CN107742279B - Image processing method, device and storage medium - Google Patents
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Abstract
The embodiment of the invention provides an image processing method, which comprises the following steps: processing an image based on a time domain and a frequency domain to obtain low-frequency information of the image; and carrying out filtering processing on the low-frequency information of the image. The embodiment of the invention also provides an image processing device and a storage medium. By the embodiment of the invention, the image can be subjected to noise reduction processing in a targeted manner on the premise of keeping the detail information of the image.
Description
Technical Field
The present invention relates to image processing technologies, and in particular, to an image processing method, an image processing apparatus, and a storage medium.
Background
In the related art, when an image is processed, the image is processed in a time domain or a frequency domain, noise in the image cannot be processed in a targeted manner, and therefore, the noise reduction effect on the image is not ideal.
Disclosure of Invention
In view of the above, embodiments of the present invention provide an image processing method, an image processing apparatus, and a storage medium to solve the problems in the prior art.
The embodiment of the invention provides an image processing method, which comprises the following steps:
processing an image based on a time domain and a frequency domain to obtain low-frequency information of the image;
and carrying out filtering processing on the low-frequency information.
In the foregoing solution, the processing an image based on a time domain and a frequency domain to obtain low-frequency information of the image includes:
processing the image based on wavelet transformation to obtain first high-frequency information of the image and first low-frequency information of the image;
determining first low-frequency information of the image as low-frequency information of the image.
In the above scheme, the method further comprises:
processing first low-frequency information of the image based on wavelet transformation to obtain second high-frequency information of the image and second low-frequency information of the image;
and updating the low-frequency information of the image based on the second low-frequency information of the image.
In the foregoing solution, the filtering the low frequency information of the image includes:
selecting odd pixels which are adjacent in sequence by taking each pixel in the low-frequency information of the image as an initial pixel;
and carrying out filtering processing on the odd number of pixel points.
In the foregoing solution, the filtering the odd number of pixels includes:
determining a first average pixel value of the odd number of pixel points;
comparing the pixel values of the pixels except the central pixel in the odd number of pixels with the first average pixel value respectively to obtain a pixel set with the pixel value larger than the first average pixel value;
determining a second average pixel value of the set of pixel points;
and updating the pixel value of the central pixel point based on the second pixel value.
An embodiment of the present invention further provides an image processing apparatus, including: a processor, a memory, and a communication bus;
the communication bus is used for realizing connection communication between the processor and the memory;
the processor is used for executing the image processing program stored in the memory so as to realize the following steps:
processing an image based on a time domain and a frequency domain to obtain low-frequency information of the image;
and carrying out filtering processing on the low-frequency information.
In the foregoing solution, the processor is specifically configured to execute the image processing program to implement the following steps:
processing the image based on wavelet transformation to obtain first high-frequency information of the image and first low-frequency information of the image;
processing first low-frequency information of the image based on wavelet transformation to obtain second high-frequency information of the image and second low-frequency information of the image;
and determining second low-frequency information of the image as the low-frequency information of the image.
In the foregoing solution, the processor is specifically configured to execute the image processing program to implement the following steps:
selecting odd pixels which are adjacent in sequence by taking each pixel in the low-frequency information of the image as an initial pixel;
and carrying out filtering processing on the odd number of pixel points.
In the foregoing solution, the processor is specifically configured to execute the image processing program to implement the following steps:
determining a first average pixel value of the odd number of pixel points;
comparing the pixel values of the pixels except the central pixel in the odd number of pixels with the first average pixel value respectively to obtain a pixel set with the pixel value larger than the first average pixel value;
determining a second average pixel value of the set of pixel points;
and updating the pixel value of the central pixel point based on the second pixel value.
An embodiment of the present invention further provides a storage medium, where the storage medium stores one or more programs, and the one or more programs are executable by one or more processors to implement the following steps:
processing an image based on a time domain and a frequency domain to obtain low-frequency information of the image;
and carrying out filtering processing on the low-frequency information.
