421 B CN 108200421B CN 201711459257 A CN201711459257 A CN 201711459257A CN 108200421 B CN108200421 B CN 108200421B
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index value
exposure index
current
current frame
white balance
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CN108200421A (en
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张啸林
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Zhuhai Dahengqin Technology Development Co Ltd
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Zhuhai Dahengqin Technology Development Co Ltd
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    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N9/00Details of colour television systems
    • H04N9/64Circuits for processing colour signals
    • H04N9/73Colour balance circuits, e.g. white balance circuits or colour temperature control
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/80Camera processing pipelines; Components thereof
    • H04N23/84Camera processing pipelines; Components thereof for processing colour signals
    • H04N23/88Camera processing pipelines; Components thereof for processing colour signals for colour balance, e.g. white-balance circuits or colour temperature control

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  • Multimedia (AREA)
  • Signal Processing (AREA)
  • Color Television Image Signal Generators (AREA)

Abstract

The embodiment of the invention discloses a white balance processing method, which comprises the steps of determining a weight group corresponding to a current ambient light source according to an exposure index value of a shooting environment and a pre-stored weight table; the pre-stored weight table comprises: presetting a corresponding relation between the exposure index value and the preset weight set; and determining an automatic white balance AWB parameter of the current frame image according to all statistic points of the current frame image and the weight group corresponding to the current environment light source, so that the current shot image is subjected to white balance processing through the AWB parameter. The embodiment of the invention discloses a terminal and a computer readable storage medium, which can improve the accuracy of AWB, automatically perform white balance processing on an image and improve the picture presentation effect of image processing.

Description

White balance processing method, terminal and computer readable storage medium
Technical Field
The present invention relates to image processing technology in the field of information processing, and in particular, to a white balance processing method, a terminal, and a computer-readable storage medium.
Background
With the continuous development of electronic technology, the development of terminals with shooting functions, especially camera devices, is also a leap forward, so that the requirements of users on the image quality (e.g., color fidelity) of the camera devices are higher and higher.
In the prior art, when Automatic White Balance (AWB) processing is performed, the range of each reference point is calculated too roughly, only bisection division is taken to count the number of the drop points, and many critical point judgments may have errors, thereby affecting final AWB judgment.
Disclosure of Invention
In order to solve the above technical problem, embodiments of the present invention provide a white balance processing method, a terminal, and a computer-readable storage medium, which improve accuracy of AWB, can automatically perform white balance processing on an image, and improve a picture presentation effect of image processing.
The technical scheme of the invention is realized as follows:
in a first aspect, an embodiment of the present invention provides a white balance processing method, where the method includes:
determining a weight group corresponding to the current ambient light source according to the exposure index value of the shooting environment and a pre-stored weight table; the pre-stored weight table comprises: presetting a corresponding relation between the exposure index value and the preset weight set;
and determining the automatic white balance AWB parameters of the current frame image according to all statistic points of the current frame image and the weight group corresponding to the current environment light source, so that the current shot image is subjected to white balance processing through the AWB parameters of the current frame image.
Further, the determining a weight group corresponding to the current ambient light source according to the exposure index value of the shooting environment and a pre-stored weight table includes:
searching a preset exposure index value with the same exposure index value of the shooting environment in the pre-stored weight table;
if the pre-stored weight table does not have a preset exposure index value which is the same as the exposure index value of the shooting environment, performing interpolation calculation on a first preset weight group corresponding to a first preset exposure index value and a second preset weight group corresponding to a second preset exposure index value in the pre-stored weight table to obtain a weight group corresponding to the current ambient light source;
wherein the first and second preset exposure index values are: and two preset exposure index values with the minimum difference value with the exposure index value of the shooting environment in the pre-stored weight table, wherein the exposure index value of the shooting environment is greater than the first preset exposure index value, and the exposure index value of the shooting environment is smaller than the second preset exposure index value.
Further, the determining the automatic white balance AWB parameter of the current frame image according to all the statistic points of the current frame image and the weight group corresponding to the current ambient light source includes:
acquiring all statistical points of a current frame image, carrying out position distribution on all statistical points in an R/G, B/G coordinate system, and calculating the number of statistical points falling into each segmentation range of each light source reference point, wherein each segment of each light source reference point comprises a plurality of segments;
and determining the AWB parameters of the current frame image according to the number of the statistical points in each segmentation range and the weight group corresponding to the current environment light source.
Further, after determining the automatic white balance AWB parameter of the current frame image according to all the statistic points of the current frame image and the weight group corresponding to the current ambient light source, the method includes:
acquiring the AWB parameters of k frames of images before the current frame of image, and performing weighting processing on the AWB parameters of the k frames and the AWB parameters of the current frame of image to obtain processed AWB parameters, so that white balance processing is performed on the current shot image through the processed AWB parameters.
Further, after determining the automatic white balance AWB parameter of the current frame image according to all the statistic points of the current frame image and the weight group corresponding to the current ambient light source, the method includes:
and storing the AWB parameter of the current frame image and the weight group corresponding to the current environment light source.
In a second aspect, an embodiment of the present invention also provides a terminal, where the terminal includes: a processor, a memory, and a communication bus;
the communication bus is used for realizing connection communication between the processor and the memory;
the processor is used for executing the white balance processing program stored in the memory to realize the following steps:
determining a weight group corresponding to the current ambient light source according to the exposure index value of the shooting environment and a pre-stored weight table; the pre-stored weight table comprises: presetting a corresponding relation between the exposure index value and the preset weight set;
and determining the automatic white balance AWB parameters of the current frame image according to all statistic points of the current frame image and the weight group corresponding to the current environment light source, so that the current shot image is subjected to white balance processing through the AWB parameters of the current frame image.
