CN112598678A

CN112598678A - Image processing method, terminal and computer readable storage medium

Info

Publication number: CN112598678A
Application number: CN202011361453.9A
Authority: CN
Inventors: 张沛昌
Original assignee: Nubia Technology Co Ltd
Current assignee: Nubia Technology Co Ltd
Priority date: 2020-11-27
Filing date: 2020-11-27
Publication date: 2021-04-02

Abstract

The invention discloses an image processing method, a terminal and a computer readable storage medium, wherein the method comprises the steps of obtaining an input image, and dividing the input image into a main image and a background image; adopting a first image processing method to amplify the main body image to obtain a target main body image, adopting a second image processing method to amplify the background image to obtain a target background image, wherein the first image processing method and the second image processing method are different image processing methods; splicing the target main body image and the target background image to obtain a target image; the invention also discloses a terminal and a storage medium, and the terminal and the storage medium adopt different image processing methods aiming at the main image and the background image by implementing the scheme, thereby realizing the purposes of highlighting the main image and reducing the time consumption and the power consumption for improving the image resolution.

Description

Image processing method, terminal and computer readable storage medium

Technical Field

The present invention relates to the field of image processing technologies, and in particular, to an image processing method, a terminal, and a computer-readable storage medium.

Background

At present, the requirement of a user on the resolution of a shot image is higher and higher, but in the related art, a certain image processing method is often adopted for image processing, thereby causing some problems. For example, a picture is 100x100 in size, and a picture enlarged to 200x200 is usually processed by an image processing method. If a faster processing speed and a simpler processing method are pursued, some conventional algorithms, such as a nearest neighbor algorithm, a bilinear interpolation method, etc., are usually directly used for processing, but the resolution of the obtained picture is not high. If the super-resolution technology is directly adopted for image amplification, although the image amplification effect is good, the processing speed is slower, and the power consumption is larger. In some scenes, the user takes a picture with more concern about the clarity of the subject, and the clearer the better, the regions outside the subject are not concerned, and the regions outside the subject region are expected to be even more blurred to highlight the subject. Therefore, how to improve the definition of the image subject and reduce the time consumption and power consumption of the image processing as much as possible becomes an urgent problem to be solved.

Disclosure of Invention

The technical problem to be solved by the present invention is to provide an image processing method, a terminal and a computer-readable storage medium, aiming at the technical problem that the prior image processing method can not improve the definition of an image main body and simultaneously reduces the time consumption and the power consumption of image processing as much as possible.

In order to solve the above technical problem, the present invention provides an image processing method, including:

acquiring an input image, and segmenting the input image into a main image and a background image;

adopting a first image processing method to amplify the main body image to obtain a target main body image, adopting a second image processing method to amplify the background image to obtain a target background image, wherein the first image processing method and the second image processing method are different image processing methods;

and splicing the target main body image and the target background image to obtain a target image.

Optionally, the resolution of the target subject image is greater than the resolution of the target background image.

Optionally, after the target subject image and the target background image are spliced, smoothing is performed on a spliced position of the target subject image and the target background image.

Optionally, the obtaining a target subject image by performing amplification processing on the subject image by using the first image processing method, and obtaining a target background image by performing amplification processing on the background image by using the second image processing method include:

and acquiring a preset magnification factor, and performing magnification processing on the main body image and the background image according to the preset magnification factor.

Optionally, the segmenting the input image into a subject image and a background image includes:

detecting the main body image by adopting an image detection technology;

and segmenting the main body image and the background image by adopting a matting technology.

Optionally, the first image processing method is to perform image processing by using a super-resolution technology.

Optionally, the second image processing method is to perform image processing by using a proximity interpolation algorithm or a bilinear interpolation method.

Optionally, the obtaining the target subject image by performing the amplification processing on the subject image by using the first image processing method includes:

inputting the main body image into a super-resolution reconstruction model obtained by pre-training to obtain a super-resolution reconstruction image; the super-resolution reconstruction model is obtained by training based on a target sample image as a training set, wherein the target sample image is an image containing the main body image.

Furthermore, the invention also provides a terminal, which 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 configured to execute one or more programs stored in the memory to implement the steps of the image processing method described above.

