Color synchronization and color difference correction method and device for FPV unmanned aerial vehicle digital decoding

Abstract

The embodiment of the disclosure belongs to the technical field of signal processing, and particularly relates to a color synchronization and color difference correction method and device for FPV unmanned aerial vehicle digital decoding, which comprises the following steps: receiving an analog image transmission signal of an FPV unmanned aerial vehicle, digitally sampling the analog image transmission signal, and obtaining chrominance signals of a plurality of sampling points in each row; calculating a phase error of each row based on the chrominance signals of the plurality of sampling points in each row and a local oscillator signal of a receiving end device; performing phase compensation row by row based on the phase error of each row, and digitally decoding the chrominance signals after phase compensation; and performing color calibration compensation on the original CVBS signal according to the chrominance difference between the digitally decoded signal and an actual analog signal. The scheme simplifies the color synchronization process, avoids the complexity of a traditional phase-locked loop, and at the same time, through independent calculation of the phase error of each row, accurate chrominance compensation is performed, and the image quality is significantly improved.

Description

Technical Field

[0001] The embodiments of this disclosure relate to the field of signal processing technology, and more specifically, to a method, apparatus, and computer-readable storage medium storing a computer program for color synchronization and color difference correction in digital decoding of FPV unmanned aerial vehicles. Background Technology

[0002] FPV signal refers to the real-time image signal transmitted by the drone through its onboard camera in a first-person view (FPV) perspective, allowing the operator to directly observe and control the flight through a head-mounted display or screen. Traditional digital decoding of FPV signals requires the extraction of the color synchronization signal using an integrator, phase detection, and loop filtering to implement a Costa phase-locked loop (PLL) to obtain the color synchronization frequency. Figure 1 This is a schematic diagram of the traditional digital decoding color synchronization signal extraction process. (Refer to...) Figure 1 As shown, according to the FPV analog television standard, the digital representation of color signals is: ,in, and These are the two parts of the color difference signal. It is a constant related to modulation. This is the color synchronization frequency. By shifting the frequency of the color signal, it is modulated using sine and cosine signals respectively:

[0003]

[0004] These two expressions show that after frequency shifting, the two parts of the color signal ( and The components are modulated using different frequency components. Then, a low-pass filter (LBP) is used to filter out the high-frequency components, retaining only the baseband color difference signal. In this way, the color difference signals can be acquired separately. and And ultimately recover the color information of the RGB image. By analyzing... and The decoding process, combined with the output of the low-pass filter, recovers the original RGB image information.

[0005] Due to the low precision of the crystal oscillator in the drone, Offset jitter, and the receiving / decoding device uses a locked state for an extended period of time. Accumulated errors lead to a degraded performance of the phase-locked loop (PLL). The frequencies of the receiving device and the drone are not perfectly synchronized, resulting in a certain fixed frequency error, which further exacerbates the PLL jitter. Therefore, in traditional digital decoding processes, the combined effects of frequency offset, jitter, and accumulated errors affect the extraction of the color synchronization signal. This makes accurate recovery of the color synchronization signal during decoding difficult and necessitates real-time frequency calibration via a COSTA PLL, increasing computational complexity. Summary of the Invention

[0006] The embodiments described herein provide a color synchronization and color difference correction method, apparatus, and computer-readable storage medium storing a computer program for digital decoding of FPV drones. By performing phase compensation and color calibration on the received signal, the synchronization problem between the drone and the receiving device is solved, ensuring that the chromaticity signal of the image is correctly decoded.

[0007] According to a first aspect of this disclosure, a method for color synchronization and color difference correction for digital decoding of an FPV unmanned aerial vehicle (FAV) is provided, comprising: receiving an analog image transmission signal from an FPV FAV; digitally sampling the analog image transmission signal to obtain chromaticity signals of multiple sampling points per row; calculating the phase error of each row based on the chromaticity signals of multiple sampling points per row and the local oscillator signal of the receiving device; performing phase compensation row by row based on the phase error of each row, and digitally decoding the phase-compensated chromaticity signals; and performing color calibration compensation on the original CVBS signal based on the chromaticity difference between the digitally decoded signal and the actual analog signal.

[0008] In some embodiments of this disclosure, receiving analog image transmission signals from an FPV drone and digitally sampling the analog image transmission signals to obtain chroma signals of multiple sampling points per row includes: converting the analog image transmission signals of the FPV drone into digital signals using an ADC, and obtaining chroma signals of N sampling points per row.

[0009] ,in, Represents the discretized chroma signal. Indicates the timestamp of the sampling point. It is the frequency of the chroma signal.

[0010] In some embodiments of this disclosure, calculating the phase error of each row based on the chroma signal of multiple sampling points per row and the local oscillator signal of the receiving device includes:

[0011] At the receiving end, a local oscillator signal with the same frequency as the input chrominance signal is generated. The local oscillator signal at the receiving end is divided into an in-phase component and a quadrature component, which are represented as follows:

[0012] ;

[0013] ;

[0014] in, This refers to the in-phase component of the local oscillator signal. The quadrature components of the local oscillator signal. This represents the phase deviation between the local oscillator signal at the receiving end and the chromaticity signal of the FPV UAV.