Further, the processor is configured to execute a white balance processing program stored in the memory to implement the steps of:
searching a preset exposure index value with the same exposure index value of the shooting environment in the pre-stored weight table;
if the pre-stored weight table does not have a preset exposure index value which is the same as the exposure index value of the shooting environment, performing interpolation calculation on a first preset weight group corresponding to a first preset exposure index value and a second preset weight group corresponding to a second preset exposure index value in the pre-stored weight table to obtain a weight group corresponding to the current ambient light source;
wherein the first and second preset exposure index values are: and two preset exposure index values with the minimum difference value with the exposure index value of the shooting environment in the pre-stored weight table, wherein the exposure index value of the shooting environment is greater than the first preset exposure index value, and the exposure index value of the shooting environment is smaller than the second preset exposure index value.
Further, the processor is configured to execute a white balance processing program stored in the memory to implement the steps of:
acquiring all statistical points of a current frame image, carrying out position distribution on all statistical points in an R/G, B/G coordinate system, and calculating the number of statistical points falling into each segmentation range of each light source reference point, wherein each segment of each light source reference point comprises a plurality of segments;
and determining the AWB parameters of the current frame image according to the number of the statistical points in each segmentation range and the weight group corresponding to the current environment light source.
Further, after determining the automatic white balance AWB parameter of the current frame image according to all the statistic points of the current frame image and the weight group corresponding to the current ambient light source, the processor is further configured to execute a white balance processing program stored in the memory to implement the following steps:
acquiring the AWB parameters of k frames of images before the current frame of image, and performing weighting processing on the AWB parameters of the k frames and the AWB parameters of the current frame of image to obtain processed AWB parameters, so that white balance processing is performed on the current shot image through the processed AWB parameters.
Further, after determining the automatic white balance AWB parameter of the current frame image according to all the statistic points of the current frame image and the weight group corresponding to the current ambient light source, the processor is further configured to execute a white balance processing program stored in the memory to implement the following steps:
and storing the AWB parameter of the current frame image and the weight group corresponding to the current environment light source.
The third aspect and the embodiments of the present invention also provide a computer-readable storage medium, which stores one or more programs that can be executed by one or more processors to implement the steps of the method as described in any one of the above.
The embodiment of the invention provides a white balance processing method, a terminal and a computer readable storage medium, wherein a weight group corresponding to a current ambient light source is determined according to an exposure index value of a shooting environment and a pre-stored weight table; the pre-stored weight table comprises: presetting a corresponding relation between the exposure index value and the preset weight set; and determining the automatic white balance AWB parameters of the current frame image according to all statistic points of the current frame image and the weight group corresponding to the current environment light source, so that the current shot image is subjected to white balance processing through the AWB parameters of the current frame image. According to the white balance processing method, the terminal and the computer readable storage medium provided by the embodiment of the invention, the weight group corresponding to the current ambient light source is determined according to the pre-stored weight table, so that the AWB parameter is determined, the accuracy of the AWB is improved, the white balance processing on the image can be automatically realized, and the image presentation effect of the image processing is improved.
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Fig. 1 is a schematic hardware configuration diagram of an alternative mobile terminal implementing various embodiments of the present invention;
FIG. 2 is a diagram of a wireless communication system for the mobile terminal shown in FIG. 1;
fig. 3 is a first flowchart of a white balance processing method according to an embodiment of the present invention;
FIG. 4 is a diagram illustrating a position distribution of statistic points in an R/G, B/G coordinate system according to an embodiment of the present invention;
FIG. 5 is a diagram illustrating an example of a segment-by-segment refinement of fiducial points provided by an embodiment of the present invention;
FIG. 6 is an example graph of weight representations for 31 points per group for N groups according to an embodiment of the present invention;
fig. 7 is a schematic flow chart of a white balance processing method according to an embodiment of the present invention;
fig. 8 is a schematic structural diagram of a terminal according to an embodiment of the present invention.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In the following description, suffixes such as "module", "component", or "unit" used to denote elements are used only for facilitating the explanation of the present invention, and have no specific meaning in itself. Thus, "module", "component" or "unit" may be used mixedly.
The terminal may be implemented in various forms. For example, the terminal described in the present invention may include a mobile terminal such as a mobile phone, a tablet computer, a notebook computer, a palmtop computer, a Personal Digital Assistant (PDA), a Portable Media Player (PMP), a navigation device, a wearable device, a smart band, a pedometer, and the like, and a fixed terminal such as a Digital TV, a desktop computer, and the like.
The following description will be given by way of example of a mobile terminal, and it will be understood by those skilled in the art that the construction according to the embodiment of the present invention can be applied to a fixed type terminal, in addition to elements particularly used for mobile purposes.
Referring to fig. 1, which is a schematic diagram of a hardware structure of a mobile terminal for implementing various embodiments of the present invention, the mobile terminal 100 may include: RF (Radio Frequency) unit 101, WiFi module 102, audio output unit 103, a/V (audio/video) input unit 104, sensor 105, display unit 106, user input unit 107, interface unit 108, memory 109, processor 110, and power supply 111. Those skilled in the art will appreciate that the mobile terminal architecture shown in fig. 1 is not intended to be limiting of mobile terminals, which may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.