Further, the present invention also provides a computer-readable storage medium storing one or more programs, which are executable by one or more processors to implement the steps of the image processing method as described above.

Advantageous effects

The invention provides an image processing method, a terminal and a computer readable storage medium, wherein the method comprises the steps of obtaining an input image, and dividing the input image into a main image and a background image; adopting a first image processing method to amplify the main body image to obtain a target main body image, adopting a second image processing method to amplify the background image to obtain a target background image, wherein the first image processing method and the second image processing method are different image processing methods; splicing the target main body image and the target background image to obtain a target image; the invention also discloses a terminal and a storage medium, and the terminal and the storage medium adopt different image processing methods aiming at the main image and the background image by implementing the scheme, thereby realizing the purposes of improving the resolution of the main image and reducing the time consumption and the power consumption of image processing.

Drawings

The invention will be further described with reference to the accompanying drawings and examples, in which:

fig. 1 is a schematic diagram of a hardware structure of an alternative mobile terminal for 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 basic flowchart of an image processing method according to a first embodiment of the present invention;

FIG. 4 is a flowchart of a matting method according to a first embodiment of the invention;

fig. 5 is a schematic structural diagram of a terminal according to a second 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 information transmission and reception or during a call, and specifically, receive downlink information of a base station and then process the downlink information to the processor 110; in addition, the uplink data is transmitted to the base station. Typically, 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. In addition, the radio frequency unit 101 can also communicate with a network and other devices through wireless communication. The wireless communication may use any communication standard or protocol, including but not limited to GSM (Global System for Mobile communications), GPRS (General Packet Radio Service), CDMA2000(Code Division Multiple Access 2000), WCDMA (Wideband Code Division Multiple Access), TD-SCDMA (Time Division-Synchronous Code Division Multiple Access), FDD-LTE (Frequency Division duplex Long Term Evolution), and TDD-LTE (Time Division duplex Long Term Evolution).

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 Processing Unit 1041 Processing image data of a fixed picture 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 is used to display information input by a user or information provided to the user. 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 (LCD), an Organic Light-Emitting Diode (OLED), 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, where the communication Network system is an LTE system of a universal mobile telecommunications technology, and the LTE 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 the LTE system is described as an example, it should be understood by those skilled in the art that the present invention is not limited to the LTE system, but may also be applied 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.

First embodiment

Fig. 3 is a basic flowchart of an image processing method provided in this embodiment, where the image processing method includes:

s301, an input image is obtained and is divided into a main body image and a background image.

In an embodiment of the present invention, the segmenting the input image into the main image and the background image includes: detecting the main body image by adopting an image detection technology; and segmenting the main body image and the background image by adopting a matting technology.

As shown in fig. 4, fig. 4 is a flowchart of a matting method provided in this embodiment, specifically, performing image processing by using a matting technique includes the following steps:

s3011: classifying the input image from multiple dimensions to obtain multiple classification results, and determining a matting parameter according to the multiple classification results.

S3012: and fusing the classification results according to the preset dimension weight to obtain a score corresponding to the input image, and determining the category of the input image according to the score.

S3013: and determining the similarity of the main image and the background image in the input image, and determining a matting algorithm according to the similarity and the category.

S3014: and carrying out cutout processing on the input image according to the cutout algorithm and the cutout parameters.

In step S3011, specifically, the input image is classified from multiple dimensions to obtain multiple classification results, and a matting parameter is determined according to the multiple classification results. The multiple dimensions may include at least two dimensions of a scene dimension, an image complexity dimension, and an object dimension, and the multiple dimensions may further include a viewing angle dimension, a hue dimension, a brightness dimension, and the like.

In addition, each dimension also corresponds to a plurality of categories, wherein the image complexity dimension can correspond to at least two categories of a simple category, a general category, a medium category, a complex category, a difficult-to-solve category, a special category and the like. The scene dimensions may correspond to at least two of the categories of indoor bright light, indoor medium light, indoor dim light, outdoor bright light, outdoor medium light, outdoor low light, artificial dim light, artificial medium light, and artificial dim light. The object dimensions may correspond to at least two of the categories of people, animals, goods, food, buildings, vehicles, and plants. In addition, the classification result is used to indicate a category to which the input image belongs in the dimension.

