WO2017202218A1

WO2017202218A1 - Device and method for acquiring image processing mode, and storage medium

Info

Publication number: WO2017202218A1
Application number: PCT/CN2017/084145
Authority: WO
Inventors: 李乐义
Original assignee: 努比亚技术有限公司
Priority date: 2016-05-26
Filing date: 2017-05-12
Publication date: 2017-11-30
Also published as: CN105898264A; CN105898264B

Abstract

Disclosed is a device for acquiring an image processing mode. The device comprises: a first acquisition unit, a classification unit, a second acquisition unit and a processing unit, wherein the first acquisition unit is configured to acquire images to be processed, and segmenting, according to a pre-set rule, the images to be processed, so as to obtain first images; the classification unit is configured to classify the first images based on pre-set classifications; the second acquisition unit is configured to respectively perform white balance treatment on each first image in each classification, so as to obtain second images, and acquiring white balance treatment results of the second images in each classification; and the processing unit is configured to analyse the white balance treatment results of the second images in each classification, so as to obtain a target white balance treatment mode for the images to be processed. Also disclosed is a method for acquiring an image processing mode, and a storage medium.

Description

Acquisition device and method for image processing method, storage medium

Cross-reference to related applications

The present application is based on a Chinese patent application filed on Apr. 26, 2016, the entire disclosure of which is hereby incorporated by reference.

Technical field

The present application relates to image processing technologies in the field of communications, and in particular, to an image processing method acquisition device and method, and a storage medium.

Background technique

White balance can solve a series of problems of color reproduction and tone processing. Automatic white balance is usually the default setting of digital camera. There is a complicated rectangular diagram in the camera, which can determine the white balance reference point in the picture to achieve white. Balance adjustment. The automatic white balance algorithm divides the entire picture into several blocks and then determines whether the color of each block falls within a specific range. These "specific ranges" may be referred to as white areas.

Generally, the accuracy of automatic white balance is very high, but the actual situation will affect the effect of white balance: when a large area of grass, skin, yellow, light blue wooden door, etc. is used as a reflector, the light source is reflected by these objects. Although the color can fall in the white area, but the light color of the light source cannot be correctly reflected, the result of the automatic white balance will be biased; when the large area of large red, dark blue, purple, brown, etc. is used as the reflector, the light source is reflected by these objects. The light color does not fall in the white area, and the automatic white balance cannot be calculated; more than one illuminant and different light colors, whether according to one of the illuminants as the light source or different light color interpolation, the final reflected light color whitish There are also some deviations in the balance results.

Summary of the invention

In view of this, the embodiment of the present invention is to provide an image processing method acquisition method and device, and a storage medium, which solves the problem that the automatic white balance method in the prior art processes the image of different situations, and the calculation deviation is improved. The effect of image white balance processing; at the same time, can improve the user experience.

In order to achieve the above object, the technical solution of the present application is implemented as follows:

In a first aspect, an embodiment of the present invention provides an apparatus for acquiring an image processing method, where the apparatus includes: a first acquiring unit, a classifying unit, a second acquiring unit, and a processing unit, where:

The first acquiring unit is configured to acquire an image to be processed, and divide the image to be processed according to a preset rule to obtain a first image;

The classifying unit is configured to classify the first image according to a preset classification;

The second acquiring unit is configured to perform white balance processing on each of the first images in each category to obtain a second image, and obtain a white balance processing result of the second image in each category;

The processing unit is configured to analyze a white balance processing result of the second image in each category to obtain a target white balance processing manner of the image to be processed.

Optionally, the classification unit includes: a first acquiring module and a classification module, where:

The first acquiring module is configured to acquire a color temperature of each of the first images in a preset partition;

The classifying module is configured to classify the first image according to a matching relationship between a color temperature of each of the first images in a preset partition and a color temperature of each of the preset categories.

Optionally, the first acquiring module is further configured to use, as the emitting object, the first image of each block as a range of color temperature of the standard light source reflected by each block of the first image and falling into the preset partition. The color temperature of the first image in the preset partition.

Optionally, the second obtaining unit includes: a calculating module and a second acquiring module, where:

The calculating module is configured to separately calculate the number of the first images in each category, and obtain a classification that the number of the first images is not zero;

The second obtaining module is configured to perform white balance processing on each of the first images in the category of the first image that is not zero according to a white balance processing algorithm of each category to obtain the second An image, and a white balance processing result of the second image in each category is obtained.

Optionally, the processing unit includes: a third acquiring module and a processing module, where:

The third obtaining module is configured to separately acquire image scores of the second image in each class;

The third acquiring module is further configured to compare image scores of the second image in each class, and obtain a target classification with the largest image score of the second image in the preset classification;

The processing module is configured to set a white balance algorithm corresponding to the target classification with the largest image score of the second image as the target white balance processing manner.

Optionally, the third obtaining module is further configured to:

Obtaining a brightness score of each of the second images according to a preset brightness score rule;

Obtaining a color score of each of the second images according to a preset color score rule;

And multiplying a brightness score and a color score of each of the obtained second images to obtain an image score of each of the second images;

The image scores of each of the second images in each class are added to obtain image scores for the second image in each of the classes.

Optionally, the preset classification is defined according to different conditions in which the standard light source is reflected by different reflective objects and falls in the white area.

In a second aspect, an embodiment of the present invention provides a method for acquiring an image processing method, where the method includes:

Obtaining an image to be processed, and dividing the image to be processed according to a preset rule To the first image;

Sorting and sorting the first image based on a preset classification;

Performing white balance processing on each of the first images in each category to obtain a second image, and acquiring a white balance processing result of the second image in each category;

A white balance processing result of the second image in each category is analyzed to obtain a target white balance processing manner of the image to be processed.

Optionally, the classifying, according to the preset classification, the first image, including:

Obtaining a color temperature of each of the first images in a preset partition;

And classifying the first image according to a matching relationship between a color temperature of each of the first images in a preset partition and a color temperature of each of the preset categories.

Optionally, the obtaining a color temperature of each of the first images in a preset partition includes:

Each of the first images is used as a transmitting object, and a range of color temperatures of the standard light source reflected by each of the first images and falling into a preset partition is used as a color temperature of the first image in a preset partition.

Optionally, the white balance processing is performed on each of the first images in each category to obtain a second image, and the white balance processing result of the second image in each category is obtained, including:

Calculating the number of the first images in each category separately, and obtaining a classification in which the number of the first images is not zero;

According to the white balance processing algorithm of each category, each of the first images in the category in which the number of the first images is not zero is respectively subjected to white balance processing to obtain the second image, and each category is obtained. The result of the white balance processing of the second image.

Optionally, the analyzing the white balance processing result of the second image in each category to obtain the target white balance processing manner of the image to be processed, including:

Obtaining image scores of the second image in each class separately;

Comparing image scores of the second image in each class, and acquiring a target classification with the largest image score of the second image in the preset classification;

And setting a white balance algorithm corresponding to the target classification in which the image score of the second image is the largest is the target white balance processing manner.