The following describes each component of the mobile terminal in detail with reference to fig. 1:
the Radio Frequency unit 101 may be configured to receive and transmit signals during a message transmission or call, specifically, receive downlink information of a base station and then process the received downlink information to the processor 110, and transmit uplink data to the base station, in General, the Radio Frequency unit 101 includes, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier, a duplexer, and the like, and in addition, the Radio Frequency unit 101 may further communicate with a network and other devices through wireless communication, and the wireless communication may use any communication standard or protocol, including, but not limited to, GSM (Global System of Mobile communication), GPRS (General Packet Radio Service), CDMA2000(Code Division Multiple Access 2000), WCDMA (Wideband Code Division Multiple Access ), TD-SCDMA (Synchronous Time Division Multiple Access, Code Division Multiple Access, Time Division Multiple Access, etc., TDD — Time Division Multiple Access, L Time Division Multiple Access, etc.
WiFi belongs to short-distance wireless transmission technology, and the mobile terminal can help a user to receive and send e-mails, browse webpages, access streaming media and the like through the WiFi module 102, and provides wireless broadband internet access for the user. Although fig. 1 shows the WiFi module 102, it is understood that it does not belong to the essential constitution of the mobile terminal, and may be omitted entirely as needed within the scope not changing the essence of the invention.
The audio output unit 103 may convert audio data received by the radio frequency unit 101 or the WiFi module 102 or stored in the memory 109 into an audio signal and output as sound when the mobile terminal 100 is in a call signal reception mode, a call mode, a recording mode, a voice recognition mode, a broadcast reception mode, or the like. Also, the audio output unit 103 may also provide audio output related to a specific function performed by the mobile terminal 100 (e.g., a call signal reception sound, a message reception sound, etc.). The audio output unit 103 may include a speaker, a buzzer, and the like.
The a/V input unit 104 is used to receive audio or video signals. The a/V input Unit 104 may include a Graphics Processing Unit (GPU) 1041 and a microphone 1042, the Graphics processor 1041 Processing image data of still pictures or video obtained by an image capturing device (e.g., a camera) in a video capturing mode or an image capturing mode. The processed image frames may be displayed on the display unit 106. The image frames processed by the graphic processor 1041 may be stored in the memory 109 (or other storage medium) or transmitted via the radio frequency unit 101 or the WiFi module 102. The microphone 1042 may receive sounds (audio data) via the microphone 1042 in a phone call mode, a recording mode, a voice recognition mode, or the like, and may be capable of processing such sounds into audio data. The processed audio (voice) data may be converted into a format output transmittable to a mobile communication base station via the radio frequency unit 101 in case of a phone call mode. The microphone 1042 may implement various types of noise cancellation (or suppression) algorithms to cancel (or suppress) noise or interference generated in the course of receiving and transmitting audio signals.
The mobile terminal 100 also includes at least one sensor 105, such as a light sensor, a motion sensor, and other sensors. Specifically, the light sensor includes an ambient light sensor that can adjust the brightness of the display panel 1061 according to the brightness of ambient light, and a proximity sensor that can turn off the display panel 1061 and/or a backlight when the mobile terminal 100 is moved to the ear. As one of the motion sensors, the accelerometer sensor can detect the magnitude of acceleration in each direction (generally, three axes), can detect the magnitude and direction of gravity when stationary, and can be used for applications of recognizing the posture of a mobile phone (such as horizontal and vertical screen switching, related games, magnetometer posture calibration), vibration recognition related functions (such as pedometer and tapping), and the like; as for other sensors such as a fingerprint sensor, a pressure sensor, an iris sensor, a molecular sensor, a gyroscope, a barometer, a hygrometer, a thermometer, and an infrared sensor, which can be configured on the mobile phone, further description is omitted here.
The Display unit 106 may include a Display panel 1061, and the Display panel 1061 may be configured in the form of a liquid Crystal Display (L acquired Crystal Display, L CD), an Organic light-Emitting Diode (O L ED), or the like.
The user input unit 107 may be used to receive input numeric or character information and generate key signal inputs related to user settings and function control of the mobile terminal. Specifically, the user input unit 107 may include a touch panel 1071 and other input devices 1072. The touch panel 1071, also referred to as a touch screen, may collect a touch operation performed by a user on or near the touch panel 1071 (e.g., an operation performed by the user on or near the touch panel 1071 using a finger, a stylus, or any other suitable object or accessory), and drive a corresponding connection device according to a predetermined program. The touch panel 1071 may include two parts of a touch detection device and a touch controller. The touch detection device detects the touch direction of a user, detects a signal brought by touch operation and transmits the signal to the touch controller; the touch controller receives touch information from the touch sensing device, converts the touch information into touch point coordinates, sends the touch point coordinates to the processor 110, and can receive and execute commands sent by the processor 110. In addition, the touch panel 1071 may be implemented in various types, such as a resistive type, a capacitive type, an infrared ray, and a surface acoustic wave. In addition to the touch panel 1071, the user input unit 107 may include other input devices 1072. In particular, other input devices 1072 may include, but are not limited to, one or more of a physical keyboard, function keys (e.g., volume control keys, switch keys, etc.), a trackball, a mouse, a joystick, and the like, and are not limited to these specific examples.
Further, the touch panel 1071 may cover the display panel 1061, and when the touch panel 1071 detects a touch operation thereon or nearby, the touch panel 1071 transmits the touch operation to the processor 110 to determine the type of the touch event, and then the processor 110 provides a corresponding visual output on the display panel 1061 according to the type of the touch event. Although the touch panel 1071 and the display panel 1061 are shown in fig. 1 as two separate components to implement the input and output functions of the mobile terminal, in some embodiments, the touch panel 1071 and the display panel 1061 may be integrated to implement the input and output functions of the mobile terminal, and is not limited herein.