The image processing method, the image processing device and the storage medium provided by the embodiment of the invention process the image based on the time domain and the frequency domain to obtain the low-frequency information of the image; and carrying out filtering processing on the low-frequency information. Therefore, when the image is processed based on the frequency domain, the embodiment of the invention can keep the detail information of the image; by acquiring the low-frequency information of the image and independently processing the low-frequency information of the image, the image can be subjected to targeted noise reduction processing.
In the embodiment of the invention, when the low-frequency information of the image is filtered, the filtering is carried out in an iterative mode, so that the filtering precision is further improved, and the noise reduction effect of the image is further improved.
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Fig. 1 is a schematic diagram of a hardware structure of a mobile terminal according to the present invention;
FIG. 2 is a diagram of a communication network system architecture according to the present invention;
FIG. 3 is a schematic diagram of a basic processing flow of an image processing method according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a processing flow of filtering odd-numbered pixel points according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of an image processing apparatus according to an embodiment of the present invention.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In the following description, suffixes such as "module", "component", or "unit" used to denote elements are used only for facilitating the explanation of the present invention, and have no specific meaning in itself. Thus, "module", "component" or "unit" may be used mixedly.
In the embodiment of the present invention, the image processing apparatus for implementing the image processing method may be any electronic device, such as a server, a terminal, and the like; the image to be processed may be stored in a storage area of the electronic device itself, or may be transmitted to the electronic device by another device through a network.
When the electronic device is a terminal, the terminal may be implemented in various forms. For example, the terminal described in the present invention may include a mobile terminal such as a mobile phone, a tablet computer, a notebook computer, a palmtop computer, a Personal Digital Assistant (PDA), a Portable Media Player (PMP), a navigation device, a wearable device, a smart band, a pedometer, and the like, and a fixed terminal such as a digital TV, a desktop computer, and the like.
The following description will be given by way of example of a mobile terminal, and it will be understood by those skilled in the art that the construction according to the embodiment of the present invention can be applied to a fixed type terminal, in addition to elements particularly used for mobile purposes.
Referring to fig. 1, which is a schematic diagram of a hardware structure of a mobile terminal for implementing various embodiments of the present invention, the mobile terminal 100 may include: RF (Radio Frequency) unit 101, WiFi module 102, audio output unit 103, a/V (audio/video) input unit 104, sensor 105, display unit 106, user input unit 107, interface unit 108, memory 109, processor 110, and power supply 111. Those skilled in the art will appreciate that the mobile terminal architecture shown in fig. 1 is not intended to be limiting of mobile terminals, which may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.
The following describes each component of the mobile terminal in detail with reference to fig. 1:
the Radio Frequency unit 101 may be configured to receive and transmit signals during a message transmission or call, specifically, receive downlink information of a base station and then process the received downlink information to the processor 110, and transmit uplink data to the base station, in General, the Radio Frequency unit 101 includes, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier, a duplexer, and the like, and in addition, the Radio Frequency unit 101 may further communicate with a network and other devices through wireless communication, and the wireless communication may use any communication standard or protocol, including, but not limited to, GSM (Global System of Mobile communication), GPRS (General Packet Radio Service), CDMA2000(Code Division Multiple Access 2000), WCDMA (Wideband Code Division Multiple Access ), TD-SCDMA (Synchronous Time Division Multiple Access, Code Division Multiple Access, Time Division Multiple Access, etc., TDD — Time Division Multiple Access, L Time Division Multiple Access, etc.
WiFi belongs to short-distance wireless transmission technology, and the mobile terminal can help a user to receive and send e-mails, browse webpages, access streaming media and the like through the WiFi module 102, and provides wireless broadband internet access for the user. Although fig. 1 shows the WiFi module 102, it is understood that it does not belong to the essential constitution of the mobile terminal, and may be omitted entirely as needed within the scope not changing the essence of the invention.
