CN114040073A - Starry sky image shooting processing method and equipment and computer readable storage medium - Google Patents
Starry sky image shooting processing method and equipment and computer readable storage medium Download PDFInfo
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Abstract
The invention discloses a starry sky image shooting processing method, equipment and a computer readable storage medium, wherein the method comprises the following steps: determining an image characteristic algorithm corresponding to a preset integral image algorithm, and calculating the average brightness ratio of each star in the first star group through the image characteristic algorithm; screening the first satellite group to obtain a second satellite group of which the average brightness ratio is smaller than a preset ratio threshold, and arranging all the satellites in the second satellite group from small to large according to the average brightness ratio; and registering and aligning according to a first preset number of the stars arranged in the front and preset star catalogue data so as to fill up a second preset number of the stars which are not included in the arrangement in the shot image. The humanized starry sky image shooting processing scheme is realized, the accuracy of starry sky shooting is improved, and the shooting experience of a user is enhanced.
Description
Technical Field
The invention relates to the field of mobile communication, in particular to a starry sky image shooting processing method, starry sky image shooting processing equipment and a computer readable storage medium.
Background
In the prior art, along with the continuous development of intelligent terminal equipment, the shooting demand of a user on the equipment is higher and higher. Particularly, the starry sky shooting function based on the mobile device is widely popular with users, and a general implementation scheme is to detect the starry to be shot in the starry sky at night after combining the sensor of the terminal and the GPS information. The above scheme has derived many relevant applications, for example, existing AR virtual reality constellations on the market, but in the existing AR virtual reality constellation applications, the acquired data only comes from the sensor and GPS information of the terminal.
However, in some reproduced shooting application schemes, due to the influence of various environments, the number of the shot stars is limited, and the existing star map generated through the AR virtual reality has a large difference from the real star map, so that the accuracy is poor, and the actual experience still needs to be improved.
Disclosure of Invention
In order to solve the technical defects in the prior art, the invention provides a starry sky image shooting processing method, which comprises the following steps:
and acquiring a mask image corresponding to the shot image, and detecting according to a preset integral image algorithm to obtain a first star group in the mask image.
Determining an image feature algorithm corresponding to the preset integral graph algorithm, and calculating the average brightness ratio of each star in the first star group through the image feature algorithm, wherein the average brightness ratio is the ratio of the upper area integral and the lower area integral in the pixel range of each star.
And screening the first satellite group to obtain a second satellite group with the average brightness ratio smaller than a preset ratio threshold, and arranging the satellites in the second satellite group from small to large according to the average brightness ratio.
And registering and aligning according to a first preset number of the stars arranged in the front and preset star catalogue data so as to fill up a second preset number of the stars which are not included in the arrangement in the shot image.
Optionally, the acquiring a mask image corresponding to the shot image, and detecting according to a preset integral image algorithm to obtain a first star group in the mask image includes:
and acquiring a binary mask image of the shot image.
And carrying out corrosion treatment on the binary mask image to enlarge a black area in the binary mask image so as to obtain the processed mask image.
Optionally, the determining an image feature algorithm corresponding to the preset integral map algorithm, and calculating an average luminance ratio of each star in the first star group through the image feature algorithm, where the average luminance ratio is a ratio of an upper area integral and a lower area integral within a pixel range of each star itself, includes:
and determining an edge feature algorithm corresponding to the preset integral graph algorithm in the image feature algorithm.
And calculating the average brightness ratio of each star in the first star group according to the edge feature algorithm.
Optionally, the determining an image feature algorithm corresponding to the preset integral map algorithm, and calculating an average luminance ratio of each star in the first star group through the image feature algorithm, where the average luminance ratio is a ratio of an upper area integral and a lower area integral within a pixel range of each star itself, further includes:
in the pixel range of each star body, the high brightness is taken as an upper area, and the low brightness is taken as a lower area.
And acquiring an upper area integral of the upper area and a lower area integral of the lower area, and taking the ratio of the upper area integral to the lower area integral as the average brightness ratio.
Optionally, the screening of the first constellation group to obtain a second constellation group with the average brightness ratio smaller than a preset ratio threshold, and arranging the stars in the second constellation group from small to large according to the average brightness ratio includes:
identifying a background object in the captured image.
And determining a first ratio threshold according to the object type of the background object.