The interface unit 108 serves as an interface through which at least one external device is connected to the mobile terminal 100. For example, the external device may include a wired or wireless headset port, an external power supply (or battery charger) port, a wired or wireless data port, a memory card port, a port for connecting a device having an identification module, an audio input/output (I/O) port, a video I/O port, an earphone port, and the like. The interface unit 108 may be used to receive input (e.g., data information, power, etc.) from external devices and transmit the received input to one or more elements within the mobile terminal 100 or may be used to transmit data between the mobile terminal 100 and external devices.
The memory 109 may be used to store software programs as well as various data. The memory 109 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone, and the like. Further, the memory 109 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device.
The processor 110 is a control center of the mobile terminal, connects various parts of the entire mobile terminal using various interfaces and lines, and performs various functions of the mobile terminal and processes data by operating or executing software programs and/or modules stored in the memory 109 and calling data stored in the memory 109, thereby performing overall monitoring of the mobile terminal. Processor 110 may include one or more processing units; preferably, the processor 110 may integrate an application processor, which mainly handles operating systems, user interfaces, application programs, etc., and a modem processor, which mainly handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 110.
The mobile terminal 100 may further include a power supply 111 (e.g., a battery) for supplying power to various components, and preferably, the power supply 111 may be logically connected to the processor 110 via a power management system, so as to manage charging, discharging, and power consumption management functions via the power management system.
Although not shown in fig. 1, the mobile terminal 100 may further include a bluetooth module or the like, which is not described in detail herein.
In order to facilitate understanding of the embodiments of the present invention, a communication network system on which the mobile terminal of the present invention is based is described below.
Referring to fig. 2, fig. 2 is an architecture diagram of a communication Network system according to an embodiment of the present invention, the communication Network system is L TE system of universal mobile telecommunications technology, and the L TE system includes a UE (User Equipment) 201, an E-UTRAN (Evolved UMTS Terrestrial Radio Access Network) 202, an EPC (Evolved Packet Core) 203, and an IP service 204 of an operator, which are in communication connection in sequence.
Specifically, the UE201 may be the terminal 100 described above, and is not described herein again.
The E-UTRAN202 includes eNodeB2021 and other eNodeBs 2022, among others. Among them, the eNodeB2021 may be connected with other eNodeB2022 through backhaul (e.g., X2 interface), the eNodeB2021 is connected to the EPC203, and the eNodeB2021 may provide the UE201 access to the EPC 203.
The EPC203 may include an MME (Mobility Management Entity) 2031, an HSS (Home Subscriber Server) 2032, other MMEs 2033, an SGW (Serving GateWay) 2034, a PGW (PDN GateWay) 2035, and a PCRF (Policy and charging rules Function) 2036, and the like. The MME2031 is a control node that handles signaling between the UE201 and the EPC203, and provides bearer and connection management. HSS2032 is used to provide registers to manage functions such as home location register (not shown) and holds subscriber specific information about service characteristics, data rates, etc. All user data may be sent through SGW2034, PGW2035 may provide IP address assignment for UE201 and other functions, and PCRF2036 is a policy and charging control policy decision point for traffic data flow and IP bearer resources, which selects and provides available policy and charging control decisions for a policy and charging enforcement function (not shown).
The IP services 204 may include the internet, intranets, IMS (IP Multimedia Subsystem), or other IP services, among others.
Although L TE system is described as an example, it should be understood by those skilled in the art that the present invention is not limited to L TE system, but also applicable to other wireless communication systems, such as GSM, CDMA2000, WCDMA, TD-SCDMA, and future new network systems.
Based on the above mobile terminal hardware structure and communication network system, the present invention provides various embodiments of the method.
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 are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order.
The embodiment of the invention provides a white balance processing method, which is applied to a terminal, wherein the functions realized by the method can be realized by calling a program code through a processor in the terminal, and the program code can be saved in a computer storage medium. Fig. 3 is a schematic flow chart of an implementation of a white balance processing method according to an embodiment of the present invention, and as shown in fig. 3, the method may include the following steps:
step 301, determining a weight group corresponding to the current ambient light source according to the exposure index value of the shooting environment and a pre-stored weight table.
Wherein the pre-stored weight table comprises: and presetting the corresponding relation between the exposure index value and the weight.
Specifically, in the embodiment of the present invention, determining the weight group corresponding to the current ambient light source according to the exposure index value of the shooting environment and the pre-stored weight table may be performed by the terminal, that is, the terminal determines the weight group corresponding to the current ambient light source according to the exposure index value of the shooting environment and the pre-stored weight table. Here, the terminal may be a terminal device having a photographing function, for example, a mobile phone, a tablet computer, or the like.
Specifically, when a user wants to take a picture through a mobile phone, the user operates the mobile phone to open a camera application on the mobile phone, for example, the mobile phone, and after a camera on the mobile phone is opened, the exposure index value of the current shooting environment is obtained, where the exposure index value is used to indicate the brightness of the current shooting environment, and a weight group corresponding to the exposure index value of the current shooting environment is searched in a pre-stored weight table according to the exposure index value of the current shooting environment. The terminal stores a weight table in advance, the pre-stored weight table stores the corresponding relationship between different preset exposure index values and different preset weight sets, and the specific pre-stored weight table is obtained as follows.
In the existing scheme, a terminal counts all statistical points of a current scene, then calculates the number N and the center point P of the statistical points falling into the range of each light source reference point according to the position distribution of the statistical points in an R/G, B/G coordinate system, calculates the number weight W of each reference point according to the N in each reference point, and combines each W and P to calculate the final weighted distribution center point position as a current AWB decision point.