Optionally, the acquiring the image scores of the second image in each class separately includes:

In a third aspect, an embodiment of the present invention provides an image processing mode acquiring device, where the device includes: a memory configured with executable instructions; and a processor configured to execute the executable instructions, where the executable instructions are configured for:

Obtaining a to-be-processed image, performing the segmentation process according to a preset rule to obtain a first image; classifying and finishing the first image based on a preset classification; respectively, for each of the categories in each category Performing white balance processing on an image to obtain a second image, and acquiring a white balance processing result of the second image in each category; analyzing a white balance processing result of the second image in each category to obtain the image to be processed The target white balance processing method.

Optionally, the executable instruction is further configured to obtain a color temperature of each of the first images in a preset partition; according to a color temperature of each of the first images in a preset partition, and the preset classification The first image is sorted and sorted by a matching relationship between color temperatures of each of the categories.

Optionally, the executable instruction is further configured to separately calculate a first image in each category a number of the first image obtained by the non-zero classification; according to the white balance processing algorithm of each category, respectively performing the first image in each of the categories in which the number of the first images is not zero The white balance process obtains the second image and acquires a white balance processing result of the second image in each category.

Optionally, the executable instruction is further configured to separately obtain image scores of the second image in each class; compare image scores of the second image in each class, and obtain the pre-preparation A target classification with the largest image score of the second image in the classification is set; and a white balance algorithm corresponding to the target classification with the largest image score of the second image is set as the target white balance processing manner.

Optionally, the executable instruction is further configured to acquire a brightness score of each of the second images according to a preset brightness score rule; and acquire each of the second images according to a preset color score rule. Color scores; respectively multiplying the obtained luminance scores and color scores of each of the second images to obtain image scores for each of the second images; The image scores of the two images are added to obtain an image score of the second image in each of the classes.

In a fourth aspect, an embodiment of the present invention provides a computer storage medium, where the computer storage medium stores a computer program, and the computer program is used to execute the image processing mode acquisition method described above.

The apparatus and method for acquiring an image processing method and the storage medium provided by the embodiments of the present invention can obtain an image to be processed, and divide the image to be processed according to a preset rule to obtain a first image, and then first Sorting the image, performing white balance processing on each of the first images in each category to obtain a second image, and acquiring white balance processing results of the second image in each category; analyzing each category The white balance processing result of the second image obtains the target white balance processing mode of the image to be processed; thus, the best processing result is selected by processing the image from the image to be processed for different white balance processing modes, and the best The processing result is used as the white balance processing mode of the image to be processed, and the automatic method in the prior art is solved. When the white balance method processes images of different situations, there is a problem of calculation deviation, which improves the processing effect of image white balance; at the same time, it lays a foundation for improving the user experience.

DRAWINGS

1 is a schematic structural diagram of hardware of an optional mobile terminal embodying various embodiments of the present invention;

2 is a schematic structural diagram of a communication system that can be operated by a mobile terminal according to an embodiment of the present invention;

FIG. 3 is a schematic flowchart of a method for acquiring an image processing method according to an embodiment of the present disclosure;

FIG. 4 is a schematic flowchart diagram of another method for acquiring an image processing manner according to an embodiment of the present disclosure;

FIG. 5 is a schematic flowchart diagram of still another method for acquiring an image processing method according to an embodiment of the present disclosure;

6 is a diagram showing an example of luminance scores of each second image in each category according to an embodiment of the present invention;

FIG. 7 is a diagram showing an example of color scores of each second image in each category according to an embodiment of the present invention; FIG.

8 is a diagram showing an example of image scores of a second image of each category according to an embodiment of the present invention;

FIG. 9 is a schematic structural diagram of an apparatus for acquiring an image processing method according to an embodiment of the present disclosure;

FIG. 10 is a schematic structural diagram of another apparatus for acquiring an image processing method according to an embodiment of the present disclosure;

FIG. 11 is a schematic structural diagram of another apparatus for acquiring an image processing method according to an embodiment of the present disclosure;

FIG. 12 is a schematic diagram of an apparatus for acquiring an image processing method according to another embodiment of the present invention; schematic diagram;

FIG. 13 is a schematic structural diagram of hardware of an image processing mode acquiring device according to an embodiment of the present invention.

detailed description

The technical solutions in the embodiments of the present invention will be clearly and completely described in the following with reference to the accompanying drawings.

A mobile terminal embodying various embodiments of the present invention will now be described with reference to FIG. In the following description, the use of suffixes such as "module", "component" or "unit" for indicating an element is merely an explanation for facilitating the present invention, and does not have a specific meaning per se. Therefore, "module" and "component" can be used in combination.

The mobile terminal can be implemented in various forms. For example, the terminals described in the present invention may include, for example, mobile phones, smart phones, notebook computers, digital broadcast receivers, personal digital assistants (PDAs), tablet computers (PADs), portable multimedia players (PMPs), navigation devices, and the like. Mobile terminals and fixed terminals such as digital TVs, desktop computers, and the like. In the following, it is assumed that the terminal is a mobile terminal. However, those skilled in the art will appreciate that configurations in accordance with embodiments of the present invention can be applied to fixed type terminals in addition to components that are specifically for mobile purposes.

FIG. 1 is a schematic diagram showing the hardware structure of a mobile terminal embodying various embodiments of the present invention.

The mobile terminal 100 may include a wireless communication unit 110, an audio/video (A/V) input unit 120, a user input unit 130, a sensing unit 140, an output unit 150, a memory 160, an interface unit 170, a controller 180, and a power supply unit 190. and many more. Figure 1 shows a mobile terminal having various components, but it should be understood that not all illustrated components are required to be implemented, and more or fewer components may be implemented instead, and the components of the mobile terminal will be described in detail below. .

Wireless communication unit 110 typically includes one or more components that permit radio communication between mobile terminal 100 and a wireless communication system or network. For example, the wireless communication unit can include a wide range At least one of the broadcast receiving module 111, the mobile communication module 112, the wireless internet module 113, the short-range communication module 114, and the location information module 115.