Optionally, the screening of the first constellation group to obtain a second constellation group with the average brightness ratio smaller than a preset ratio threshold, and arranging the stars in the second constellation group from small to large according to the average brightness ratio, further includes:
presetting a second ratio threshold smaller than the first ratio threshold.
And screening the first star group to obtain a second star group of which the average brightness ratio is greater than the second ratio threshold and smaller than the first ratio threshold.
Optionally, the registering and aligning according to a first preset number of stars arranged in the front and preset star table data to fill up a second preset number of stars not included in the arrangement in the captured image includes:
the front arranged stars are extracted and registered and aligned with the star catalogue data.
And determining a second preset number of the stars to be complemented according to the registration and the result thereof.
Optionally, the registering and aligning according to a first preset number of stars arranged in the front and preset star table data to fill up a second preset number of stars not included in the arrangement in the captured image further includes:
and screening the stars to be added in the sky area in the mask image from the stars in the second preset number.
And filling up the star bodies to be added in the shot image.
The invention also provides starry sky image shooting processing equipment, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the computer program realizes the steps of the starry sky image shooting processing method according to any one of the above items when being executed by the processor.
The invention also provides a computer readable storage medium, which stores a starry sky image shooting processing program, and when the starry sky image shooting processing program is executed by a processor, the starry sky image shooting processing method realizes the steps of the starry sky image shooting processing method.
By implementing the starry sky image shooting processing method, the starry sky image shooting processing equipment and the computer readable storage medium, a mask image corresponding to a shot image is obtained, and a first star group in the mask image is obtained through detection according to a preset integral image algorithm; determining an image feature algorithm corresponding to the preset integral map algorithm, and calculating the average brightness ratio of each star in the first star group through the image feature algorithm, wherein the average brightness ratio is the ratio of upper area integral and lower area integral in the pixel range of each star; screening the first satellite group to obtain a second satellite group of which the average brightness ratio is smaller than a preset ratio threshold, and arranging all the satellites in the second satellite group from small to large according to the average brightness ratio; and registering and aligning according to a first preset number of the stars arranged in the front and preset star catalogue data so as to fill up a second preset number of the stars which are not included in the arrangement in the shot image. The humanized starry sky image shooting processing scheme is realized, so that the user can complete the stars according to the actual star state in the current shot image, the accuracy of starry sky shooting is improved, and the use experience of the user on the starry sky shooting function is enhanced.
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 a mobile terminal according to the present invention;
fig. 2 is a communication network system architecture diagram provided by an embodiment of the present invention;
FIG. 3 is a flowchart of a starry sky image capture processing method according to a first embodiment of the present invention;
FIG. 4 is a flowchart of a second embodiment of a starry sky image capture process of the present invention;
FIG. 5 is a flowchart of a starry sky image capture processing method according to a third embodiment of the present invention;
FIG. 6 is a flowchart of a starry sky image capture processing method according to a fourth embodiment of the present invention;
FIG. 7 is a flowchart of a fifth embodiment of a starry sky image capture processing method of the present invention;
FIG. 8 is a flowchart of a starry sky image capture processing method according to a sixth embodiment of the present invention;
FIG. 9 is a flowchart of a starry sky image capture processing method according to a seventh embodiment of the present invention;
FIG. 10 is a flowchart of an eighth embodiment of a starry sky image capture processing method of the present invention;
FIG. 11 is an integration diagram of a starry sky image capture processing method according to a first embodiment of the present invention;
fig. 12 is another integration diagram of the starry sky image capturing processing method according to the first 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 processor 1041 Processing image data of still pictures or video obtained by an image capturing device (e.g., a camera) in a video capturing mode or an image capturing mode. The processed image frames may be displayed on the display unit 106. The image frames processed by the graphic processor 1041 may be stored in the memory 109 (or other storage medium) or transmitted via the radio frequency unit 101 or the WiFi module 102. The microphone 1042 may receive sounds (audio data) via the microphone 1042 in a phone call mode, a recording mode, a voice recognition mode, or the like, and may be capable of processing such sounds into audio data. The processed audio (voice) data may be converted into a format output transmittable to a mobile communication base station via the radio frequency unit 101 in case of a phone call mode. The microphone 1042 may implement various types of noise cancellation (or suppression) algorithms to cancel (or suppress) noise or interference generated in the course of receiving and transmitting audio signals.