The audio output unit 103 may convert audio data received by the radio frequency unit 101 or the WiFi module 102 or stored in the memory 109 into an audio signal and output as sound when the mobile terminal 100 is in a call signal reception mode, a call mode, a recording mode, a voice recognition mode, a broadcast reception mode, or the like. Also, the audio output unit 103 may also provide audio output related to a specific function performed by the mobile terminal 100 (e.g., a call signal reception sound, a message reception sound, etc.). The audio output unit 103 may include a speaker, a buzzer, and the like.
The a/V input unit 104 is used to receive audio or video signals. The a/V input Unit 104 may include a Graphics Processing Unit (GPU) 1041 and a microphone 1042, the Graphics processor 1041 Processing image data of still pictures or video obtained by an image capturing device (e.g., a camera) in a video capturing mode or an image capturing mode. The processed image frames may be displayed on the display unit 106. The image frames processed by the graphic processor 1041 may be stored in the memory 109 (or other storage medium) or transmitted via the radio frequency unit 101 or the WiFi module 102. The microphone 1042 may receive sound (audio data) via the microphone 1042 in an operation mode such as a phone call mode, a recording mode, a voice recognition mode, and the like, and can process such sound into audio data. The processed audio (voice) data may be converted into a format output transmittable to a mobile communication base station via the radio frequency unit 101 in case of a phone call mode. The microphone 1042 may implement various types of noise cancellation (or suppression) algorithms to cancel (or suppress) noise or interference generated in the course of receiving and transmitting audio signals.
The mobile terminal 100 also includes at least one sensor 105, such as a light sensor, a motion sensor, and other sensors. Specifically, the light sensor includes an ambient light sensor that can adjust the brightness of the display panel 1061 according to the brightness of ambient light, and a proximity sensor that can turn off the display panel 1061 and/or a backlight when the mobile terminal 100 is moved to the ear. As one of the motion sensors, the accelerometer sensor can detect the magnitude of acceleration in each direction (generally, three axes), can detect the magnitude and direction of gravity when stationary, and can be used for applications of recognizing the posture of a mobile phone (such as horizontal and vertical screen switching, related games, magnetometer posture calibration), vibration recognition related functions (such as pedometer and tapping), and the like; as for other sensors such as a fingerprint sensor, a pressure sensor, an iris sensor, a molecular sensor, a gyroscope, a barometer, a hygrometer, a thermometer, and an infrared sensor, which can be configured on the mobile phone, further description is omitted here.
The Display unit 106 may include a Display panel 1061, and the Display panel 1061 may be configured in the form of a liquid Crystal Display (L acquired Crystal Display, L CD), an Organic light-Emitting Diode (O L ED), or the like.
The user input unit 107 may be used to receive input numeric or character information and generate key signal inputs related to user settings and function control of the mobile terminal. Specifically, the user input unit 107 may include a touch panel 1071 and other input devices 1072. The touch panel 1071, also referred to as a touch screen, may collect a touch operation performed by a user on or near the touch panel 1071 (e.g., an operation performed by the user on or near the touch panel 1071 using a finger, a stylus, or any other suitable object or accessory), and drive a corresponding connection device according to a predetermined program. The touch panel 1071 may include two parts of a touch detection device and a touch controller. The touch detection device detects the touch direction of a user, detects a signal brought by touch operation and transmits the signal to the touch controller; the touch controller receives touch information from the touch sensing device, converts the touch information into touch point coordinates, sends the touch point coordinates to the processor 110, and can receive and execute commands sent by the processor 110. In addition, the touch panel 1071 may be implemented in various types, such as a resistive type, a capacitive type, an infrared ray, and a surface acoustic wave. In addition to the touch panel 1071, the user input unit 107 may include other input devices 1072. In particular, other input devices 1072 may include, but are not limited to, one or more of a physical keyboard, function keys (e.g., volume control keys, switch keys, etc.), a trackball, a mouse, a joystick, and the like, and are not limited to these specific examples.