The broadcast receiving module 111 receives a broadcast signal and/or broadcast associated information from an external broadcast management server via a broadcast channel. The broadcast channel can include a satellite channel and/or a terrestrial channel. The broadcast management server may be a server that generates and transmits a broadcast signal and/or broadcast associated information or a server that receives a previously generated broadcast signal and/or broadcast associated information and transmits it to the terminal. The broadcast signal may include a TV broadcast signal, a radio broadcast signal, a data broadcast signal, and the like. Moreover, the broadcast signal may further include a broadcast signal combined with a TV or radio broadcast signal. The broadcast associated information may also be provided via a mobile communication network, and in this case, the broadcast associated information may be received by the mobile communication module 112. The broadcast signal may exist in various forms, for example, it may exist in the form of Digital Multimedia Broadcasting (DMB) Electronic Program Guide (EPG), Digital Video Broadcasting Handheld (DVB-H) Electronic Service Guide (ESG), and the like. . The broadcast receiving module 111 can receive a signal broadcast by using various types of broadcast systems. In particular, the broadcast receiving module 111 can use forward link media (MediaFLO) by using, for example, multimedia broadcast-terrestrial (DMB-T), digital multimedia broadcast-satellite (DMB-S), digital video broadcast-handheld (DVB-H) The digital broadcasting system of the @) data broadcasting system, the terrestrial digital broadcasting integrated service (ISDB-T), and the like receives digital broadcasting. The broadcast receiving module 111 can be constructed as various broadcast systems suitable for providing broadcast signals as well as the above-described digital broadcast system. The broadcast signal and/or broadcast associated information received via the broadcast receiving module 111 may be stored in the memory 160 (or other type of storage medium).

The mobile communication module 112 transmits the radio signals to and/or receives radio signals from at least one of a base station (e.g., an access point, a Node B, etc.), an external terminal, and a server. Such radio signals may include voice call signals, video call signals, or various types of data transmitted and/or received in accordance with text and/or multimedia messages.

The wireless internet module 113 supports wireless internet access of the mobile terminal. The module can be internally or externally coupled to the terminal. The wireless internet access technology involved in the module may include WLAN (Wireless LAN) (Wi-Fi), Wibro (Wireless Broadband), Wimax (Worldwide Interoperability for Microwave Access), HSDPA (High Speed Downlink Packet Access), and the like.

The short range communication module 114 is a module for supporting short range communication. Some examples of short-range communication technologies include BluetoothTM, Radio Frequency Identification (RFID), Infrared Data Association (IrDA), Ultra Wide Band (UWB), ZigbeeTM, and the like.

The location information module 115 is a module for checking or acquiring location information of the mobile terminal. A typical example of location information module 115 is Global Positioning System (GPS) module 115. According to the current technology, the position information module 115 as a GPS calculates distance information and accurate time information from three or more satellites and applies triangulation to the calculated information to accurately calculate the three-dimensional current based on longitude, latitude, and altitude. location information. Currently, the method for calculating position and time information uses three satellites and corrects the calculated position and time information errors by using another satellite. Further, the position information module 115 as a GPS can calculate the speed information by continuously calculating the current position information in real time.

The A/V input unit 120 is for receiving an audio or video signal. The A/V input unit 120 may include a camera 121 and a microphone 122 that processes image data of still pictures or video obtained by the image capturing device in a video capturing mode or an image capturing mode. The processed image frame can be displayed on the display unit 151. The image frames processed by the camera 121 may be stored in the memory 160 (or other storage medium) or transmitted via the wireless communication unit 110, and two or more cameras 121 may be provided according to the configuration of the mobile terminal. The microphone 122 can receive sound (audio data) via the microphone 122 in an operation mode of a telephone call mode, a recording mode, a voice recognition mode, and the like, and can process such sound as audio data. The processed audio (voice) data can be converted to a format output that can be transmitted to the mobile communication base station via the mobile communication module 112 in the case of a telephone call mode. The microphone 122 can implement various types of noise cancellation (or suppression) algorithms to cancel (or suppress) noise or interference generated during the process of receiving and transmitting audio signals.

The user input unit 130 may generate key input data according to a command input by the user to control various operations of the mobile terminal. The user input unit 130 allows the user to input various types of information, and may include a keyboard, a touch pad (eg, a touch sensitive component that detects changes in resistance, pressure, capacitance, and the like due to contact), and the like. In particular, when the touch panel is superimposed on the display unit 151 in the form of a layer, a touch screen can be formed.

The sensing unit 140 detects the current state of the mobile terminal 100 (eg, the open or closed state of the mobile terminal 100), the location of the mobile terminal 100, the presence or absence of contact (ie, touch input) by the user with the mobile terminal 100, and the mobile terminal. The orientation of 100, the acceleration or deceleration movement and direction of the mobile terminal 100, and the like, and generates a command or signal for controlling the operation of the mobile terminal 100. For example, when the mobile terminal 100 is implemented as a slide type mobile phone, the sensing unit 140 can sense whether the slide type phone is turned on or off. In addition, the sensing unit 140 can detect whether the power supply unit 190 provides power or whether the interface unit 170 is coupled to an external device.

The interface unit 170 serves as an interface through which at least one external device can connect with the mobile terminal 100. For example, the external device may include a wired or wireless headset port, an external power (or battery charger) port, a wired or wireless data port, a memory card port, a port for connecting a device having an identification module, and an audio input/output. (I/O) port, video I/O port, headphone port, and more. The interface unit 170 can be configured to receive input from an external device (eg, data information, power, etc.) and transmit the received input to one or more components within the mobile terminal 100 or can be used at the mobile terminal and external device Transfer data between.

The output unit 150 may include a display module 151, an audio output module 152, and the like.

The display unit 151 can display information processed in the mobile terminal 100. For example, when the mobile terminal 100 is in a phone call mode, the display unit 151 can display a user interface (UI) or a graphical user interface (GUI) related to a call or other communication (eg, text messaging, multimedia file download, etc.). When the mobile terminal 100 is in the video call mode or the image capturing mode, the display unit 151 may display the captured image and/or the received image, show the video or a picture. Like the UI or GUI of related functions and so on.

Meanwhile, when the display module 151 and the touch panel are superposed on each other in the form of layers to form a touch screen, the display module 151 can function as an input device and an output device. The display module 151 may include at least one of a liquid crystal display (LCD), a thin film transistor LCD (TFT-LCD), an organic light emitting diode (OLED) display, a flexible display, a three-dimensional (3D) display, and the like. Some of these displays may be configured to be transparent to allow a user to view from the outside, which may be referred to as a transparent display, and a typical transparent display may be, for example, a TOLED (Transparent Organic Light Emitting Diode) display or the like. According to a particular desired embodiment, the mobile terminal 100 may include two or more display units (or other display devices), for example, the mobile terminal may include an external display unit (not shown) and an internal display unit (not shown) . The touch screen can be used to detect touch input pressure as well as touch input position and touch input area.

The audio output module 152 may convert audio data received by the wireless communication unit 110 or stored in the memory 160 when the mobile terminal is in a call signal receiving mode, a call mode, a recording mode, a voice recognition mode, a broadcast receiving mode, and the like. The audio signal is output as sound. Moreover, the audio output module 152 can provide audio output (eg, call signal reception sound, message reception sound, etc.) associated with a particular function performed by the mobile terminal 100. The audio output module 152 can include a speaker, a buzzer, and the like.

The memory 160 may store a software program or the like that performs processing and control operations performed by the controller 180, or may temporarily store data that has been output or is to be output. Moreover, the memory 160 can store data regarding vibrations and audio signals of various manners that are output when a touch is applied to the touch screen.