In addition, the above-mentioned newspaper parameter is used for adjusting the degree of distinction between the main image and the background image in the input image, so that the main image part in the input image can be separated more easily.

In step S3013, the similarity between the main image and the background image in the input image is determined, and the matting algorithm is determined according to the similarity and the category. The matting algorithm may be a threshold method, a flood method, a watershed method, an image segmentation method, or a deep learning method, and the embodiment of the present invention is not limited.

In this embodiment of the present invention, optionally, determining the similarity between the subject image and the background image in the input image includes: performing region division on an input image to determine a main image and a background image, and calculating a main color histogram corresponding to the main image: determining a color histogram corresponding to each background image, and fusing the color histograms according to a preset region weight to obtain a background color histogram: and calculating the similarity of the main body color histogram and the background color histogram as the similarity of the main body image and the background image in the input image. The method for dividing the input image into regions to determine the main image and the background image may be: the input image is divided into N (N is a positive integer) regions, and a region having an intersection with a frame of the input image is determined as a background image, and a region having no intersection with a frame of the input image is determined as a subject image.

Among them, the color histogram is a color feature widely adopted in many image retrieval systems. It describes the proportion of different colors in the whole image, and does not care about the spatial position of each color, i.e. cannot describe the object or object in the image. The body color histogram and the background color histogram represent distribution curves of colors of the respective color channels.

In step S3014, a matting process is performed on the input image according to a matting algorithm and a matting parameter.

In the embodiment of the present invention, optionally, performing matting processing on an input image according to a matting algorithm and a matting parameter includes: performing discrimination adjustment on the input image according to the matting parameter; and separating the main image and the background image of the input image after the discrimination adjustment according to a matting algorithm, and taking the separated main image as a matting processing result.

Specifically, the process of taking the separated main body image as the matting processing result includes: and softening the edge of the separated main body image through the edge softening parameter, and performing gradual change processing on the region in the preset range of the edge through the feather range parameter so as to take the main body image after the gradual change processing as a matting processing result.

Wherein, the mode of carrying out the discrimination adjustment to the input image according to the matting parameter can be as follows: and adjusting the contrast, brightness, sharpness and dynamic range of the input image according to the matting parameters. In addition, the degree of distinction of the input image is adjusted according to the matting parameter, and it can be understood that if the input image is shot in an outdoor over-bright scene, the brightness of the input image can be reduced through the matting parameter, and the degree of distinction of the main image and the background image is further improved; if the input image is shot in an outdoor too dark scene, the brightness of the input image can be improved through the matting parameters, and then the distinguishing degree of the main body image and the background image is improved.

The mode of separating the main image and the background image of the input image after the discrimination adjustment according to the matting algorithm can be as follows: and separating the main image and the background image of the input image after the discrimination adjustment by a threshold value method, a water overflow method, a watershed method, an image segmentation method or a deep learning method.

S302, a first image processing method is adopted to amplify the main body image to obtain a target main body image, a second image processing method is adopted to amplify the background image to obtain a target background image, and the first image processing method and the second image processing method are different image processing methods.

It should be understood that the user's requirements for clarity of the subject image and the background image are typically different. In general, when a user takes a picture in some scenes, the user is more concerned about the definition of the shot subject, the clearer is the better, the areas outside the subject are not concerned, and the areas outside the subject area are expected to be more blurred to highlight the subject. Therefore, in the embodiment of the present invention, the subject image and the background image are processed by different image processing methods, respectively.

In the embodiment of the invention, if the user is more concerned about the subject image. Then, the resolution of the target subject image obtained after the subject image is amplified by the first image processing method is greater than the resolution of the background subject image obtained after the background image is amplified by the second image processing method.

Specifically, the obtaining a target subject image by performing an amplification process on a subject image by using a first image processing method, and obtaining a target background image by performing an amplification process on the background image by using a second image processing method includes: and acquiring a preset magnification factor, and performing magnification processing on the main body image and the background image according to the preset magnification factor. The preset magnification factor may be set by a user before image processing, or may be directly preset a fixed value to be stored in the image processing apparatus, which is not limited herein.

