Image super-resolution processing method, terminal and computer readable medium

Abstract

The application discloses an image super-resolution processing method, a terminal and a computer readable medium. The image super-resolution processing method comprises the following steps: performing segmentation processing on a target image to obtain a plurality of segmented images; performing super-resolution processing on the segmented images in parallel; and merging the super-resolution processed images to obtain a super-resolution image corresponding to the target image. The technical scheme of the embodiment performs segmentation processing on an image with a large area to obtain a plurality of segmented images, then simultaneously performs super-resolution processing on each of the segmented images, finally merges the plurality of images after the super-resolution processing is completed, and further obtains a super-resolution image corresponding to the target image. Compared with the existing super-resolution processing mode of the whole target image, the technical scheme of the embodiment greatly improves the efficiency of image super-resolution processing.

Description

Technical Field

[0001] This invention relates to the field of image processing technology, and in particular to an image super-resolution processing method, a terminal, and a computer-readable medium. Background Technology

[0002] Images taken by users on mobile devices or downloaded from apps (such as browsers, Weibo, Taobao, etc.) often have low resolution. As the screen resolution of mobile devices increases, the low resolution greatly reduces the user experience.

[0003] Super-resolution processing of images can enrich image details, improve image quality, enhance the display effect of images on mobile devices, and facilitate users to perform secondary editing and creation on images. However, image super-resolution operations are usually time-consuming, so super-resolution processing of images on mobile devices usually does not result in a good user experience. Summary of the Invention

[0004] The main objective of this invention is to provide an image super-resolution processing method, terminal, and computer-readable medium, which aims to perform super-resolution on images by concurrently performing image super-resolution operations on the sub-image sequences obtained after image segmentation, thereby effectively reducing image super-resolution latency.

[0005] To achieve the above objectives, the image super-resolution processing method proposed in this invention includes the following steps:

[0006] The target image is segmented to obtain several segmented images;

[0007] The segmented images are subjected to super-resolution processing in parallel;

[0008] The super-resolution images are merged to obtain a super-resolution image corresponding to the target image.

[0009] Optionally, the step of segmenting the target image includes:

[0010] The target image is first segmented using a semantic-based image segmentation method to obtain several first sub-images;

[0011] Determine whether the first sub-image needs to undergo a second segmentation process;

[0012] If so, the first sub-image will be segmented a second time.

[0013] Optionally, the step of determining whether the first sub-image needs to undergo a second segmentation process includes:

[0014] Determine whether the number of the first sub-images is less than a first preset value;

[0015] If so, then the first sub-image needs to undergo a second segmentation process;

[0016] If not, it is determined that the first sub-image does not need to be segmented a second time, and based on the area of ​​the first sub-image, the first sub-image is merged or segmented to obtain several second sub-images.

[0017] Optionally, the step of merging or segmenting the first sub-image based on its area includes:

[0018] Determine whether the area of ​​the first sub-image is less than the second preset value;

[0019] If so, the first sub-image will be merged.

[0020] If not, the first sub-image will be segmented using an equal-division method.

[0021] Optionally, the step of merging the first sub-image includes:

[0022] Merge the first sub-image with the smallest area that is adjacent to the first sub-image.

[0023] Optionally, after the step of merging or segmenting the first sub-image to obtain several second sub-images, the method further includes:

[0024] Determine whether the second sub-image requires a second segmentation process;

[0025] If so, the second sub-image will be segmented a second time.

[0026] Optionally, the step of determining whether the second sub-image needs a second segmentation process includes:

[0027] Obtain the area of ​​the second sub-image;

[0028] Calculate the mean area and variance of the area of ​​the second sub-image;

[0029] Determine whether the area variance of the second sub-image is greater than a third preset value;

[0030] If so, the second sub-image needs to undergo a second segmentation process;

[0031] If not, the second sub-image is determined not to require a second segmentation process.

[0032] Optionally, the second segmentation process can be performed by dividing the data into equal parts.

[0033] Furthermore, the present invention also proposes a terminal, including a memory, a processor, and an implementation program for an image super-resolution processing method stored in the memory and executable on the processor. When the implementation program for the image super-resolution processing method is executed by the processor, the following steps are taken:

[0034] The target image is segmented to obtain several segmented images;

[0035] The segmented images are subjected to super-resolution processing in parallel;

[0036] The super-resolution images are merged to obtain a super-resolution image corresponding to the target image.