The memory 160 may include at least one type of storage medium including a flash memory, a hard disk, a multimedia card, a card type memory (eg, SD or DX memory, etc.), a random access memory (RAM), a static random access memory ( SRAM), read only memory (ROM), electrically erasable programmable read only memory (EEPROM), programmable read only memory Memory (PROM), magnetic memory, disk, optical disk, etc. Moreover, the mobile terminal 100 can cooperate with a network storage device that performs a storage function of the memory 160 through a network connection.

The controller 180 typically controls the overall operation of the mobile terminal. For example, the controller 180 performs the control and processing associated with voice calls, data communications, video calls, and the like. In addition, the controller 180 may include a multimedia module 181 for reproducing (or playing back) multimedia data, which may be constructed within the controller 180 or may be configured to be separate from the controller 180. The controller 180 may perform a pattern recognition process to recognize a handwriting input or a picture drawing input performed on the touch screen as a character or an image.

The power supply unit 190 receives external power or internal power under the control of the controller 180 and provides appropriate power required to operate the various components and components.

The various embodiments described herein can be implemented in a computer readable medium using, for example, computer software, hardware, or any combination thereof. For hardware implementations, the embodiments described herein may be through the use of application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays ( An FPGA, a processor, a controller, a microcontroller, a microprocessor, at least one of the electronic units designed to perform the functions described herein, in some cases, such an embodiment may be at the controller 180 Implemented in the middle. For software implementations, implementations such as procedures or functions may be implemented with separate software modules that permit the execution of at least one function or operation. The software code can be implemented by a software application (or program) written in any suitable programming language, which can be stored in memory 160 and executed by controller 180.

So far, the mobile terminal has been described in terms of its function. Hereinafter, for the sake of brevity, a slide type mobile terminal among various types of mobile terminals such as a folding type, a bar type, a swing type, a slide type mobile terminal, and the like will be described as an example. Therefore, the present invention can be applied to any type of mobile terminal, and is not limited to a slide type mobile terminal.

The mobile terminal 100 as shown in FIG. 1 may be configured to utilize the number of transmissions via a frame or a packet It operates according to, for example, wired and wireless communication systems as well as satellite-based communication systems.

A communication system in which a mobile terminal according to the present invention can be operated will now be described with reference to FIG.

Such communication systems may use different air interfaces and/or physical layers. For example, air interfaces used by communication systems include, for example, Frequency Division Multiple Access (FDMA), Time Division Multiple Access (TDMA), Code Division Multiple Access (CDMA), and Universal Mobile Telecommunications System (UMTS) (in particular, Long Term Evolution (LTE)). ), Global System for Mobile Communications (GSM), etc. As a non-limiting example, the following description relates to a CDMA communication system, but such teachings are equally applicable to other types of systems.

Referring to FIG. 2, a CDMA wireless communication system can include a plurality of mobile terminals 100, a plurality of base stations (BS) 270, a base station controller (BSC) 275, and a mobile switching center (MSC) 280. The MSC 280 is configured to interface with a public switched telephone network (PSTN) 290. The MSC 280 is also configured to interface with a BSC 275 that can be coupled to the base station 270 via a backhaul line. The backhaul line can be constructed in accordance with any of a number of known interfaces including, for example, E1/T1, ATM, IP, PPP, Frame Relay, HDSL, ADSL, or xDSL. It will be appreciated that the system as shown in FIG. 2 can include multiple BSCs 275.

Each BS 270 can serve one or more partitions (or regions), each of which is covered by a multi-directional antenna or an antenna directed to a particular direction radially away from the BS 270. Alternatively, each partition may be covered by two or more antennas for diversity reception. Each BS 270 can be configured to support multiple frequency allocations, and each frequency allocation has a particular frequency spectrum (eg, 1.25 MHz, 5 MHz, etc.).

The intersection of partitioning and frequency allocation can be referred to as a CDMA channel. BS 270 may also be referred to as a Base Transceiver Subsystem (BTS) or other equivalent terminology. In such a case, the term "base station" can be used to generally refer to a single BSC 275 and at least one BS 270. A base station can also be referred to as a "cell station." Alternatively, each partition of a particular BS 270 may be referred to as a plurality of cellular stations.

As shown in FIG. 2, a broadcast transmitter (BT) 295 transmits a broadcast signal to the mobile terminal 100 operating within the system. The broadcast receiving module 111 as shown in FIG. 1 is disposed at the mobile terminal 100 to receive the broadcast signal transmitted by BT295. In Figure 2, several Global Positioning System (GPS) satellites 300 are shown. The satellite 300 helps locate at least one of the plurality of mobile terminals 100.

In Figure 2, a plurality of satellites 300 are depicted, but it is understood that useful positioning information can be obtained using any number of satellites. The position information module 115 as a GPS as shown in FIG. 1 is generally configured to cooperate with the satellite 300 to obtain desired positioning information. Instead of GPS tracking technology or in addition to GPS tracking technology, other techniques that can track the location of the mobile terminal can be used. Additionally, at least one GPS satellite 300 can selectively or additionally process satellite DMB transmissions.

As a typical operation of a wireless communication system, BS 270 receives reverse link signals from various mobile terminals 100. Mobile terminal 100 typically participates in calls, messaging, and other types of communications. Each reverse link signal received by a particular base station 270 is processed within a particular BS 270. The obtained data is forwarded to the relevant BSC 275. The BSC provides call resource allocation and coordinated mobility management functions including a soft handoff procedure between the BSs 270. The BSC 275 also routes the received data to the MSC 280, which provides additional routing services for interfacing with the PSTN 290. Similarly, PSTN 290 interfaces with MSC 280, MSC 280 interfaces with BSC 275, and BSC 275 controls BS 270 accordingly to transmit forward link signals to mobile terminal 100.

Various embodiments of the present invention are proposed based on the above-described mobile terminal hardware structure and communication system.

An embodiment of the present invention provides a method for acquiring an image processing method. Referring to FIG. 3, the method includes the following steps:

Step 301: Acquire an image to be processed, and divide the image to be processed according to a preset rule to obtain a first image.

Specifically, the step 301 is to obtain an image to be processed, and the image to be processed is divided according to a preset rule to obtain a first image, which may be implemented by an acquiring device of an image processing mode. The acquired image to be processed may be one frame of image data, and the first image after the segmentation may include at least two image blocks; the image processing mode acquisition device in the present invention may be a terminal device, for example It can be a mobile terminal device such as a mobile phone or a camera.

When the image is segmented according to the preset rule, the preset rule may be preset by the user according to his or her own wishes, the processing capability of the terminal device actually applied, and the processing effect that the user wants to achieve, and of course, the first segmentation is obtained. The more image blocks of an image, the better the white balance processing effect of each image obtained, and the higher the requirement for the terminal device; on the contrary, the smaller the image block of the first image obtained by segmentation, the smaller each image finally obtained. The worse the white balance processing effect, the lower the requirements for the terminal equipment.