The statistical point of the pure gray object under the current light source is the reference point of the current light source, as shown in fig. 4, the above process is described by taking fig. 4 as an example, in the figure, the large dots are red dots, and the red dots are the reference points of the light sources (there are 9 reference points in the figure); a blue area (an area formed by a small square), a yellow area (an area formed by a large square) and a red area (an area formed by a small circle) are statistical points acquired by the current camera; the yellow dots are the final AWB assumed points combining the weight of each light source and the position information of the statistical point.
However, the method in the prior art has certain disadvantages that the number of the falling points is only considered, the weight of the number of the falling points is calculated, namely, the more the statistical points falling around the reference points are, the larger the influence of the reference points on the final awb points is, the reference points are not set with weights, when the scene is very bright, the outdoor scene is very likely, the reference of the statistical points falling into the day region (D75/D65/D50/NOON) is higher, the weight should be larger, the reference of other falling points is not large, when the scene is general brightness or low brightness, the indoor or dark environment is very likely, the statistical points falling into the inoor A/H region (T L84/CW) are higher, the weight should be larger, the reference of other falling points is not large, and the calculation of the range of each reference point is too rough, the division is only the dichotomy method to count the number of the falling points, many critical point judgments may have errors, and further influence the final judgment.
In order to improve the accuracy of the AWB of the existing method, the method provided by the embodiment of the present invention sets N weight sets in advance according to the index values ae index of different exposure values, wherein the index values of the exposure values can judge the current luminance environment, distinguish outdoor shading outdoor _ shade, indoor index, dark color dark, and the like, and the brighter environment index value is smaller, and the darker index value is larger. Then, according to the distribution of the reference point positions of the light sources, each segment is further subdivided into 4 segments, and 31 segment points in total are obtained, as shown in fig. 5, the light source weight W1 (ranging from 0 to 10) is set for each segment, and at this time, a weight table of N groups of 31 points each can be obtained, as shown in fig. 6.
Step 302, determining an Automatic White Balance (AWB) parameter of the current frame image according to all statistic points of the current frame image and the weight group corresponding to the current environment light source, so that the current shot image is subjected to white balance processing through the AWB parameter of the current frame image.
Specifically, when the AWB is calculated, the terminal may interpolate a group of weight tables from the N groups of weight table sets according to the environment index, then calculate a final AWB result, that is, an AWB parameter, by combining the weight tables and the distribution of the drop points in each segment, and perform white balance processing on the current captured image by using the AWB parameter.
Among them, white balance is an extremely important concept of image processing. White Balance is the reduction of White objects. The object is illuminated under different light sources, the presented color is different, which is determined by the color temperature of the light source, and the reflected spectrum of the object has certain deviation from the true color, wherein, the white object changes most obviously, under the illumination of low color temperature such as indoor tungsten filament lamp light, the white object looks with orange color tone, the object shot under the illumination condition is yellow, but under the illumination of high color temperature such as sky blue, the object has blue color tone. The purpose of automatic white balance AWB is to eliminate color deviations caused by different light sources, so that the shot picture conforms to the habit of human eyes as much as possible.
According to the white balance processing method provided by the embodiment of the invention, the weight group corresponding to the current ambient light source is determined according to the pre-stored weight table, so that the AWB parameter is determined, the accuracy of the AWB is improved, the white balance processing on the image can be automatically realized, and the image presentation effect of the image processing is improved.
The embodiment of the invention provides a white balance processing method, which is applied to a terminal, wherein the functions realized by the method can be realized by calling a program code through a processor in the terminal, and the program code can be saved in a computer storage medium. Fig. 7 is a schematic flow chart of an implementation of a white balance processing method according to an embodiment of the present invention, and as shown in fig. 7, the method may include the following steps:
step 401, obtaining an exposure index value of the current shooting environment.
Wherein the exposure index value is used for representing the brightness of the current shooting environment.
Specifically, the terminal obtains an exposure index value of the current shooting environment, the exposure index value can judge the current brightness environment, and the brighter environment index value is smaller, and the darker index value is larger.
Step 402, searching a pre-stored weight table for a pre-set exposure index value having the same exposure index value of the shooting environment, and if the pre-stored weight table does not have the pre-set exposure index value having the same exposure index value of the shooting environment, performing interpolation calculation on a first pre-set weight group corresponding to the first pre-set exposure index value and a second pre-set weight group corresponding to the second pre-set exposure index value in the pre-stored weight table to obtain a weight group corresponding to the current ambient light source.
Wherein the first and second preset exposure index values are: and two preset exposure index values with the minimum difference value with the exposure index value of the shooting environment in the pre-stored weight table, wherein the exposure index value of the shooting environment is greater than the first preset exposure index value, and the exposure index value of the shooting environment is smaller than the second preset exposure index value.
Specifically, the terminal searches a pre-stored weight table for a preset exposure index value with the same exposure index value of the shooting environment, and if the pre-stored weight table finds a preset exposure index value with the same exposure index value of the shooting environment, the preset weight corresponding to the preset exposure index value is recombined into the weight group corresponding to the current ambient light source.
The interpolation method is also called "interpolation method", and is a method of making an appropriate specific function by using function values of a plurality of points known in a certain interval of the function f (x), and using values of the specific function as approximate values of the function f (x) at other points in the interval, and is called "interpolation method". I.e. in known function tables, intermediate values are inserted which are not listed in some tables and which are required.