The mobile terminal 100 also includes at least one sensor 105, such as a light sensor, a motion sensor, and other sensors. Specifically, the light sensor includes an ambient light sensor that can adjust the brightness of the display panel 1061 according to the brightness of ambient light, and a proximity sensor that can turn off the display panel 1061 and/or a backlight when the mobile terminal 100 is moved to the ear. As one of the motion sensors, the accelerometer sensor can detect the magnitude of acceleration in each direction (generally, three axes), can detect the magnitude and direction of gravity when stationary, and can be used for applications of recognizing the posture of a mobile phone (such as horizontal and vertical screen switching, related games, magnetometer posture calibration), vibration recognition related functions (such as pedometer and tapping), and the like; as for other sensors such as a fingerprint sensor, a pressure sensor, an iris sensor, a molecular sensor, a gyroscope, a barometer, a hygrometer, a thermometer, and an infrared sensor, which can be configured on the mobile phone, further description is omitted here.
The display unit 106 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.
Example one
Fig. 3 is a flowchart of a starry sky image capturing processing method according to a first embodiment of the present invention. A starry sky image shooting processing method comprises the following steps:
and S1, acquiring a mask image corresponding to the shot image, and detecting according to a preset integral image algorithm to obtain a first star group in the mask image.
S2, determining an image feature algorithm corresponding to the preset integral map algorithm, and calculating the average brightness ratio of each star in the first star group through the image feature algorithm, wherein the average brightness ratio is the ratio of the upper area integral and the lower area integral in the pixel range of each star.
S3, screening the first star group to obtain a second star group with the average brightness ratio smaller than a preset ratio threshold, and arranging the stars in the second star group from small to large according to the average brightness ratio.
And S4, registering and aligning according to a first preset number of the stars arranged in the front and preset star catalogue data so as to fill up a second preset number of the stars which are not contained in the arrangement in the shot image.
In the embodiment, firstly, a preview image is acquired, and a sky area of the image is extracted by using depth learning; then, detecting the positions of the stars in the sky area by using haar characteristics; then, computing brightness information of the stars by utilizing haar (a machine-learned image processing algorithm) characteristics, and sequencing the brightness of the stars; and finally, registering and aligning the stars generated by the astronomical table by using the detected stars, and completing the stars which are not shot.
Optionally, in this embodiment, the stars are detected through the integral map and the haar feature. The Haar-like feature used in this embodiment is a feature description operator commonly used in the field of computer vision. Specifically, the haar feature can be customized according to requirements, and is a common edge haar feature, a line haar feature, a central point haar feature and the like. Optionally, the edge haar feature is adopted in the present embodiment, and the calculation of the haar feature of the present embodiment is based on an integral graph, for example, please refer to the integral diagram shown in fig. 11. In the score map, at point 1, score SAT1 ═ sum (ra) SAT1 ═ sum (ra), at point 2, score SAT2 ═ sum (ra) + sum (rb) SAT2 ═ sum (ra) + sum (rb), at point 3, score SAT3 ═ sum (ra) + sum (rc) SAT3 ═ sum (ra) + sum (rc), and at point 4, score SAT4 ═ sum (ra) + sum (rb) + sum (rc) SAT4 ═ sum (ra) + sum (rc). In this embodiment, based on the above integral calculation manner, in order to calculate the sum of rectangular pixels in the area where the star is located, for example, the sum (integral) of pixel values of all points in the area Rd can be expressed as: sum (rd) ═ SAT1+ SAT4-SAT2-SAT 3. Similarly, please refer to the integration diagram shown in fig. 12, wherein the above formula can be applied to the Sum _ a region and the Sum _ B region based on the haar feature. In particular, in the present embodiment, a value T is defined, where the value T is an average luminance ratio of upper and lower regions of the haar feature. It can be seen that the larger T, the brighter the relative brightness of Sum _ a is determined.
The method has the advantages that a mask image corresponding to a shot image is obtained, and a first star group in the mask image is obtained through detection according to a preset integral image algorithm; determining an image feature algorithm corresponding to the preset integral map algorithm, and calculating the average brightness ratio of each star in the first star group through the image feature algorithm, wherein the average brightness ratio is the ratio of upper area integral and lower area integral in the pixel range of each star; screening the first satellite group to obtain a second satellite group of which the average brightness ratio is smaller than a preset ratio threshold, and arranging all the satellites in the second satellite group from small to large according to the average brightness ratio; and registering and aligning according to a first preset number of the stars arranged in the front and preset star catalogue data so as to fill up a second preset number of the stars which are not included in the arrangement in the shot image. The humanized starry sky image shooting processing scheme is realized, so that the user can complete the stars according to the actual star state in the current shot image, the accuracy of starry sky shooting is improved, and the use experience of the user on the starry sky shooting function is enhanced.