In an actual application, the method in this embodiment may be specifically applied to a mobile terminal, that is, the acquiring device in the image processing mode may be specifically a mobile terminal; where the mobile terminal refers to a device that can be used in mobile, in a broad sense. It includes mobile phones, laptops, tablets, POS machines, and even car computers. However, in most cases, it refers to a mobile phone or a smartphone with a variety of application functions and a tablet. With the development of networks and technologies in the direction of more and more broadband, the mobile communication industry will move toward a real era of mobile information. On the other hand, with the rapid development of integrated circuit technology, the processing power of mobile terminals has already had powerful processing capabilities, and mobile terminals are changing from simple call tools to an integrated information processing platform. This also adds a broader space for development of mobile terminals. Mobile terminals have evolved over the decades with the development of mobile communications as simple communication devices. Mobile intelligent terminals are transformed into key portals and major innovation platforms for Internet services in a short period of time, new media, e-commerce and information service platforms, the most important hub for Internet resources, mobile network resources and environmental interaction resources, and their operating systems and processing. The chip has even become the strategic commanding height of the entire information and communication technology industry today. The mobile intelligent terminal can be referred to as an intelligent terminal for short. The mobile intelligent terminal has the ability to access the Internet, and is usually equipped with various operating systems, and can customize various functions according to user requirements. Smart terminals commonly found in life include mobile smart terminals, in-vehicle smart terminals, smart TVs, wearable devices, and the like.

Step 302: Sort and sort the first image based on the preset classification.

Specifically, step 302 is based on the preset classification, and classifying the first image may be performed by a map. A device like a processing method is implemented. The preset classification may be determined according to the relationship between the color temperature of the reflected light source falling in the preset partition and the color temperature of the original standard light source after the reflection of the standard light source by the reflective object of different colors; The first image may be classified into a specific object, and each of the first images is used as a launching object, and the color temperature of each standard in each of the preset categories is reflected by the standard light source after being reflected by each of the first images. The range is compared, and then the category to which the first image of each block obtained by the segmentation belongs is determined.

Step 303: Perform white balance processing on each of the first images in each category to obtain a second image, and obtain a white balance processing result of the second image in each category.

Specifically, step 303 performs white balance processing on each first image in each category to obtain a second image, and obtains a white balance processing result of the second image in each category, which may be an image processing mode acquisition device. To achieve. Performing white balance processing on each of the first images in each category may perform white balance processing on all the first images in each category in units of categories, and the specific white balance processing manner may be according to different categories. Corresponding white balance processing mode; the image obtained after the first image is subjected to white balance processing is the second image, the image block of the second image is the same as the number of image blocks in the first image, and the image block in the first image There is a one-to-one correspondence with the image blocks in the second image.

Step 304: Analyze a white balance processing result of the second image in each category to obtain a target white balance processing manner of the image to be processed.

Specifically, step 304 analyzes the white balance processing result of the second image in each category, and the target white balance processing manner of obtaining the image to be processed may be implemented by an image processing method. The method for analyzing the white balance processing result of the second image in each category, and obtaining the target white balance processing manner of the image to be processed may specifically be obtaining the image score of each second image after the white balance processing, based on each second The image score of the image is obtained as an image score of all the second images in each category, and the image score of the second image in each category is compared to obtain the most suitable image to be processed. The white balance processing method corresponding to the best category of the image, that is, the white balance processing result is the image target white balance processing mode of the image to be processed.

The method for obtaining an image processing method according to the embodiment of the present invention can obtain an image to be processed, and divide the image to be processed according to a preset rule to obtain a first image, and then classify and sort the first image based on the preset classification. Performing white balance processing on each of the first images in each category to obtain a second image, and acquiring white balance processing results of the second image in each category; analyzing white balance processing of the second image in each category As a result, a target white balance processing manner of the image to be processed is obtained; thus, the best processing result is selected from the processing results for different white balance processing methods according to the image to be processed, and the optimal processing result is taken as the to-be-processed The white balance processing method of the image solves the problem that the automatic white balance method in the prior art processes the image of different situations, and the calculation bias is improved, and the processing effect of the image white balance is improved; at the same time, the user experience can be improved.

An embodiment of the present invention provides a method for acquiring an image processing manner. Referring to FIG. 4, the method includes the following steps:

Step 401: The acquiring device of the image processing mode acquires an image to be processed, and divides the image to be processed according to a preset rule to obtain a first image.

Step 402: The image processing mode acquiring device acquires a color temperature of each first image in a preset partition.

Specifically, each of the first images obtained by the segmentation may be used as a reflective object, and the standard light source is used to illuminate the reflective object, and then the reflected light falls in a preset partition; Setting a specific color temperature range in the partition can obtain a color temperature of the first image in the preset partition; the preset partition can be a white area, and the white area can be a plurality of areas close to the standard light source color, which can be regarded as a standard light source light. The color of the light reflected by black and white.

Step 403: The image processing mode acquiring device classifies the first image according to a matching relationship between a color temperature of each first image in a preset partition and a color temperature of each category in the preset classification. sort out.

Specifically, the preset classification may be defined according to different conditions in which the standard light source is reflected by different reflective objects and falls in the white area. For example, the preset classification may include three categories, and the first category may be a standard light source. After the black and white objects are reflected, all the light can fall correctly in the white area, and the color temperature falling in the white area is the same as the color temperature of the light source before reflection; the second category can be 5000-7000K color temperature and 3000-5000K After the color temperature light source is irradiated to the yellow reflective object, the reflected light falls into the white area, and the color temperature is lower than the color temperature of the light source, or the light source may be irradiated on the green plant in the sunny day and the cloudy sky, and then fall into the white area. At this time, the color temperature falling into the white area is still lower than the color temperature of the original light source; the third category may be 3.2000-3000K color temperature and 3000-5000K color temperature light source after illuminating the light blue reflective object, at this time after reflection The color temperature of the light falling into the white zone is higher than the color temperature of the light source. After that, the relationship between the color temperature of each of the first images in the preset partition, that is, the white area, and the color temperature of each category in the preset category, the color temperature of the first image in the white area and the category of the preset classification may be determined. The category in which the color temperature range is matched is the category corresponding to the first image. For example, if the color temperature range of any first image in the white area belongs to the color temperature range of the first category in the white area, the first image may be considered as the first image. Classified as the first category.

Step 404: The acquiring device of the image processing mode separately calculates the number of the first images in each category, and obtains a classification in which the number of the first images is not zero.

Step 405: The image processing mode acquiring device performs white balance processing on each of the first images of the non-zero number of the first images according to the white balance processing algorithm of each category to obtain a second image, and acquires each of the images. The result of white balance processing of the second image in the category.