For example, if the exposure index value of the shooting environment is 100, it can be found from the table shown in fig. 6 that the two preset exposure index values having the smallest difference from the exposure index value 100 of the shooting environment are 95 and 143, i.e., the first preset exposure index value is 95, the second preset exposure index value 143, the first preset weight set {1, 1, 1, 5, 5, 5, 5, 5, 5, 5, 5, 5, 3, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, performing interpolation calculation according to the first preset weight group and the second preset weight group to obtain a weight group corresponding to the exposure index value of the shooting environment of 100, where a specific interpolation calculation process may be implemented by an existing algorithm, and details are not repeated herein in the embodiments of the present invention.
And 403, acquiring all statistical points of the current frame image, performing position distribution on all statistical points in an R/G, B/G coordinate system, calculating the number of the statistical points falling into each segmentation range of each light source reference point, and determining the AWB parameter of the current frame image according to the number of the statistical points in each segmentation range and the weight group corresponding to the current environment light source.
Specifically, thinning segmentation is performed between each segment of each light source reference point in advance, and therefore, each segment of each light source reference point includes a plurality of segments. For example, as shown in fig. 5, each segment of the light source is further subdivided into 4 segments according to the distribution of the positions of the reference points of the light source, and the total number of the segment points is 31.
Specifically, when the AWB is calculated, the terminal may interpolate a group of weight tables from the N groups of weight table sets according to the environment index, then calculate a final AWB result, that is, an AWB parameter, by combining the weight tables and the distribution of the drop points in each segment, and perform white balance processing on the current captured image by using the AWB parameter.
Further, after determining the automatic white balance AWB parameter of the current frame image according to all the statistic points of the current frame image and the weight group corresponding to the current ambient light source, the method includes:
and storing the AWB parameter of the current frame image and the weight group corresponding to the current environment light source.
Further, after determining the automatic white balance AWB parameter of the current frame image according to all the statistic points of the current frame image and the weight group corresponding to the current ambient light source, the method includes:
acquiring the AWB parameters of k frames of images before the current frame of image, and performing weighting processing on the AWB parameters of the k frames and the AWB parameters of the current frame of image to obtain processed AWB parameters, so that white balance processing is performed on the current shot image through the processed AWB parameters.
Specifically, a history information queue may be set during shooting, the AWB result of the previous K frames may be stored, the weight of the AWB result may be set to W2, and weighting processing may be performed with the current AWB result, so that the output result of the current AWB may be smoothed, and transition of the AWB result may be prevented.
According to the white balance processing method provided by the embodiment of the invention, the weight group corresponding to the current ambient light source is determined according to the pre-stored weight table, so that the AWB parameter is determined, the accuracy of the AWB is improved, the white balance processing on the image can be automatically realized, and the image presentation effect of the image processing is improved.
An embodiment of the present invention also provides a terminal 50, as shown in fig. 8, where the terminal 50 includes: a processor 501, a memory 502, and a communication bus 503;
the communication bus 503 is used for realizing connection communication between the processor 501 and the memory 502;
the processor 501 is configured to execute the white balance processing program stored in the memory 502 to implement the following steps:
determining a weight group corresponding to the current ambient light source according to the exposure index value of the shooting environment and a pre-stored weight table; the pre-stored weight table comprises: presetting a corresponding relation between the exposure index value and the preset weight set;
and determining the automatic white balance AWB parameters of the current frame image according to all statistic points of the current frame image and the weight group corresponding to the current environment light source, so that the current shot image is subjected to white balance processing through the AWB parameters of the current frame image.
Further, the processor 501 is configured to execute the white balance processing program stored in the memory 502 to implement the following steps:
searching a preset exposure index value with the same exposure index value of the shooting environment in the pre-stored weight table;
if the pre-stored weight table does not have a preset exposure index value which is the same as the exposure index value of the shooting environment, performing interpolation calculation on a first preset weight group corresponding to a first preset exposure index value and a second preset weight group corresponding to a second preset exposure index value in the pre-stored weight table to obtain a weight group corresponding to the current ambient light source;
wherein the first and second preset exposure index values are: and two preset exposure index values with the minimum difference value with the exposure index value of the shooting environment in the pre-stored weight table, wherein the exposure index value of the shooting environment is greater than the first preset exposure index value, and the exposure index value of the shooting environment is smaller than the second preset exposure index value.
Further, the processor 501 is configured to execute the white balance processing program stored in the memory 502 to implement the following steps:
acquiring all statistical points of a current frame image, carrying out position distribution on all statistical points in an R/G, B/G coordinate system, and calculating the number of statistical points falling into each segmentation range of each light source reference point, wherein each segment of each light source reference point comprises a plurality of segments;
and determining the AWB parameters of the current frame image according to the number of the statistical points in each segmentation range and the weight group corresponding to the current environment light source.
Further, after determining the automatic white balance AWB parameter of the current frame image according to all the statistic points of the current frame image and the weight set corresponding to the current ambient light source, the processor 501 is further configured to execute a white balance processing program stored in the memory 502 to implement the following steps:
acquiring the AWB parameters of k frames of images before the current frame of image, and performing weighting processing on the AWB parameters of the k frames and the AWB parameters of the current frame of image to obtain processed AWB parameters, so that white balance processing is performed on the current shot image through the processed AWB parameters.
Further, after determining the automatic white balance AWB parameter of the current frame image according to all the statistic points of the current frame image and the weight set corresponding to the current ambient light source, the processor 501 is further configured to execute a white balance processing program stored in the memory 502 to implement the following steps:
and storing the AWB parameter of the current frame image and the weight group corresponding to the current environment light source.