Further, the touch panel 1071 may cover the display panel 1061, and when the touch panel 1071 detects a touch operation thereon or nearby, the touch panel 1071 transmits the touch operation to the processor 110 to determine the type of the touch event, and then the processor 110 provides a corresponding visual output on the display panel 1061 according to the type of the touch event. Although the touch panel 1071 and the display panel 1061 are shown in fig. 1 as two separate components to implement the input and output functions of the mobile terminal, in some embodiments, the touch panel 1071 and the display panel 1061 may be integrated to implement the input and output functions of the mobile terminal, and is not limited herein.
The interface unit 108 serves as an interface through which at least one external device is connected to the mobile terminal 100. For example, the external device may include a wired or wireless headset port, an external power supply (or battery charger) port, a wired or wireless data port, a memory card port, a port for connecting a device having an identification module, an audio input/output (I/O) port, a video I/O port, an earphone port, and the like. The interface unit 108 may be used to receive input (e.g., data information, power, etc.) from external devices and transmit the received input to one or more elements within the mobile terminal 100 or may be used to transmit data between the mobile terminal 100 and external devices.
The memory 109 may be used to store software programs as well as various data. The memory 109 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone, and the like. Further, the memory 109 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device.
The processor 110 is a control center of the mobile terminal, connects various parts of the entire mobile terminal using various interfaces and lines, and performs various functions of the mobile terminal and processes data by operating or executing software programs and/or modules stored in the memory 109 and calling data stored in the memory 109, thereby performing overall monitoring of the mobile terminal. Processor 110 may include one or more processing units; preferably, the processor 110 may integrate an application processor, which mainly handles operating systems, user interfaces, application programs, etc., and a modem processor, which mainly handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 110.
The mobile terminal 100 may further include a power supply 111 (e.g., a battery) for supplying power to various components, and preferably, the power supply 111 may be logically connected to the processor 110 via a power management system, so as to manage charging, discharging, and power consumption management functions via the power management system.
Although not shown in fig. 1, the mobile terminal 100 may further include a bluetooth module or the like, which is not described in detail herein.
In order to facilitate understanding of the embodiments of the present invention, a communication network system on which the mobile terminal of the present invention is based is described below.
Referring to fig. 2, fig. 2 is an architecture diagram of a communication Network system according to an embodiment of the present invention, the communication Network system is L TE system of universal mobile telecommunications technology, and the L TE system includes a UE (User Equipment) 201, an E-UTRAN (Evolved UMTS Terrestrial Radio Access Network) 202, an EPC (Evolved Packet Core) 203, and an IP service 204 of an operator, which are in communication connection in sequence.
Specifically, the UE201 may be the terminal 100 described above, and is not described herein again.
The E-UTRAN202 includes eNodeB2021 and other eNodeBs 2022, among others. Among them, the eNodeB2021 may be connected with other eNodeB2022 through backhaul (e.g., X2 interface), the eNodeB2021 is connected to the EPC203, and the eNodeB2021 may provide the UE201 access to the EPC 203.
The EPC203 may include an MME (Mobility Management Entity) 2031, an HSS (Home Subscriber Server) 2032, other MMEs 2033, an SGW (Serving gateway) 2034, a PGW (PDN gateway) 2035, and a PCRF (Policy and charging functions Entity) 2036, and the like. The MME2031 is a control node that handles signaling between the UE201 and the EPC203, and provides bearer and connection management. HSS2032 is used to provide registers to manage functions such as home location register (not shown) and holds subscriber specific information about service characteristics, data rates, etc. All user data may be sent through SGW2034, PGW2035 may provide IP address assignment for UE201 and other functions, and PCRF2036 is a policy and charging control policy decision point for traffic data flow and IP bearer resources, which selects and provides available policy and charging control decisions for a policy and charging enforcement function (not shown).