Example two
Fig. 4 is a flowchart of a second embodiment of the starry sky image shooting processing method according to the present invention, and based on the above embodiment, the acquiring a mask image corresponding to a shot image, and detecting and obtaining a first star group in the mask image according to a preset integral image algorithm includes:
and S11, acquiring a binary mask image of the shot image.
And S12, performing erosion processing on the binary mask image to enlarge a black area in the binary mask image, and obtaining the processed mask image.
Optionally, in this embodiment, an erosion processing manner of an enode (one image processing manner) is adopted to perform morphological erosion processing on the binary mask image, so as to enlarge a black area in the binary mask image, and obtain the processed mask image, thereby avoiding identifying a non-sky area as a sky area.
The method has the advantages that the binary mask image of the shot image is obtained; and carrying out corrosion treatment on the binary mask image to enlarge a black area in the binary mask image so as to obtain the processed mask image. The humanized starry sky image shooting processing scheme is realized, so that the user can complete the stars according to the actual star state in the current shot image, the accuracy of starry sky shooting is improved, and the use experience of the user on the starry sky shooting function is enhanced.
EXAMPLE III
Fig. 5 is a flowchart of a starry sky image shooting processing method according to a third embodiment of the present invention, where based on the above embodiments, the determining an image feature algorithm corresponding to the preset integral map algorithm, and calculating an average luminance ratio of each star in the first star group through the image feature algorithm, where the average luminance ratio is a ratio of an upper area integral and a lower area integral of each star within a pixel range of the star itself, and the method includes:
and S21, determining an edge feature algorithm corresponding to the preset integral image algorithm in the image feature algorithms.
And S22, calculating the average brightness ratio of each star in the first star group according to the edge feature algorithm.
The method has the advantages that the edge feature algorithm corresponding to the preset integral image algorithm is determined in the image feature algorithm; and calculating the average brightness ratio of each star in the first star group according to the edge feature algorithm. The humanized starry sky image shooting processing scheme is realized, so that the user can complete the stars according to the actual star state in the current shot image, the accuracy of starry sky shooting is improved, and the use experience of the user on the starry sky shooting function is enhanced.
Example four
Fig. 6 is a flowchart of a starry sky image shooting processing method according to a fourth embodiment of the present invention, where based on the above embodiments, the determining an image feature algorithm corresponding to the preset integral map algorithm, and calculating an average luminance ratio of each star in the first star group through the image feature algorithm, where the average luminance ratio is a ratio of an upper area integral and a lower area integral of each star within a pixel range of the star, and the method further includes:
and S23, in the pixel range of each star body, taking the high brightness as an upper area and taking the low brightness as a lower area.
And S24, acquiring an upper region integral of the upper region and a lower region integral of the lower region, and taking the ratio of the upper region integral to the lower region integral as the average brightness ratio.
The method has the advantages that the high brightness is taken as the upper area and the low brightness is taken as the lower area in the pixel range of each star; and acquiring an upper area integral of the upper area and a lower area integral of the lower area, and taking the ratio of the upper area integral to the lower area integral as the average brightness ratio. The humanized starry sky image shooting processing scheme is realized, so that the user can complete the stars according to the actual star state in the current shot image, the accuracy of starry sky shooting is improved, and the use experience of the user on the starry sky shooting function is enhanced.
EXAMPLE five
Fig. 7 is a flowchart of a starry sky image shooting processing method according to a fifth embodiment of the present invention, where based on the above embodiments, the step of screening out a second star group from the first star group, where the average luminance ratio is smaller than a preset ratio threshold, and arranging stars in the second star group from small to large according to the average luminance ratio includes:
and S31, identifying the background object in the shot image.
And S32, determining a first ratio threshold according to the object type of the background object.
Alternatively, in this embodiment, when the value T is greater than a certain value, the star may be considered as a street lamp. Therefore, in order to improve the accuracy of star detection, the first ratio threshold is determined according to the object type of the background object.
Alternatively, in the present embodiment, the object types include light emitting lamp bodies such as a street lamp, a car lamp, and a signal lamp.