Here, the Memory 502 may be a volatile Memory or a non-volatile Memory, and may also include both volatile and non-volatile memories, wherein the non-volatile Memory may be a Read Only Memory (ROM), a Programmable Read Only Memory (PROM), an Erasable Programmable Read Only Memory (EPROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a magnetic Random Access Memory (FRAM), a magnetic Random Access Memory (Flash Memory), a magnetic surface Memory, an optical Disc, or a Compact Disc Read Only Memory (CD-ROM), a Compact Disc Read-Only Memory (magnetic Random Access Memory), a magnetic surface Memory (magnetic Random Access Memory) may be a magnetic disk Memory or a magnetic tape Memory, and may be a Random Access Memory (DRAM), or may be a Dynamic Random Access Memory (DRAM), and may be any other Random Access Memory (Dynamic Random Access Memory) including a Dynamic Random Access Memory (SDRAM) or a Dynamic Random Access Memory (Dynamic Random Access Memory) used as an external Access Memory (SDRAM), or may be a Dynamic Random Access Memory (Dynamic Random Access Memory) used as an Access Memory, such as an Access RAM (DRAM), or may be a Dynamic Random Access Memory (Dynamic Access RAM) used as an Access RAM (Dynamic Access RAM) for example, a Dynamic Access RAM (Dynamic Access RAM) suitable for a Dynamic Access RAM, a Dynamic Access RAM (Dynamic Access RAM) used as an Access RAM, a Dynamic Access RAM (Dynamic Access RAM, a Dynamic Access RAM, and a Dynamic Access RAM (RAM) used as an Access RAM, a Dynamic Access RAM, and a.
The memory 502 in embodiments of the present invention is used to store various types of data to support the operation of the terminal 50. Examples of such data include: any computer program for operating on the terminal 50, such as an operating system and application programs; contact data; telephone book data; a message; a picture; video, etc. The operating system includes various system programs, such as a framework layer, a core library layer, a driver layer, and the like, and is used for implementing various basic services and processing hardware-based tasks. The application programs may include various application programs such as a Media Player (Media Player), a Browser (Browser), etc. for implementing various application services. The program for implementing the method of the embodiment of the present invention may be included in the application program.
The method disclosed by the above-mentioned embodiments of the present invention may be applied to the processor 501, or implemented by the processor 501. The processor 501 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware or instructions in the form of software in the processor 501. The Processor 501 may be a general purpose Processor, a Digital Signal Processor (DSP), or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, etc. Processor 501 may implement or perform the methods, steps, and logic blocks disclosed in embodiments of the present invention. A general purpose processor may be a microprocessor or any conventional processor or the like. The steps of the method disclosed by the embodiment of the invention can be directly implemented by a hardware decoding processor, or can be implemented by combining hardware and software modules in the decoding processor. The software modules may be located in a storage medium located in the memory 502, and the processor 501 reads the information in the memory 502 and performs the steps of the aforementioned methods in conjunction with its hardware.
Specifically, for understanding of the terminal provided in the embodiment of the present invention, reference may be made to the description of the foregoing white balance processing method embodiment, and details of the embodiment of the present invention are not described herein again.
The terminal provided by the embodiment of the invention determines the weight group corresponding to the current ambient light source according to the pre-stored weight table, thereby determining the AWB parameter, improving the accuracy of the AWB, realizing automatic white balance processing on the image and improving the picture presentation effect of the image processing.
In the embodiment of the present invention, if the white balance processing method is implemented in the form of a software functional module and sold or used as an independent product, the white balance processing method may also be stored in a computer-readable storage medium. Based on such understanding, the technical solutions of the embodiments of the present invention may be essentially implemented or a part contributing to the prior art may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read Only Memory (ROM), a magnetic disk, or an optical disk. Thus, embodiments of the invention are not limited to any specific combination of hardware and software.
An embodiment of the present invention provides a computer-readable storage medium storing one or more programs, the one or more programs being executable by one or more processors to implement the steps of:
determining a weight group corresponding to the current ambient light source according to the exposure index value of the shooting environment and a pre-stored weight table; the pre-stored weight table comprises: presetting a corresponding relation between the exposure index value and the preset weight set;
and determining the automatic white balance AWB parameters of the current frame image according to all statistic points of the current frame image and the weight group corresponding to the current environment light source, so that the current shot image is subjected to white balance processing through the AWB parameters of the current frame image.
The above description of the computer-readable storage medium embodiments, similar to the above description of the method, has the same beneficial effects as the method embodiments. For technical details not disclosed in the embodiments of the computer-readable storage medium of the present invention, a person skilled in the art shall understand with reference to the description of the embodiments of the method of the present invention.
It should be appreciated that reference throughout this specification to "one embodiment" or "an embodiment" means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, the appearances of the phrases "in one embodiment" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. It should be understood that, in various embodiments of the present invention, the sequence numbers of the above-mentioned processes do not mean the execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention. The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described device embodiments are merely illustrative, for example, the division of the unit is only a logical functional division, and there may be other division ways in actual implementation, such as: multiple units or components may be combined, or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the coupling, direct coupling or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between the devices or units may be electrical, mechanical or other forms.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units; can be located in one place or distributed on a plurality of network units; some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, all the functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately regarded as one unit, or two or more units may be integrated into one unit; the integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
Those of ordinary skill in the art will understand that: all or part of the steps for realizing the method embodiments can be completed by hardware related to program instructions, the program can be stored in a computer readable storage medium, and the program executes the steps comprising the method embodiments when executed; and the aforementioned storage medium includes: various media that can store program codes, such as a removable Memory device, a Read Only Memory (ROM), a magnetic disk, or an optical disk.