The IP services 204 may include the internet, intranets, IMS (IP Multimedia Subsystem), or other IP services, among others.
Although L TE system is described as an example, it should be understood by those skilled in the art that the present invention is not limited to L TE system, but also applicable to other wireless communication systems, such as GSM, CDMA2000, WCDMA, TD-SCDMA, and future new network systems.
Based on the above mobile terminal hardware structure and communication network system, the present invention provides various embodiments of the method.
Example one
A processing flow diagram of an image processing method according to an embodiment of the present invention, as shown in fig. 3, includes the following steps:
step S101, processing the image based on the time domain and the frequency domain, and acquiring the low-frequency information of the image.
In an optional embodiment, the image processing device processes the image based on wavelet transformation, and acquires first high-frequency information and first low-frequency information of the image; if all pixel points in the image are subjected to subtraction on the pixel values of two adjacent pixel points, first high-frequency information of the image is obtained; and adding the pixel values of two adjacent pixel points to obtain first low-frequency information of the image. Processing the first low-frequency information of the image based on wavelet transformation to obtain second high-frequency information of the image and second low-frequency information of the image; if so, subtracting the pixel values of two adjacent pixel points from all the pixel points corresponding to the first low-frequency information to obtain second high-frequency information of the image; adding the pixel values of two adjacent pixel points to obtain second low-frequency information of the image; and taking the second low-frequency information as the low-frequency information of the image. Wherein the low frequency information of the image is used to characterize noise information in the image.
Here, when the low-frequency information of the image is acquired, the position information corresponding to the low-frequency information of the image can be acquired, so that when the image is subsequently subjected to filtering processing, the adjacent pixel points can be acquired based on the position information.
It should be noted that wavelet transform is a time-scale analysis method of signals, has the characteristic of multi-resolution analysis, and has the capability of representing the local characteristics of signals in both time domain and frequency domain, and is a time domain and frequency domain localization analysis method with fixed window size but variable shape, and variable time window and frequency window. The method has the characteristics of higher frequency resolution and time resolution in the low-frequency part of the image and higher time resolution and lower frequency resolution in the high-frequency part of the image. Therefore, by performing wavelet transform processing on an image, detailed information in the image can be retained.
According to the embodiment of the invention, the low-frequency information in the low-frequency information of the image can be obtained by performing wavelet transformation processing on the image twice, so that the precision of obtaining the noise in the image is improved, the noise is conveniently processed in a targeted manner, and the noise reduction effect of the image is further improved.
And step S102, filtering the low-frequency information of the image.
In an optional embodiment, the image processing apparatus selects an odd number of sequentially adjacent pixels with each pixel in the low-frequency information of the image as an initial pixel, and performs filtering processing on the odd number of pixels. Here, the number of the selected pixels may be preset, for example, 5, 7, or 9.
Taking the example that the low-frequency information of the image corresponds to M rows and N columns of pixel points, filtering processing is performed on the M rows of pixel points first, and then filtering processing is performed on the N columns of pixel points. Therefore, iterative filtering processing of the pixel points is realized, and the precision of the filtering processing is improved.
In an optional embodiment, a processing flow of performing filtering processing on odd number of pixel points, as shown in fig. 4, includes the following steps:
step S1021, determining a first average pixel value of odd pixels.
In an optional implementation manner, the image processing device determines the pixel value of each pixel point respectively, and adds the pixel values of all the pixel points to obtain a total pixel value; and dividing the total pixel value by the number of the pixel points to obtain a first average pixel value.
Step S1022, comparing the pixel values of the pixels other than the central pixel among the odd pixels with the first average pixel value, respectively.