[0037] Furthermore, the present invention also proposes a computer-readable medium storing an implementation program of an image super-resolution processing method, wherein the implementation program of the image super-resolution processing method, when executed, performs the following steps:

[0038] The target image is segmented to obtain several segmented images;

[0039] The segmented images are subjected to super-resolution processing in parallel;

[0040] The super-resolution images are merged to obtain a super-resolution image corresponding to the target image.

[0041] The technical solution of this invention involves segmenting a large image to obtain several segmented images, then simultaneously performing super-resolution processing on each segmented image, and finally merging the super-resolution images to obtain the super-resolution image corresponding to the target image. Compared with existing methods that perform super-resolution processing on the entire target image, the technical solution of this embodiment greatly improves the efficiency of image super-resolution processing. Attached Figure Description

[0042] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.

[0043] Figure 1 A schematic diagram of the hardware structure of a mobile terminal to implement various embodiments of the present invention;

[0044] Figure 2A communication network system architecture diagram provided for an embodiment of the present invention;

[0045] Figure 3 This is a flowchart of an embodiment of the image super-resolution processing method of the present invention;

[0046] Figure 4 This is a flowchart of the second embodiment of the image segmentation method of the present invention;

[0047] Figure 5 This is a flowchart of the third embodiment of the image segmentation method of the present invention;

[0048] Figure 6 for Figure 5 The flowchart shown illustrates the specific steps of merging or segmenting the first sub-image based on its area to obtain several second sub-images.

[0049] Figure 7 for Figure 5 The flowchart shown illustrates the specific steps involved in determining whether the second sub-image needs to undergo a second segmentation process.

[0050] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0051] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0052] In the following description, the use of suffixes such as "module," "part," or "unit" to denote elements is solely for the purpose of illustrative purposes and has no specific meaning in itself. Therefore, "module," "part," or "unit" may be used interchangeably.

[0053] Terminals can be implemented in various forms. For example, the terminals described in this invention may include mobile terminals such as mobile phones, tablets, laptops, handheld computers, personal digital assistants (PDAs), portable media players (PMPs), navigation devices, wearable devices, smart bracelets, pedometers, etc., as well as fixed terminals such as digital TVs and desktop computers.

[0054] The following description will use a mobile terminal as an example. Those skilled in the art will understand that, apart from elements specifically designed for mobile purposes, the construction according to embodiments of the present invention can also be applied to fixed-type terminals.

[0055] Please see Figure 1This is a schematic diagram of the hardware structure of a mobile terminal implementing various embodiments of the present invention. The mobile terminal 100 may include: an RF (Radio Frequency) unit 101, a WiFi module 102, an audio output unit 103, an A / V (Audio / Video) input unit 104, a sensor 105, a display unit 106, a user input unit 107, an interface unit 108, a memory 109, a processor 110, and a power supply 111, etc. Those skilled in the art will understand that... Figure 1 The mobile terminal structure shown does not constitute a limitation on the mobile terminal. The mobile terminal may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0056] The following is combined with Figure 1 A detailed introduction to each component of the mobile terminal:

[0057] The radio frequency unit 101 can be used for receiving and transmitting signals during information transmission or calls. Specifically, it receives downlink information from the base station and processes it with the processor 110; additionally, it transmits uplink data to the base station. Typically, the radio frequency unit 101 includes, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low-noise amplifier, and a duplexer. Furthermore, the radio frequency unit 101 can also communicate wirelessly with networks and other devices. The aforementioned wireless communications may use any communication standard or protocol, including but not limited to GSM (Global System of Mobile communication), GPRS (General Packet Radio Service), CDMA2000 (Code Division Multiple Access 2000), WCDMA (Wideband Code Division Multiple Access), TD-SCDMA (Time Division-Synchronous Code Division Multiple Access), FDD-LTE (Frequency Division Duplexing-Long Term Evolution), and TDD-LTE (Time Division Duplexing-Long Term Evolution).

[0058] WiFi is a short-range wireless transmission technology. Mobile terminals, through the WiFi module 102, can help users send and receive emails, browse web pages, and access streaming media, providing users with wireless broadband internet access. Although Figure 1 WiFi module 102 is shown, but it is understood that it is not a necessary component of a mobile terminal and can be omitted as needed without changing the nature of the invention.