Specifically, each class's own white balance processing algorithm may be used to calculate the weighted average to project to the desired light color according to different projection rules, and then the number of the first image according to the values of the projected red, green and blue primary colors. A corresponding white balance process is performed for each of the first images of the non-zero categories, and a white balance processing result of the second image in each category is obtained. The specific white balance processing process can refer to the white balance processing of different types of images in the prior art. Cheng.

Step 406: The image processing mode acquiring device respectively acquires image scores of the second image in each class.

Specifically, the sum of the image scores of all the second images in each category may be obtained to obtain image scores of all the second images in each class.

Step 407: The image processing mode acquiring device analyzes and processes the image score of the second image in each class to obtain a target white balance processing mode of the image to be processed.

It should be noted that the explanation of the same steps or concepts in the other embodiments may refer to the descriptions in other embodiments, and details are not described herein again.

An embodiment of the present invention provides a method for acquiring an image processing manner. Referring to FIG. 5, the method includes the following steps:

Step 501: The acquiring device of the image processing mode acquires an image to be processed, and divides the image to be processed according to a preset rule to obtain a first image.

Step 502: The acquiring device of the image processing mode acquires a color temperature of each first image in a preset partition.

Step 503: The image processing mode acquiring device sorts the first image according to a matching relationship between a color temperature of each first image in a preset partition and a color temperature of each category in the preset classification.

Step 504: The acquiring device of the image processing mode separately calculates the number of the first images in each category, and obtains a classification in which the number of the first images is not zero.

Step 505: The image processing mode acquiring device performs white balance processing on each of the first images of the non-zero number of the first image according to the white balance processing algorithm of each category to obtain a second image, and obtain each The result of white balance processing of the second image in the category.

Step 506: The acquiring device of the image processing mode acquires a brightness score of each second image according to a preset brightness score rule.

Specifically, the preset brightness score rule may be preset and saved in the terminal device according to the principle of facilitating the definition of the brightness of different image blocks, for example, may be set according to the brightness of the image block, and the brighter the image block is. The larger the brightness score is, the smaller the opposite brightness score is, and the brightness score of each second image can be defined in the form of a step change; wherein, as shown in FIG. 6, the obtained second image can be obtained. The brightness score is stored in the terminal device in the form of a table. For example, the brightness score of the second image may be divided into 0 to 255 levels, and the brightness value of the second image a in the first category may be 10, the first category. The brightness score of the second image b in the second category may be 45, the brightness score of the second image c in the second category may be 20, and the brightness score of the second image d in the second category may be 35, the third The luminance score of the second image e in the category may be 105, and the luminance score of the second image f in the third category may be 50 or the like.

Step 507: The acquiring device of the image processing mode acquires a color score of each second image according to a preset color score rule.

Specifically, the preset brightness score rule may be preset and saved in the terminal device according to a principle that the color of the different image blocks is conveniently defined by the user, for example, the corresponding color may be defined according to whether the color in the image block is a common color. The color score of the image block, if in an image block When the color of the common color is red, blue, green, etc., the color score of the image block can be defined to be high. If the color of an image block is an uncommon color such as purple, the color score of the image block can be defined. The value is lower and the color score of each second image can be defined in the form of a step change. Wherein, as shown in FIG. 7, the obtained color scores of the respective second images may be stored in the terminal device in the form of a table, for example, the color score of the second image may be divided into 0 to 255 levels, the first category. The color score of the second image a in the second category may be 20, the color score of the second image b in the first category may be 200, and the color score of the second image c in the second category may be 15, second The color score of the second image d in the category may be 100, the color score of the second image e in the third category may be 30, and the color score of the second image f in the third category may be 135 or the like.

Step 508: The image processing mode acquiring device separately multiplies the obtained luminance score and the color score of each second image to obtain an image score of each second image.

Step 509: The image processing mode acquiring device adds the image scores of each second image in each category to obtain image scores of the second image in each class.

Specifically, after the luminance score and the color score of each second image are multiplied, the image score of the second image may be obtained, and then the image scores of all the second images in each category may be added. That is, the image score of the second image in the first category can be obtained. Referring to FIG. 8 , the obtained image scores of the second image of each category can be stored in the terminal device in units of categories, for example, the first The image score of the category may be 18200, the image score of the second category may be 8000, and the image score of the third category may be 10040, indicating that the white balance processing effect of the first category is the best, so the image to be processed can be set. The target white balance processing mode is a white balance processing algorithm corresponding to the first category.

Step 510: The image processing mode acquiring device compares the image scores of the second image in each category, and obtains the target classification with the largest image score of the second image in the preset classification.

Step 511: The image processing mode acquiring device sets the white balance algorithm corresponding to the target classification with the largest image score of the second image as the target white balance processing mode of the image to be processed.

Specifically, the terminal device can compare the size relationship between the image scores of the second image in each category, and set the white balance algorithm corresponding to the category to which the image with the largest image score belongs to be the target white of the image to be processed. Balanced processing.

The embodiment of the present invention further describes a computer storage medium, wherein the computer storage medium stores a computer program, and the computer program is used to execute the image processing mode acquisition method described in the embodiment of the present invention.

An embodiment of the present invention provides an image processing mode acquisition device 6, which can be applied to an image processing mode acquisition method provided by the embodiment corresponding to FIG. 3 to FIG. The method includes: a first obtaining unit 61, a classifying unit 62, a second acquiring unit 63, and a processing unit 64, wherein:

The first obtaining unit 61 is configured to acquire an image to be processed, and divide the image to be processed according to a preset rule to obtain a first image.

The classification unit 62 classifies the first image based on the preset classification.

The second obtaining unit 63 is configured to perform white balance processing on each of the first images in each category to obtain a second image, and acquire a white balance processing result of the second image in each category.

The processing unit 64 is configured to analyze the white balance processing result of the second image in each category to obtain a target white balance processing manner of the image to be processed.

The acquiring device of the image processing mode provided by the embodiment of the present invention can obtain the image to be processed, and divide the image to be processed according to a preset rule to obtain a first image, and then classify and sort the first image based on the preset classification. Performing white balance processing on each of the first images in each category to obtain a second image, and acquiring white balance processing results of the second image in each category; analyzing white balance processing of the second image in each category As a result, a target white balance processing manner of the image to be processed is obtained; thus, the best processing result is selected from the processing results for different white balance processing methods according to the image to be processed, and the optimal processing result is taken as the to-be-processed The white balance processing method of the image solves the problem that the automatic white balance method in the prior art processes the image of different situations, and the calculation bias is improved, and the processing effect of the image white balance is improved; at the same time, the user experience can be improved.

Specifically, referring to FIG. 10, the classification unit 62 may include: a first acquisition module 621 and a classification module 622, where:

The first obtaining module 621 is configured to acquire a color temperature of each first image in a preset partition.

The classification module 622 is configured to classify the first image according to a matching relationship between a color temperature of each first image in a preset partition and a color temperature of each category in the preset classification.