The method has the advantages that the background object in the shot image is identified; and determining a first ratio threshold according to the object type of the background object. The humanized starry sky image shooting processing scheme is realized, so that the user can complete the stars according to the actual star state in the current shot image, the accuracy of starry sky shooting is improved, and the use experience of the user on the starry sky shooting function is enhanced.
EXAMPLE six
Fig. 8 is a flowchart of a starry sky image shooting processing method according to a sixth embodiment of the present invention, where based on the above embodiments, the method further includes the steps of screening a first star group to obtain a second star group whose average luminance ratio is smaller than a preset ratio threshold, and arranging stars in the second star group from small to large according to the average luminance ratio:
and S33, presetting a second ratio threshold smaller than the first ratio threshold.
And S34, screening the first star group to obtain a second star group of which the average brightness ratio is greater than the second ratio threshold and smaller than the first ratio threshold.
Optionally, in this embodiment, in order to avoid that the user cannot visually recognize the stars with too low brightness, and avoid additional meaningless processing, in this step, a second ratio threshold smaller than the first ratio threshold is preset for screening the stars with low brightness.
The method has the advantages that a second ratio threshold smaller than the first ratio threshold is preset; and screening the first star group to obtain a second star group of which the average brightness ratio is greater than the second ratio threshold and smaller than the first ratio threshold. The humanized starry sky image shooting processing scheme is realized, so that the user can complete the stars according to the actual star state in the current shot image, the accuracy of starry sky shooting is improved, and the use experience of the user on the starry sky shooting function is enhanced.
EXAMPLE seven
Fig. 9 is a flowchart of a starry sky image shooting processing method according to a seventh embodiment of the present invention, and based on the foregoing embodiment, the registering and aligning according to a first preset number of stars arranged in front and preset star table data to fill up a second preset number of stars not included in the arrangement in the shot image includes:
and S41, extracting the stars arranged at the forefront, and registering and aligning the stars with the star catalogue data.
And S42, determining a second preset number of the stars to be complemented according to the registration and the result of the registration.
The method has the advantages that the method extracts the stars arranged at the forefront, and carries out registration and alignment with the star catalogue data; and determining a second preset number of the stars to be complemented according to the registration and the result thereof. The humanized starry sky image shooting processing scheme is realized, so that the user can complete the stars according to the actual star state in the current shot image, the accuracy of starry sky shooting is improved, and the use experience of the user on the starry sky shooting function is enhanced.
Example eight
Fig. 10 is a flowchart of an eighth embodiment of a starry sky image shooting processing method according to the present invention, and based on the above embodiment, the registering and aligning according to a first preset number of stars arranged in front and preset star table data to fill up a second preset number of stars not included in the arrangement in the shot image further includes:
and S43, screening the stars to be added in the sky area in the mask image from the second preset number of stars.
And S44, filling the star bodies to be added in the shot images.
Alternatively, in the present embodiment, the number of stars filled in the current image and the number of stars included in the original image are displayed in the captured image.
Optionally, in this embodiment, a selection instruction of a user is received, it is determined that the filled stars and the original stars remain in the captured image, or only the original stars remain, or a list of the filled stars and the original stars is generated, so that the user can select the stars to be displayed in the captured image.
The method has the advantages that the star to be added in the sky area in the mask image is obtained by screening the star with the second preset number; and filling up the star bodies to be added in the shot image. The humanized starry sky image shooting processing scheme is realized, so that the user can complete the stars according to the actual star state in the current shot image, the accuracy of starry sky shooting is improved, and the use experience of the user on the starry sky shooting function is enhanced.
Example nine
Based on the above embodiment, the present invention further provides a starry sky image shooting processing apparatus, which includes a memory, a processor, and a computer program stored on the memory and operable on the processor, where the computer program, when executed by the processor, implements the steps of the starry sky image shooting processing method according to any one of the above embodiments.
It should be noted that the device embodiment and the method embodiment belong to the same concept, and specific implementation processes thereof are detailed in the method embodiment, and technical features in the method embodiment are correspondingly applicable in the device embodiment, which is not described herein again.
Example ten
Based on the foregoing embodiments, the present invention further provides a computer-readable storage medium, where a starry sky image shooting processing program is stored, and when being executed by a processor, the starry sky image shooting processing program implements the steps of the starry sky image shooting processing method according to any one of the foregoing embodiments.