[0059] The audio output unit 103 can convert audio data received by the radio frequency unit 101 or the WiFi module 102 or stored in the memory 109 into audio signals and output them as sound when the mobile terminal 100 is in call signal receiving mode, call mode, recording mode, voice recognition mode, broadcast receiving mode, etc. Furthermore, the audio output unit 103 can also provide audio output related to specific functions performed by the mobile terminal 100 (e.g., call signal receiving sound, message receiving sound, etc.). The audio output unit 103 may include a speaker, a buzzer, etc.

[0060] 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 GPU 1041 processes image data of still images or videos acquired by an image capture device (such as a camera) in video capture mode or image capture mode. The processed image frames can be displayed on the display unit 106. The image frames processed by the GPU 1041 can be stored in the memory 109 (or other storage media) or transmitted via the radio frequency unit 101 or the WiFi module 102. The microphone 1042 can receive sound (audio data) in operating modes such as telephone call mode, recording mode, and voice recognition mode, and can process such sound into audio data. The processed audio (voice) data can be converted into a format that can be transmitted to a mobile communication base station via the radio frequency unit 101 in telephone call mode. The microphone 1042 can implement various types of noise cancellation (or suppression) algorithms to eliminate (or suppress) noise or interference generated during the reception and transmission of audio signals.

[0061] 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 and a proximity sensor. The ambient light sensor can adjust the brightness of the display panel 1061 according to the ambient light level, and the proximity sensor can turn off the display panel 1061 and / or backlight when the mobile terminal 100 is moved to the ear. As a type of motion sensor, the accelerometer sensor can detect the magnitude of acceleration in various directions (generally three axes). When stationary, it can detect the magnitude and direction of gravity and can be used for applications that recognize the phone's posture (such as landscape / portrait switching, related games, magnetometer posture calibration), vibration recognition-related functions (such as pedometer, tapping), etc. Other sensors that may be configured in the phone, such as fingerprint sensors, pressure sensors, iris sensors, molecular sensors, gyroscopes, barometers, hygrometers, thermometers, and infrared sensors, will not be described in detail here.

[0062] The display unit 106 is used to display information input by the user or information provided to the user. The display unit 106 may include a display panel 1061, which may be configured in the form of a liquid crystal display (LCD), an organic light-emitting diode (OLED), or the like.

[0063] User input unit 107 can be used to receive input numerical or character information, and generate key signal inputs related to user settings and function control of the mobile terminal. Specifically, user input unit 107 may include touch panel 1071 and other input devices 1072. Touch panel 1071, also known as touch screen, can collect touch operations on or near the user (such as operations performed by the user using a finger, stylus, or any suitable object or accessory on or near touch panel 1071), and drive corresponding connection devices according to a pre-set program. Touch panel 1071 may include two parts: a touch detection device and a touch controller. The touch detection device detects the user's touch position and the signal generated by the touch operation, and transmits the signal to the touch controller; the touch controller receives touch information from the touch detection device, converts it into touch point coordinates, sends it to processor 110, and can receive and execute commands from processor 110. In addition, touch panel 1071 can be implemented using various types such as resistive, capacitive, infrared, and surface acoustic wave. In addition to the touch panel 1071, the user input unit 107 may also include other input devices 1072. Specifically, other input devices 1072 may include, but are not limited to, one or more of the following: physical keyboard, function keys (such as volume control buttons, power buttons, etc.), trackball, mouse, joystick, etc., without being limited here.

[0064] Furthermore, the touch panel 1071 may cover the display panel 1061. When the touch panel 1071 detects a touch operation on or near it, it transmits the information to the processor 110 to determine the type of touch event. Subsequently, the processor 110 provides corresponding visual output on the display panel 1061 based on the type of touch event. Although in Figure 1 In this embodiment, the touch panel 1071 and the display panel 1061 are two independent components to realize the input and output functions of the mobile terminal. However, in some embodiments, the touch panel 1071 and the display panel 1061 can be integrated to realize the input and output functions of the mobile terminal. The specific implementation is not limited here.

[0065] Interface unit 108 serves as an interface through which at least one external device can connect to 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 with an identification module, an audio input / output (I / O) port, a video I / O port, a headphone port, and so on. Interface unit 108 may be used to receive input (e.g., data, power, etc.) from the external device and transmit the received input to one or more elements within mobile terminal 100, or it may be used to transmit data between mobile terminal 100 and the external device.