In an embodiment, the first obtaining module 621 is further configured to use each of the first images as a transmitting object, and reflect a color temperature of the standard light source into each of the first images and fall into a preset partition. The range is the color temperature of the first image in the preset partition.

Specifically, referring to FIG. 11, the second obtaining unit 63 may include: a calculating module 631 and a second acquiring module 632, where:

The calculating module 631 is configured to separately calculate the number of the first images in each category to obtain the first A classification in which the number of images is not zero.

The second obtaining module 632 is configured to perform white balance processing on each of the first images of the non-zero number of the first images according to the white balance processing algorithm of each category to obtain a second image, and obtain each category. The result of white balance processing of the second image.

Further specifically, referring to FIG. 12, the processing unit 64 includes: a third obtaining module 641 and a processing module 642, wherein:

The third obtaining module 641 is configured to respectively acquire image scores of the second image in each class.

The third obtaining module 641 is further configured to compare image scores of the second image in each class, and obtain a target classification with the largest image score of the second image in the preset classification.

The processing module 642 is configured to set a white balance algorithm corresponding to the target classification with the largest image score of the second image as the target white balance processing mode.

Specifically, the third obtaining module 641 is further configured to perform the following steps:

The brightness score of each second image is obtained according to a preset brightness score rule.

The color score of each second image is obtained according to a preset color score rule.

The obtained luminance scores and color scores of each of the second images are respectively multiplied to obtain image scores for each of the second images.

The image scores of each of the second images in each class are added to obtain image scores for the second image in each class.

It should be noted here that the description of the above embodiment of the device is similar to the description of the method embodiment described above, and has the same advantageous effects as the method embodiment, and therefore will not be described again. For the technical details that are not disclosed in the embodiment of the present invention, please refer to the description of the method embodiment of the present invention for the sake of space saving, and therefore no further details are provided.

The acquiring device of the image processing mode provided by the embodiment of the present invention can obtain the image to be processed, and divide the image to be processed according to a preset rule to obtain a first image, and then classify and sort the first image based on the preset classification. For each first image in each category Performing a white balance process to obtain a second image, and acquiring a white balance processing result of the second image in each category; analyzing a white balance processing result of the second image in each category to obtain a target white balance processing manner of the image to be processed In this way, the prior art is solved by selecting the best processing result from the processing results for different white balance processing methods according to the image to be processed, and using the optimal processing result as the white balance processing manner of the image to be processed. When the automatic white balance method is used to process images of different situations, there is a problem of calculation deviation, which improves the processing effect of image white balance; at the same time, the user experience can be improved.

In an actual application, the first acquiring unit 61, the classifying unit 62, the second obtaining unit 63, the processing unit 64, the first obtaining module 621, the classifying module 622, the calculating module 631, the second obtaining module 632, and the third obtaining Both the module 641 and the processing module 642 can be implemented by a central processing unit (CPU), a microprocessor (Micro Processor Unit (MPU), a digital signal processor (DSP) or a field located in the wireless data transmitting device. Realizable by a Field Programmable Gate Array (FPGA).

An embodiment of the present invention further provides an image processing mode acquiring device 7. As shown in FIG. 13, the device includes: a memory 71 configured with executable instructions; and a processor 72 configured to execute the executable instructions. The executable instructions are configured to:

In an embodiment, the executable instruction is further configured to acquire a color temperature of each of the first images in a preset partition; according to a color temperature of each of the first images in a preset partition, and the pre- The matching relationship between the color temperatures of each category in the classification is performed, and the first image is sorted.

In another embodiment, the executable instructions are further configured to calculate respectively in each category a number of the first images, obtaining a classification in which the number of the first images is not zero; according to a white balance processing algorithm of each category, each of the categories in which the number of the first images is not zero An image is subjected to white balance processing to obtain the second image, and a white balance processing result of the second image in each category is acquired.

In another embodiment, the executable instructions are further configured to respectively acquire image scores of the second image in each class; compare image scores of the second image in each class, and obtain a target classification with the largest image score of the second image in the preset classification; setting a white balance algorithm corresponding to the target classification with the largest image score of the second image as the target white balance processing manner.

In another embodiment, the executable instruction is further configured to acquire a brightness score of each of the second images according to a preset brightness score rule; and obtain each of the foregoing according to a preset color score rule Color scores of the second image; respectively multiplying the obtained luminance scores and color scores of each of the second images to obtain image scores for each of the second images; The image scores of the second image are added to obtain image scores of the second image in each class.

Here, it is noted that the first obtaining unit 61, the classifying unit 62, the second obtaining unit 63, the processing unit 64, the first obtaining module 621, the classifying module 622, the calculating module 631, the second obtaining module 632, and the Both the acquisition module 641 and the processing module 642 can be implemented by the processor 72 in particular. The processor 72 can be specifically a CPU, an MPU, a DSP, an FPGA, or the like.

It is to be understood that the term "comprises", "comprising", or any other variants thereof, is intended to encompass a non-exclusive inclusion, such that a process, method, article, or device comprising a series of elements includes those elements. Also includes other elements not explicitly listed, or It also includes elements inherent to such a process, method, article or device. An element that is defined by the phrase "comprising a ..." does not exclude the presence of additional equivalent elements in the process, method, item, or device that comprises the element.

The serial numbers of the embodiments of the present invention are merely for the description, and do not represent the advantages and disadvantages of the embodiments.

Through the description of the above embodiments, those skilled in the art can clearly understand that the foregoing embodiment method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be through hardware, but in many cases, the former is better. Implementation. Based on such understanding, the technical solution of the present invention, which is essential or contributes to the prior art, may be embodied in the form of a software product stored in a storage medium (such as ROM/RAM, disk, The optical disc includes a number of instructions for causing a terminal device (which may be a cell phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the methods described in various embodiments of the present invention.

The present invention has been described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (system), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or FIG. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing device to produce a machine for the execution of instructions for execution by a processor of a computer or other programmable data processing device. Means for implementing the functions specified in one or more of the flow or in a block or blocks of the flow chart.

The computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture comprising the instruction device. The apparatus implements the functions specified in one or more blocks of a flow or a flow and/or block diagram of the flowchart.

These computer program instructions can also be loaded into a computer or other programmable data processing device Having a series of operational steps performed on a computer or other programmable device to produce computer-implemented processing such that instructions executed on a computer or other programmable device are provided for implementing one or more processes in a flowchart and/or Or block diagram the steps of a function specified in a box or multiple boxes.

The above are only the preferred embodiments of the present invention, and are not intended to limit the scope of the invention, and the equivalent structure or equivalent process transformations made by the description of the present invention and the drawings are directly or indirectly applied to other related technical fields. The same is included in the scope of patent protection of the present invention.

Industrial applicability

The embodiment of the present invention solves the prior art by selecting an optimal processing result from the processing results of the image to be processed for different white balance processing modes, and using the optimal processing result as the white balance processing mode of the image to be processed. In the automatic white balance method, there is a problem of calculation deviation when processing images of different situations, thereby improving the processing effect of image white balance; at the same time, laying a foundation for improving the user experience.