Taking the selected pixels as a first pixel, a second pixel, a third pixel, a fourth pixel and a fifth pixel as examples, the first pixel is an initial pixel, the third pixel is a central pixel, and the fifth pixel is a termination pixel; the image processing device compares the pixel values of the first pixel point, the second pixel point, the fourth pixel point and the fifth pixel point with the first average pixel value respectively to obtain a pixel point set with the pixel value larger than the first average pixel value. The pixel point set with the pixel value larger than the first average pixel value obtained in the embodiment of the invention comprises a first pixel point, a second pixel point and a fifth pixel point. When the pixel values of the pixel points except the central pixel point are respectively compared with the first average pixel value, the pixel points which are smaller than the first average pixel value are considered as pixel points which can be used for averaging, and the pixel points do not need to be further processed.
In step S1023, a second average pixel value of the pixel point set is determined.
In an optional embodiment, the image processing apparatus adds the pixel values of the first pixel point, the second pixel point and the fifth pixel point to obtain a total pixel value; and dividing the total pixel value by the number 3 of the pixel points to obtain a second average pixel value.
Step S1024, based on the second pixel value, updating the pixel value of the central pixel point.
In an optional embodiment, the image processing apparatus updates the pixel value of the third pixel point to the second average pixel value, that is, replaces the average pixel value of the third pixel point with the second average pixel value.
Based on the above implementation process of the image processing apparatus shown in fig. 4, in which the image processing apparatus performs filtering processing on odd number of pixels, it can be understood that the image processing apparatus uses five pixels as a group, and the process of processing each row of pixels is as follows: the method comprises the steps of dividing first to fifth pixel points into a first group of pixel points, and processing five pixel points included in the first group of pixel points to update the pixel value of a third pixel point. Dividing the second pixel point to the fifth pixel point into a second group of pixel points, and when five pixel points included in the second group of pixel points are processed, the pixel value of the used third pixel point is the updated pixel value of the third pixel point; namely, if the pixel value of the pixel point involved in the image processing process is updated, the updated pixel value is adopted. Therefore, iterative filtering of the image is realized, and the noise reduction effect of the image is improved.
Similarly, when the image processing apparatus processes each row of pixels, the pixel value of each pixel included in each row of pixels is updated when the pixel is processed in a row unit, and the updated pixel value is used.
Example two
A processing flow of the image processing method provided by the second embodiment of the present invention is similar to the processing flow of the image processing method shown in fig. 3, except that when acquiring low-frequency information of an image, the image processing apparatus processes the image based on wavelet transformation to acquire first high-frequency information and first low-frequency information of the image; if all pixel points in the image are subjected to subtraction on the pixel values of two adjacent pixel points, first high-frequency information of the image is obtained; adding the pixel values of two adjacent pixel points to obtain first low-frequency information of the image, and taking the first low-frequency information as the low-frequency information of the image.
EXAMPLE III
In order to implement the foregoing image processing method embodiment of the present invention, a third embodiment of the present invention further provides an image processing apparatus, where a schematic structural diagram of the image processing apparatus is shown in fig. 5, and the image processing apparatus includes: a processor 301, a memory 302, and a communication bus 303; wherein the content of the first and second substances,
the communication bus 303 is used for realizing connection communication between the processor 301 and the memory 302;
the processor 301 is configured to execute the image processing program stored in the memory 302 to implement the following steps:
processing an image based on a time domain and a frequency domain to obtain low-frequency information of the image;
and carrying out filtering processing on the low-frequency information of the image.
In a preferred embodiment, the processor 301 is specifically configured to process the image based on a wavelet transform, to obtain first high frequency information of the image and first low frequency information of the image;
determining first low-frequency information of the image as low-frequency information of the image.
In a preferred embodiment, the processor 301 is further configured to process the first low-frequency information of the image based on a wavelet transform, to obtain second high-frequency information of the image and second low-frequency information of the image; and updating the low-frequency information of the image based on the second low-frequency information of the image.
In a preferred embodiment, the processor 301 is specifically configured to select odd number of pixels that are adjacent in sequence by using each pixel in the low-frequency information of the image as an initial pixel;
and carrying out filtering processing on the odd number of pixel points.