[0066] The memory 109 can be used to store software programs and various data. The memory 109 may primarily include a program storage area and a data storage area. The program storage area may store the operating system, applications required for at least one function (such as sound playback, image playback, etc.), etc.; the data storage area may store data created based on the use of the mobile phone (such as audio data, phonebook, etc.). Furthermore, the memory 109 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0067] The processor 110 is the control center of the mobile terminal. It connects various parts of the mobile terminal via various interfaces and lines. By running or executing software programs and / or modules stored in the memory 109, and by calling data stored in the memory 109, it performs various functions and processes data of the mobile terminal, thereby providing overall monitoring of the mobile terminal. The processor 110 may include one or more processing units; preferably, the processor 110 may integrate an application processor and a modem processor. The application processor mainly handles the operating system, user interface, and applications, while the modem processor mainly handles wireless communication. It is understood that the modem processor may not be integrated into the processor 110.

[0068] The mobile terminal 100 may also include a power supply 111 (such as a battery) that supplies power to various components. Preferably, the power supply 111 can be logically connected to the processor 110 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system.

[0069] although Figure 1 As not shown, the mobile terminal 100 may also include a Bluetooth module, etc., which will not be described in detail here.

[0070] To facilitate understanding of the embodiments of the present invention, the communication network system on which the mobile terminal of the present invention is based is described below.

[0071] Please see Figure 2 , Figure 2 This invention provides a communication network system architecture diagram. The communication network system is an LTE system based on the universal mobile communication technology. 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 the operator's IP services 204, which are connected in sequence.

[0072] Specifically, UE201 can be the aforementioned terminal 100, which will not be elaborated here.

[0073] E-UTRAN202 includes eNodeB2021 and other eNodeB2022s. Among them, eNodeB2021 can connect to other eNodeB2022s through backhaul (e.g., X2 interface), and eNodeB2021 connects to EPC203. eNodeB2021 can provide UE201 with access to EPC203.

[0074] EPC203 may include MME (Mobility Management Entity) 2031, HSS (Home Subscriber Server) 2032, other MMEs 2033, SGW (Serving Gateway) 2034, PGW (Packet Data Network Gateway) 2035, and PCRF (Policy and Charging Rules Function) 2036, etc. Among them, MME2031 is the control node that handles signaling between UE201 and EPC203, providing bearer and connection management. HSS2032 provides registers to manage functions such as the Home Location Register (not shown in the diagram) and stores user-specific information such as service characteristics and data rates. All user data can be sent through SGW2034. PGW2035 can provide UE 201 IP address allocation and other functions. PCRF2036 is the policy and charging control decision point for service data flow and IP bearer resources. It selects and provides available policy and charging control decisions for the policy and charging enforcement function unit (not shown in the figure).

[0075] IP services 204 may include the Internet, intranet, IMS (IP Multimedia Subsystem), or other IP services.

[0076] Although the above description uses the LTE system as an example, those skilled in the art should understand that the present invention is not only applicable to the LTE system, but also to other wireless communication systems, such as GSM, CDMA2000, WCDMA, TD-SCDMA, and future new network systems, etc., which are not limited here.

[0077] Based on the aforementioned mobile terminal hardware structure and communication network system, various embodiments of the method of the present invention are proposed.

[0078] like Figure 3 As shown, Figure 3 This is a flowchart of the first embodiment of the image segmentation method of the present invention.

[0079] In this embodiment, the image super-resolution processing method includes the following steps:

[0080] Step S310: The target image is segmented to obtain several segmented images.

[0081] Specifically, in this embodiment, the target image can be segmented at least once (the image segmentation method can be any existing image segmentation method) to obtain several segmented images.

[0082] Step S320: Perform super-resolution processing on the segmented image in parallel.

[0083] Specifically, in this embodiment, super-resolution processing is performed on each segmented image simultaneously, thereby greatly improving the super-resolution speed.

[0084] Step S330: Merge the super-resolution images to obtain a super-resolution image corresponding to the target image.

[0085] Specifically, in this embodiment, all the super-resolution processed images are merged by image merging (any existing image merging method can be used) to obtain the super-resolution processed image.

[0086] The technical solution of this embodiment involves segmenting a large image to obtain several segmented images, then simultaneously performing super-resolution processing on each segmented image, and finally merging the super-resolution images to obtain the super-resolution image of the corresponding target image. Compared with existing methods that perform super-resolution processing on the entire target image, the technical solution of this embodiment greatly improves the efficiency of image super-resolution processing.