Claims

An apparatus for acquiring an image processing method, the device comprising: a first acquiring unit, a classifying unit, a second acquiring unit, and a processing unit, wherein:

The first acquiring unit is configured to acquire an image to be processed, and divide the image to be processed according to a preset rule to obtain a first image;

The classifying unit is configured to classify the first image according to a preset classification;

The second acquiring unit is configured to perform white balance processing on each of the first images in each category to obtain a second image, and obtain a white balance processing result of the second image in each category;

The processing unit is configured to analyze a white balance processing result of the second image in each category to obtain a target white balance processing manner of the image to be processed.
The device according to claim 1, wherein the classification unit comprises: a first acquisition module and a classification module, wherein:

The first acquiring module is configured to acquire a color temperature of each of the first images in a preset partition;

The classifying module is configured to classify the first image according to a matching relationship between a color temperature of each of the first images in a preset partition and a color temperature of each of the preset categories.
The device according to claim 2, wherein the first obtaining module is further configured to use each of the first images as a transmitting object, and reflect a standard light source through each block of the first image to fall into a preset. The range of color temperatures in the partition is the color temperature of the first image in the preset partition.
The device according to claim 1, wherein the second obtaining unit comprises: a calculating module and a second acquiring module, wherein:

The calculating module is configured to separately calculate the number of the first images in each category, and obtain a classification that the number of the first images is not zero;

The second obtaining module is configured to perform white balance processing on each of the first images in the category of the first image that is not zero according to a white balance processing algorithm of each category to obtain the second An image, and a white balance processing result of the second image in each category is obtained.
The device of claim 1, wherein the processing unit comprises: a third acquisition module and a processing module, wherein:

The third obtaining module is configured to separately acquire image scores of the second image in each class;

The third acquiring module is further configured to compare image scores of the second image in each class, and obtain a target classification with the largest image score of the second image in the preset classification;

The processing module is configured to set a white balance algorithm corresponding to the target classification with the largest image score of the second image as the target white balance processing manner.
The device according to claim 5, wherein the third obtaining module is further configured to:

Obtaining a brightness score of each of the second images according to a preset brightness score rule;

Obtaining a color score of each of the second images according to a preset color score rule;

And multiplying a brightness score and a color score of each of the obtained second images to obtain an image score of each of the second images;

The image scores of each of the second images in each class are added to obtain image scores for the second image in each of the classes.
The apparatus according to any one of claims 1 to 6, wherein the preset classification is defined according to different conditions in which a standard light source is reflected in a white area after being reflected by a different reflective object.
A method for obtaining an image processing method, the method comprising:

Obtaining an image to be processed, and dividing the image to be processed according to a preset rule To the first image;

Sorting and sorting the first image based on a preset classification;

Performing white balance processing on each of the first images in each category to obtain a second image, and acquiring a white balance processing result of the second image in each category;

A white balance processing result of the second image in each category is analyzed to obtain a target white balance processing manner of the image to be processed.
The method according to claim 8, wherein the classifying the first image based on a preset classification comprises:

Obtaining a color temperature of each of the first images in a preset partition;

And classifying the first image according to a matching relationship between a color temperature of each of the first images in a preset partition and a color temperature of each of the preset categories.
The method of claim 9, wherein the obtaining a color temperature of each of the first images in a preset partition comprises:

Each of the first images is used as a transmitting object, and a range of color temperatures of the standard light source reflected by each of the first images and falling into a preset partition is used as a color temperature of the first image in a preset partition.
The method according to claim 8, wherein said performing white balance processing on each of said first images in each category to obtain a second image, and acquiring white of said second image in each category Balance the processing results, including:

Calculating the number of the first images in each category separately, and obtaining a classification in which the number of the first images is not zero;

According to the white balance processing algorithm of each category, each of the first images in the category in which the number of the first images is not zero is respectively subjected to white balance processing to obtain the second image, and each category is obtained. The result of the white balance processing of the second image.
The method of claim 8 wherein said analyzing the second of each category The white balance processing result of the image, the target white balance processing manner of the image to be processed is obtained, including:

Obtaining image scores of the second image in each class separately;

Comparing image scores of the second image in each class, and acquiring a target classification with the largest image score of the second image in the preset classification;

And setting a white balance algorithm corresponding to the target classification in which the image score of the second image is the largest is the target white balance processing manner.
The method of claim 12, wherein the separately obtaining image scores of the second image in each class comprises:

Obtaining a brightness score of each of the second images according to a preset brightness score rule;

Obtaining a color score of each of the second images according to a preset color score rule;

And multiplying a brightness score and a color score of each of the obtained second images to obtain an image score of each of the second images;

The image scores of each of the second images in each class are added to obtain image scores for the second image in each of the classes.
The method according to any one of claims 8 to 13, wherein the preset classification is defined according to different conditions in which the standard light source is reflected in different white objects after being reflected by different reflective objects.
An apparatus for acquiring an image processing method, the device comprising: a memory configured with executable instructions; and a processor configured to execute the executable instructions, the executable instructions configured to:

Obtaining a to-be-processed image, performing the segmentation process according to a preset rule to obtain a first image; classifying and finishing the first image based on a preset classification; respectively, for each of the categories in each category Performing white balance processing on an image to obtain a second image, and acquiring a white balance processing result of the second image in each category; analyzing white level of the second image in each category The processing result is balanced to obtain a target white balance processing manner of the image to be processed.
The device according to claim 15, wherein the executable instructions are further configured to acquire a color temperature of each of the first images in a preset partition; according to each of the first images in a preset partition The matching relationship between the color temperature and the color temperature of each of the preset categories is used to sort the first image.
The apparatus of claim 15, wherein the executable instructions are further configured to separately calculate a number of first images in each category to obtain a classification in which the number of the first images is not zero; a white balance processing algorithm of the category, respectively performing white balance processing on each of the first images in the category in which the number of the first images is not zero to obtain the second image, and acquiring the second in each category The white balance processing result of the image.
The apparatus of claim 15, wherein the executable instructions are further configured to separately acquire image scores for the second image in each class; compare images of the second image in each of the classes a score, obtaining a target classification with the largest image score of the second image in the preset classification; setting a white balance algorithm corresponding to the target classification with the largest image score of the second image as the target white Balanced processing.
The device according to claim 18, wherein the executable instruction is further configured to acquire a brightness score of each of the second images according to a preset brightness score rule; and obtain according to a preset color score rule Color scores of each of the second images; respectively multiplying the obtained luminance scores and color scores of each of the second images to obtain image scores for each of the second images; The image scores of each of the second images in the class are added to obtain image scores for the second image in each of the classes.
A computer storage medium storing a computer program for performing the image processing method acquisition method according to any one of the preceding claims 8 to 14.