Alternatively, the integrated unit of the present invention may be stored in a computer-readable storage medium if it is implemented in the form of a software functional module and sold or used as a separate product. Based on such understanding, the technical solutions of the embodiments of the present invention may be essentially implemented or a part contributing to the prior art may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, a ROM, a magnetic or optical disk, or other various media that can store program code.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.

Claims (8)

1. A white balance processing method, characterized by comprising:
determining a weight group corresponding to the current ambient light source according to the exposure index value of the shooting environment and a pre-stored weight table; the pre-stored weight table comprises: presetting a corresponding relation between the exposure index value and the preset weight set; wherein the exposure index value is used for representing the brightness of the current shooting environment;
determining automatic white balance AWB parameters of the current frame image according to all statistic points of the current frame image and the weight group corresponding to the current environment light source, so that white balance processing is performed on the current shot image through the AWB parameters of the current frame image;
the determining of the automatic white balance AWB parameter of the current frame image according to all the statistic points of the current frame image and the weight group corresponding to the current environment light source comprises the following steps:
acquiring all statistical points of a current frame image, carrying out position distribution on all statistical points in an R/G, B/G coordinate system, and calculating the number of statistical points falling into each segmentation range of each light source reference point, wherein each segment of each light source reference point comprises a plurality of segments;
and determining the AWB parameters of the current frame image according to the number of the statistical points in each segmentation range and the weight group corresponding to the current environment light source.
2. The method of claim 1, wherein determining the weight group corresponding to the current ambient light source according to the exposure index value of the shooting environment and a pre-stored weight table comprises:
searching a preset exposure index value with the same exposure index value of the shooting environment in the pre-stored weight table;
if the pre-stored weight table does not have a preset exposure index value which is the same as the exposure index value of the shooting environment, performing interpolation calculation on a first preset weight group corresponding to a first preset exposure index value and a second preset weight group corresponding to a second preset exposure index value in the pre-stored weight table to obtain a weight group corresponding to the current ambient light source;
wherein the first and second preset exposure index values are: and two preset exposure index values with the minimum difference value with the exposure index value of the shooting environment in the pre-stored weight table, wherein the exposure index value of the shooting environment is greater than the first preset exposure index value, and the exposure index value of the shooting environment is smaller than the second preset exposure index value.
3. The method according to claim 1 or 2, wherein after determining the automatic white balance AWB parameter of the current frame image according to all statistic points of the current frame image and the weight set corresponding to the current ambient light source, the method comprises:
acquiring the AWB parameters of k frames of images before the current frame of image, and performing weighting processing on the AWB parameters of the k frames and the AWB parameters of the current frame of image to obtain processed AWB parameters, so that white balance processing is performed on the current shot image through the processed AWB parameters.
4. The method according to claim 1 or 2, wherein after determining the automatic white balance AWB parameter of the current frame image according to all statistic points of the current frame image and the weight set corresponding to the current ambient light source, the method comprises:
and storing the AWB parameter of the current frame image and the weight group corresponding to the current environment light source.
5. A terminal, characterized in that the terminal comprises: a processor, a memory, and a communication bus;
the communication bus is used for realizing connection communication between the processor and the memory;
the processor is used for executing the white balance processing program stored in the memory to realize the following steps:
determining a weight group corresponding to the current ambient light source according to the exposure index value of the shooting environment and a pre-stored weight table; the pre-stored weight table comprises: presetting a corresponding relation between the exposure index value and the preset weight set; wherein the exposure index value is used for representing the brightness of the current shooting environment;
determining automatic white balance AWB parameters of the current frame image according to all statistic points of the current frame image and the weight group corresponding to the current environment light source, so that white balance processing is performed on the current shot image through the AWB parameters of the current frame image;
the processor is further configured to execute a white balance processing program stored in the memory to implement the steps of:
acquiring all statistical points of a current frame image, carrying out position distribution on all statistical points in an R/G, B/G coordinate system, and calculating the number of statistical points falling into each segmentation range of each light source reference point, wherein each segment of each light source reference point comprises a plurality of segments;
and determining the AWB parameters of the current frame image according to the number of the statistical points in each segmentation range and the weight group corresponding to the current environment light source.
6. The terminal of claim 5, wherein the processor is configured to execute a white balance processing program stored in the memory to implement the steps of:
searching a preset exposure index value with the same exposure index value of the shooting environment in the pre-stored weight table;
if the pre-stored weight table does not have a preset exposure index value which is the same as the exposure index value of the shooting environment, performing interpolation calculation on a first preset weight group corresponding to a first preset exposure index value and a second preset weight group corresponding to a second preset exposure index value in the pre-stored weight table to obtain a weight group corresponding to the current ambient light source;
wherein the first and second preset exposure index values are: and two preset exposure index values with the minimum difference value with the exposure index value of the shooting environment in the pre-stored weight table, wherein the exposure index value of the shooting environment is greater than the first preset exposure index value, and the exposure index value of the shooting environment is smaller than the second preset exposure index value.
7. The terminal according to claim 5 or 6, wherein after determining the automatic white balance AWB parameter of the current frame image according to all statistic points of the current frame image and the weight set corresponding to the current ambient light source, the processor is further configured to execute a white balance processing program stored in the memory to implement the following steps:
acquiring the AWB parameters of k frames of images before the current frame of image, and performing weighting processing on the AWB parameters of the k frames and the AWB parameters of the current frame of image to obtain processed AWB parameters, so that white balance processing is performed on the current shot image through the processed AWB parameters.
8. A computer readable storage medium, characterized in that the computer readable storage medium stores one or more programs which are executable by one or more processors to implement the steps of the method according to any one of claims 1 to 4.
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