[0087] Furthermore, such as Figure 4 As shown, Figure 4 This is a flowchart of the second embodiment of the image segmentation method of the present invention.

[0088] In this embodiment, the image super-resolution processing method includes the following steps:

[0089] Step S410: The target image is segmented for the first time using a semantic-based image segmentation method to obtain several first sub-images;

[0090] Step S420: Determine whether the first sub-image needs to be segmented a second time; if yes, proceed to step S430; if no, proceed to step S440.

[0091] Specifically, in this embodiment, the method for determining whether the first sub-image needs super-resolution processing can be: determining whether the number of the first sub-images is less than a first preset value; if yes, then determining that the first sub-image needs to undergo a second segmentation process; if no, then determining that the first sub-image does not need to undergo a second segmentation process.

[0092] Step S430: Perform a second segmentation process on the first sub-image, and then execute step S440.

[0093] Specifically, in this embodiment, the second segmentation process can be performed by equal division.

[0094] Step S440: Perform super-resolution processing on the segmented image in parallel.

[0095] Specifically, in this embodiment, when the first sub-image does not require a second segmentation process, the first sub-image is directly subjected to super-resolution processing; when the first sub-image requires segmentation processing, the first sub-image is subjected to a second segmentation process before super-resolution processing is performed.

[0096] Step S450: Merge the super-resolution images to obtain a super-resolution image corresponding to the target image.

[0097] The technical solution of this embodiment involves segmenting a large image to obtain several segmented images, then simultaneously performing super-resolution processing on each segmented image, and finally merging the super-resolution images to obtain the super-resolution image of the corresponding target image. Compared with existing methods that perform super-resolution processing on the entire target image, the technical solution of this embodiment greatly improves the efficiency of image super-resolution processing.

[0098] Furthermore, such as Figure 5 As shown, Figure 5 This is a flowchart of the third embodiment of the image segmentation method of the present invention.

[0099] In this embodiment, the image super-resolution processing method includes the following steps:

[0100] Step S510: The target image is segmented for the first time using a semantic-based image segmentation method to obtain several first sub-images;

[0101] Step S520: Determine whether the number of the first sub-images is less than a first preset value; if yes, proceed to step S530; if no, proceed to step S540.

[0102] Step S530: Perform a second segmentation process on the first sub-image.

[0103] Step S540: Based on the area of ​​the first sub-image, merge or segment the first sub-image to obtain several second sub-images.

[0104] Specifically, such as Figure 6 As shown, Figure 6 for Figure 5The flowchart shown illustrates the specific steps involved in merging or segmenting the first sub-image based on its area to obtain several second sub-images.

[0105] In this embodiment, the specific steps of merging or segmenting the first sub-image based on its area to obtain several second sub-images include:

[0106] Step S541: Determine whether the area of ​​the first sub-image is less than the second preset value; if yes, proceed to step S542; if no, proceed to step S543.

[0107] Step S542: Merge the first sub-image.

[0108] Specifically, in this embodiment, the specific steps for merging the first sub-image include: merging the first sub-image with the smallest area that is adjacent to the first sub-image with the first sub-image.

[0109] Step S543: Segment the first sub-image.

[0110] Specifically, in this embodiment, the specific steps for segmenting the first sub-image include: segmenting the first sub-image using an equal-division segmentation method.

[0111] Step S550: Determine whether the second sub-image needs to be segmented a second time; if yes, proceed to step S560; if no, proceed to step S570.

[0112] Specifically, such as Figure 7 As shown, Figure 7 for Figure 5 The flowchart shown illustrates the specific steps involved in determining whether the second sub-image needs to undergo a second segmentation process.

[0113] In this embodiment, the specific steps for determining whether the second sub-image needs to undergo a second segmentation process include:

[0114] Step S561: Obtain the area of ​​the second sub-image;

[0115] Step S562: Calculate the mean area and variance of the area of ​​the second sub-image;

[0116] Step S563: Determine whether the area variance of the second sub-image is greater than a third preset value. If yes, proceed to step S564; otherwise, proceed to step S565.

[0117] Step S564: Determine that the second sub-image needs to undergo a second segmentation process.

[0118] Step S565: Determine that the second sub-image does not need to undergo a second segmentation process.

[0119] Step S560: Perform a second segmentation process on the second sub-image.

[0120] Step S570: Perform super-resolution processing on the segmented image in parallel.