In a preferred embodiment, the processor 301 is specifically configured to determine a first average pixel value of the odd number of pixels;
comparing the pixel values of the pixels except the central pixel in the odd number of pixels with the first average pixel value respectively to obtain a pixel set with the pixel value larger than the first average pixel value;
determining a second average pixel value of the set of pixel points;
and updating the pixel value of the central pixel point based on the second pixel value.
In the embodiment of the present invention, the functions executed by the processor 301 in the image processing apparatus may be implemented by a Central Processing Unit (CPU), a microprocessor unit (MPU), a Digital Signal Processor (DSP), or a programmable gate array (FPGA) located on the same electronic device.
Example four
To achieve the foregoing image processing apparatus and method embodiments of the present invention, a fourth embodiment of the present invention further provides a storage medium, where the storage medium stores one or more programs, and the one or more programs are executable by one or more processors to implement the following steps:
processing an image based on a time domain and a frequency domain to obtain low-frequency information of the image;
and carrying out filtering processing on the low-frequency information of the image.
In a preferred embodiment, the one or more programs are specifically executable by the one or more processors to perform the steps of:
processing the image based on wavelet transformation to obtain first high-frequency information of the image and first low-frequency information of the image;
determining first low-frequency information of the image as low-frequency information of the image.
In a preferred embodiment, the one or more programs are specifically executable by the one or more processors to perform the steps of:
processing first low-frequency information of the image based on wavelet transformation to obtain second high-frequency information of the image and second low-frequency information of the image;
and updating the low-frequency information of the image based on the second low-frequency information of the image.
In a preferred embodiment, the one or more programs are specifically executable by the one or more processors to perform the steps of:
selecting odd pixels which are adjacent in sequence by taking each pixel in the low-frequency information of the image as an initial pixel;
and carrying out filtering processing on the odd number of pixel points.
In a preferred embodiment, the one or more programs are specifically executable by the one or more processors to perform the steps of:
determining a first average pixel value of the odd number of pixel points;
comparing the pixel values of the pixels except the central pixel in the odd number of pixels with the first average pixel value respectively to obtain a pixel set with the pixel value larger than the first average pixel value;
determining a second average pixel value of the set of pixel points;
and updating the pixel value of the central pixel point based on the second pixel value.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described device embodiments are merely illustrative, for example, the division of the unit is only a logical functional division, and there may be other division ways in actual implementation, such as: multiple units or components may be combined, or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the coupling, direct coupling or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between the devices or units may be electrical, mechanical or other forms.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed on a plurality of network units; some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, all the functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately regarded as one unit, or two or more units may be integrated into one unit; the integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
Those of ordinary skill in the art will understand that: all or part of the steps for implementing the method embodiments may be implemented by hardware related to program instructions, and the program may be stored in a computer readable storage medium, and when executed, the program performs the steps including the method embodiments; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
Alternatively, the integrated unit of the present invention may be stored in a computer-readable storage medium if it is implemented in the form of a software functional module and sold or used as a separate product. Based on such understanding, the technical solutions of the embodiments of the present invention may be essentially implemented or a part contributing to the prior art may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, a ROM, a RAM, a magnetic or optical disk, or various other media that can store program code.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (3)
1. An image processing method, comprising:
processing an image based on a time domain and a frequency domain to obtain low-frequency information of the image; the processing the image based on the time domain and the frequency domain to obtain the low-frequency information of the image comprises the following steps: processing the image based on wavelet transformation to obtain first high-frequency information of the image and first low-frequency information of the image; determining first low-frequency information of the image as low-frequency information of the image; processing first low-frequency information of the image based on wavelet transformation to obtain second high-frequency information of the image and second low-frequency information of the image; updating the low-frequency information of the image based on the second low-frequency information of the image; wherein the low-frequency information of the image is used for representing noise information in the image; the high-frequency information of the image is obtained by subtracting two adjacent pixel values, and the low-frequency information of the image is obtained by adding the two adjacent pixel values;
performing filtering processing on the low-frequency information of the image, wherein the performing filtering processing on the low-frequency information of the image comprises: selecting odd pixels which are adjacent in sequence by taking each pixel in the low-frequency information of the image as an initial pixel; filtering the odd number of pixel points; wherein the performing filter processing on the odd number of pixels includes: determining a first average pixel value of the odd number of pixel points; comparing the pixel values of the pixels except the central pixel in the odd number of pixels with the first average pixel value respectively to obtain a pixel set with the pixel value larger than the first average pixel value; determining a second average pixel value of the set of pixel points; and updating the pixel value of the central pixel point based on the second average pixel value.