It should be noted that the media embodiment and the method embodiment belong to the same concept, and specific implementation processes thereof are detailed in the method embodiment, and technical features in the method embodiment are correspondingly applicable in the media embodiment, which is not described herein again.
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 (10)
1. A starry sky image shooting processing method is characterized by comprising the following steps:
acquiring a mask image corresponding to a shot image, and detecting according to a preset integral image algorithm to obtain a first star group in the mask image;
determining an image feature algorithm corresponding to the preset integral map algorithm, and calculating the average brightness ratio of each star in the first star group through the image feature algorithm, wherein the average brightness ratio is the ratio of upper area integral and lower area integral in the pixel range of each star;
screening the first satellite group to obtain a second satellite group of which the average brightness ratio is smaller than a preset ratio threshold, and arranging all the satellites in the second satellite group from small to large according to the average brightness ratio;
and registering and aligning according to a first preset number of the stars arranged in the front and preset star catalogue data so as to fill up a second preset number of the stars which are not included in the arrangement in the shot image.
2. The starry sky image shooting processing method according to claim 1, wherein the acquiring a mask image corresponding to the shot image and detecting and obtaining a first star group in the mask image according to a preset integral image algorithm includes:
acquiring a binary mask image of the shot image;
and carrying out corrosion treatment on the binary mask image to enlarge a black area in the binary mask image so as to obtain the processed mask image.
3. The starry sky image shooting processing method according to claim 2, wherein the determining an image feature algorithm corresponding to the preset integral map algorithm, and calculating an average brightness ratio of each star in the first star group through the image feature algorithm, wherein the average brightness ratio is a ratio of an upper area integral and a lower area integral within a pixel range of each star, includes:
determining an edge feature algorithm corresponding to the preset integral image algorithm in the image feature algorithm;
and calculating the average brightness ratio of each star in the first star group according to the edge feature algorithm.
4. The starry sky image shooting processing method according to claim 3, wherein the determining an image feature algorithm corresponding to the preset integral map algorithm, and calculating an average brightness ratio of each star in the first star group through the image feature algorithm, wherein the average brightness ratio is a ratio of an upper area integral and a lower area integral within a pixel range of each star, further comprising:
in the pixel range of each star, the high brightness is taken as an upper area, and the low brightness is taken as a lower area;
and acquiring an upper area integral of the upper area and a lower area integral of the lower area, and taking the ratio of the upper area integral to the lower area integral as the average brightness ratio.
5. The starry sky image shooting processing method according to claim 4, wherein the step of screening the first star group to obtain a second star group with the average brightness ratio smaller than a preset ratio threshold, and arranging stars in the second star group from small to large according to the average brightness ratio comprises:
identifying a background object in the captured image;
and determining a first ratio threshold according to the object type of the background object.
6. The starry sky image shooting processing method according to claim 5, wherein the second star group in which the average brightness ratio is smaller than a preset ratio threshold is obtained by screening the first star group, and the stars in the second star group are arranged from small to large according to the average brightness ratio, further comprising:
presetting a second ratio threshold smaller than the first ratio threshold;
and screening the first star group to obtain a second star group of which the average brightness ratio is greater than the second ratio threshold and smaller than the first ratio threshold.
7. The starry sky image shooting processing method according to claim 6, wherein the registering and aligning according to a first preset number of stars arranged in front with preset star table data to fill up a second preset number of stars not included in the arrangement in the shot image comprises:
extracting the stars arranged at the forefront, and registering and aligning with the star catalogue data;
and determining a second preset number of the stars to be complemented according to the registration and the result thereof.
8. The starry sky image capture processing method as claimed in claim 7, wherein the registering and aligning according to a first preset number of stars arranged in front with preset star table data to fill up a second preset number of stars not included in the arrangement in the captured image further comprises:
screening the stars to be added in the sky area in the mask image from the stars in the second preset number;
and filling up the star bodies to be added in the shot image.
9. A starry sky image capture processing apparatus, characterized in that the apparatus comprises a memory, a processor and a computer program stored on the memory and executable on the processor, the computer program, when executed by the processor, implementing the steps of the starry sky image capture processing method as claimed in any one of claims 1 to 8.
10. A computer-readable storage medium, characterized in that a starry sky image capture processing program is stored thereon, which when executed by a processor implements the steps of the starry sky image capture processing method as claimed in any one of claims 1 to 8.
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