[0121] Specifically, in this embodiment, when the first sub-image does not require a second segmentation process, the first sub-image is directly subjected to super-resolution processing; when the first sub-image requires segmentation processing, the first sub-image is subjected to a second segmentation process before super-resolution processing. Similarly, when the second sub-image does not require a second segmentation process, the second sub-image is directly subjected to super-resolution processing; when the second sub-image requires segmentation processing, the second sub-image is subjected to a second segmentation process before super-resolution processing.

[0122] Step S580: Merge the super-resolution images to obtain the super-resolution image corresponding to the target image.

[0123] The technical solution of this embodiment involves segmenting a large image to obtain several segmented images, then simultaneously performing super-resolution processing on each segmented image, and finally merging the super-resolution images to obtain the super-resolution image of the corresponding target image. Compared with existing methods that perform super-resolution processing on the entire target image, the technical solution of this embodiment greatly improves the efficiency of image super-resolution processing.

[0124] This invention also proposes a terminal, including a memory, a processor, and an implementation program for an image super-resolution processing method stored in the memory and executable on the processor. When the implementation program for the image super-resolution processing method is executed by the processor, it implements all the steps in any of the above embodiments. Since the terminal can execute all the steps in any of the above embodiments, this mobile terminal has at least all the beneficial effects brought about by the technical solutions of the above method embodiments, which will not be elaborated further here.

[0125] The present invention also proposes a computer-readable medium storing an implementation program of an image super-resolution processing method. When executed, the implementation program of the image super-resolution processing method can perform all the steps in any of the above embodiments. Since the computer-readable medium can execute all the steps in any of the above embodiments, the present computer-readable medium at least has all the beneficial effects brought about by the technical solutions of the above method embodiments, which will not be elaborated further here.

[0126] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0127] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0128] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0129] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims. All of these forms are within the protection scope of the present invention.

Claims

1. An image super-resolution processing method, characterized in that, Includes the following steps: The target image is segmented to obtain several segmented images; specifically, the target image is segmented for the first time to obtain several first sub-images; it is determined whether the first sub-image needs to be segmented for the second time. If so, the first sub-image is segmented for the second time. Otherwise, based on the area of ​​the first sub-image, the first sub-image is merged or segmented to obtain several second sub-images. The segmented images are subjected to super-resolution processing in parallel; The super-resolution images are merged to obtain a super-resolution image corresponding to the target image; Specifically, determining whether the first sub-image needs to undergo a second segmentation process includes: determining whether the number of the first sub-images is less than a first preset value; if so, determining that the first sub-image needs to undergo a second segmentation process. The merging of the first sub-image specifically includes: determining whether the area of ​​the first sub-image is less than a second preset value; if so, merging the first sub-image with the smallest area that is adjacent to the first sub-image with the first sub-image.

2. The image super-resolution processing method as described in claim 1, characterized in that, The segmentation process of the target image includes: The target image is segmented for the first time using a semantic-based image segmentation method.

3. The image super-resolution processing method as described in claim 1, characterized in that, The step of merging or segmenting the first sub-image based on its area further includes: The first sub-image is segmented using the equal division method.

4. The image super-resolution processing method as described in claim 1, characterized in that, After the step of merging or segmenting the first sub-image to obtain several second sub-images, the method further includes: Determine whether the second sub-image requires a second segmentation process; If so, the second sub-image will be segmented a second time.

5. The image super-resolution processing method as described in claim 4, characterized in that, The step of determining whether the second sub-image needs a second segmentation process includes: Obtain the area of ​​the second sub-image; Calculate the mean area and variance of the area of ​​the second sub-image; Determine whether the area variance of the second sub-image is greater than a third preset value; If so, the second sub-image needs to undergo a second segmentation process; If not, the second sub-image is determined not to require a second segmentation process.

6. The image super-resolution processing method as described in claim 4, characterized in that, The second segmentation process is a method of equal division.

7. A terminal, characterized in that, The image super-resolution processing method includes a memory, a processor, and an implementation program of the image super-resolution processing method stored in the memory and executable on the processor. When the implementation program of the image super-resolution processing method is executed by the processor, it implements the steps of the image super-resolution processing method as described in any one of claims 1 to 6.

8. A computer-readable medium, characterized in that, The computer-readable medium stores an implementation program of the image super-resolution processing method, which, when executed, performs the steps of the image super-resolution processing method as described in any one of claims 1 to 6.

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