2. An image processing apparatus characterized by comprising: a processor, a memory, and a communication bus;
the communication bus is used for realizing connection communication between the processor and the memory;
the processor is used for executing the image processing program stored in the memory so as to realize the following steps:
processing an image based on a time domain and a frequency domain to obtain low-frequency information of the image; the processing the image based on the time domain and the frequency domain to obtain the low-frequency information of the image comprises the following steps: processing the image based on wavelet transformation to obtain first high-frequency information of the image and first low-frequency information of the image; determining first low-frequency information of the image as low-frequency information of the image; processing first low-frequency information of the image based on wavelet transformation to obtain second high-frequency information of the image and second low-frequency information of the image; updating the low-frequency information of the image based on the second low-frequency information of the image; wherein the low-frequency information of the image is used for representing noise information in the image; the high-frequency information of the image is obtained by subtracting two adjacent pixel values, and the low-frequency information of the image is obtained by adding the two adjacent pixel values;
performing filtering processing on the low-frequency information of the image, wherein the performing filtering processing on the low-frequency information of the image comprises: selecting odd pixels which are adjacent in sequence by taking each pixel in the low-frequency information of the image as an initial pixel; filtering the odd number of pixel points; wherein the performing filter processing on the odd number of pixels includes: determining a first average pixel value of the odd number of pixel points; comparing the pixel values of the pixels except the central pixel in the odd number of pixels with the first average pixel value respectively to obtain a pixel set with the pixel value larger than the first average pixel value; determining a second average pixel value of the set of pixel points; and updating the pixel value of the central pixel point based on the second average pixel value.
3. A storage medium storing one or more programs, the one or more programs executable by one or more processors to perform the steps of:
processing an image based on a time domain and a frequency domain to obtain low-frequency information of the image; processing an image based on a time domain and a frequency domain to obtain low-frequency information of the image; the processing the image based on the time domain and the frequency domain to obtain the low-frequency information of the image comprises the following steps: processing the image based on wavelet transformation to obtain first high-frequency information of the image and first low-frequency information of the image; determining first low-frequency information of the image as low-frequency information of the image; processing first low-frequency information of the image based on wavelet transformation to obtain second high-frequency information of the image and second low-frequency information of the image; updating the low-frequency information of the image based on the second low-frequency information of the image; wherein the low-frequency information of the image is used for representing noise information in the image; the high-frequency information of the image is obtained by subtracting two adjacent pixel values, and the low-frequency information of the image is obtained by adding the two adjacent pixel values;
performing filtering processing on the low-frequency information of the image, wherein the performing filtering processing on the low-frequency information of the image comprises: selecting odd pixels which are adjacent in sequence by taking each pixel in the low-frequency information of the image as an initial pixel; filtering the odd number of pixel points; wherein the performing filter processing on the odd number of pixels includes: determining a first average pixel value of the odd number of pixel points; comparing the pixel values of the pixels except the central pixel in the odd number of pixels with the first average pixel value respectively to obtain a pixel set with the pixel value larger than the first average pixel value; determining a second average pixel value of the set of pixel points; and updating the pixel value of the central pixel point based on the second average pixel value.
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