In order to achieve the above effects, it is necessary that the processing effect of the first image processing method is superior to that of the second image processing method. Specifically, the first image processing method is to perform image processing by using a super-resolution technique.

The obtaining of the target subject image by performing the amplification processing on the subject image by using the first image processing method includes: inputting the main body image into a super-resolution reconstruction model obtained by pre-training to obtain a super-resolution reconstruction image; the super-resolution reconstruction model is obtained by training based on a target sample image as a training set, wherein the target sample image is an image containing the main body image.

In this embodiment, the second image processing method may be image processing using a proximity interpolation algorithm or a bilinear interpolation method.

Wherein, the adjacent interpolation algorithm does not need calculation. In the four adjacent pixels of the pixel to be solved, the gray value of the adjacent pixel closest to the pixel to be solved is given to the pixel to be solved. The bilinear interpolation method is to use the gray levels of four adjacent pixels of the pixel to be solved to do linear interpolation in two directions.

And S303, splicing the target main body image and the target background image to obtain a target image.

It should be understood that the joint between the target subject image and the target background image is not smooth in the target image obtained after the stitching. Therefore, after the target subject image and the target background image are spliced, smoothing is performed on the spliced position of the target subject image and the target background image.

It should be understood that image smoothing, i.e., suppressing, weakening or eliminating details, abrupt changes, edges and noise in the image. The image smoothing is low-pass filtering the image, and can be implemented in a spatial domain or a frequency domain. The spatial domain image smoothing method mainly uses low-pass convolution filtering, median filtering and the like; the low-pass filter commonly used for frequency domain image smoothing includes a low-pass ladder filter, a low-pass gaussian filter, a low-pass exponential filter, a butterworth low-pass filter, and the like. And the target image is better and natural by smoothing processing.

Advantageous effects

The invention provides an image processing method, a terminal and a computer readable storage medium, wherein the method comprises the steps of obtaining an input image, and dividing the input image into a main image and a background image; adopting a first image processing method to amplify the main body image to obtain a target main body image, adopting a second image processing method to amplify the background image to obtain a target background image, wherein the first image processing method and the second image processing method are different image processing methods; splicing the target main body image and the target background image to obtain a target image; by the method, the problems that the image main body is unclear, time consumption is high when the image resolution is improved, and the power consumption of the terminal is high are solved.

Second embodiment

The present embodiment further provides a terminal, as shown in fig. 5, which includes a processor 51, a memory 52 and a communication bus 53, wherein:

the communication bus 53 is used for realizing connection communication between the processor 51 and the memory 52;

the processor 51 is configured to execute one or more programs stored in the memory 52 to implement the steps of the image processing method in the first embodiment.

The present embodiment also provides 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 image processing method as in the first embodiment.

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.

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.

Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.

While the present invention has been described with reference to the embodiments shown in the drawings, the present invention is not limited to the embodiments, which are illustrative and not restrictive, and it will be apparent to those skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope of the invention as defined in the appended claims.

Claims

1. An image processing method, comprising:

2. The image processing method of claim 1, wherein a resolution of the target subject image is greater than a resolution of the target background image.

3. The image processing method according to claim 1, wherein after the stitching the target subject image and the target background image, further comprising smoothing the stitched portion of the target subject image and the target background image.

4. The image processing method of claim 1, wherein the obtaining of the target subject image by magnifying the subject image with the first image processing method and obtaining the target background image by magnifying the background image with the second image processing method comprises:

5. The image processing method of any of claims 1-4, wherein the segmenting the input image into a subject image and a background image comprises:

detecting the main body image by adopting an image detection technology;

6. The image processing method according to any of claims 1 to 4, wherein the first image processing method is image processing using a super resolution technique.

7. The image processing method according to any of claims 1 to 4, wherein the second image processing method is image processing using a proximity interpolation algorithm or a bilinear interpolation method.

8. The image processing method of claim 6, wherein the obtaining of the target subject image by performing the magnification processing on the subject image by using the first image processing method comprises:

9. A terminal, characterized in that the terminal comprises a processor, a memory and a communication bus;

the processor is configured to execute one or more programs stored in the memory to implement the steps of the image processing method according to any one of claims 1 to 8.

10. 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 image processing method according to any one of claims 1 to 8.