[0015] The high-frequency and low-frequency components are obtained by multiplying the chrominance signal of multiple sampling points in each row with the local oscillator signal:

[0016] ;

[0017] ;

[0018] in, and It is a high-frequency component. and It is the low-frequency component related to phase error; the signal is filtered using a low-pass filter to retain the low-frequency component, and the phase error of multiple sampling points in each row is calculated by arctangent operation.

[0019] In some embodiments of this disclosure, phase compensation is performed row by row based on the phase error of each row, and digital decoding of the phase-compensated chroma signal includes:

[0020] The average phase error of each row is obtained by averaging the phase errors of multiple sampling points in each row:

[0021] ;

[0022] in, This represents the mean phase error for each row. This represents the phase error at each sampling point. This is the number of sampling points in that row; phase compensation is performed row by row based on the mean phase error.

[0023] In some embodiments of this disclosure, phase compensation based on the mean phase signal line by line includes: traversing each line of data and superimposing a negative mean phase error on the local oscillator signal, with the phase compensation time for each line being 64 microseconds.

[0024] In some embodiments of this disclosure, color calibration compensation of the original CVBS signal based on the chromaticity difference between the digitally decoded signal and the actual analog signal includes: identifying the minimum value of the decoded original CVBS signal, calculating a compensation value based on the minimum value of the original CVBS signal, and adding the compensation value to the original CVBS signal so that its minimum value is greater than 0, thereby obtaining the color-corrected CVBS signal.

[0025] According to a second aspect of this disclosure, a color synchronization and color difference correction device for digital decoding of an FPV unmanned aerial vehicle (FAV) is provided. The device includes at least one processor and at least one memory storing a computer program. When the computer program is executed by the at least one processor, the device causes the following actions: receiving an analog image transmission signal from the FPV FAV; digitally sampling the analog image transmission signal to obtain chroma signals of multiple sampling points per row; calculating the phase error of each row based on the chroma signals of the multiple sampling points per row and the local oscillator signal of the receiving device; performing phase compensation row by row based on the phase error of each row, and digitally decoding the phase-compensated chroma signals; and performing color calibration compensation on the original CVBS signal based on the chroma difference between the digitally decoded signal and the actual analog signal.

[0026] According to a third aspect of this disclosure, a computer-readable storage medium storing a computer program is provided, wherein the computer program, when executed by a processor, implements the steps of a color synchronization and color difference correction method for digital decoding of an FPV unmanned aerial vehicle according to a first aspect of this disclosure.

[0027] The color synchronization and color difference correction method and apparatus for digital decoding of FPV UAVs according to embodiments of the present disclosure simplify the color synchronization process by using SDR (Software Defined Radio) technology to achieve digital decoding, avoid the complexity of traditional phase-locked loops, and significantly improve image quality by independently calculating the phase error of each line and performing accurate color compensation, thereby reducing image distortion and color deviation caused by phase errors. Attached Figure Description

[0028] To more clearly illustrate the technical solutions of the embodiments of this disclosure, the accompanying drawings of the embodiments will be briefly described below. It should be understood that the drawings described below only relate to some embodiments of this disclosure and are not intended to limit this disclosure, wherein:

[0029] Figure 1 This is a schematic diagram of the traditional digital decoding color synchronization signal extraction process;

[0030] Figure 2 An exemplary flowchart illustrates a method for color synchronization and color difference correction for digital decoding of FPV drones according to an embodiment of the present disclosure;

[0031] Figure 3 It is a digitally decoded image after phase compensation;

[0032] Figure 4 This is a color diagram of the original image;

[0033] Figure 5 This is a schematic diagram of the original CVBS data;

[0034] Figure 6 This is a schematic diagram of the corrected CVBS data;

[0035] Figure 7 A schematic block diagram of a color synchronization and color difference correction apparatus for digital decoding of FPV drones according to an embodiment of the present disclosure is shown.

[0036] It should be noted that the elements in the attached diagram are schematic and not drawn to scale. Detailed Implementation

[0037] To make the objectives, technical solutions, and advantages of the embodiments of this disclosure clearer, the technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this disclosure. All other embodiments obtained by those skilled in the art based on the described embodiments of this disclosure without creative effort are also within the scope of protection of this disclosure.

[0038] Unless otherwise defined, all terms used herein (including technical and scientific terms) shall have the same meaning as commonly understood by one of ordinary skill in the art to which this subject matter pertains. It will be further understood that terms such as those defined in commonly used dictionaries shall be interpreted as having meanings consistent with their meanings in the context of the specification and in the relevant art, and shall not be interpreted in an idealized or overly formal form unless otherwise explicitly defined herein. Furthermore, terms such as “first” and “second” are used only to distinguish one component (or part of a component) from another component (or another part of a component).

[0039] To address the synchronization issues between the drone and the receiving device, particularly regarding chromaticity signals and phase differences, this disclosure proposes an improved chromaticity correction scheme that does not rely entirely on all the functions of the COSTA phase-locked loop but only uses a portion of them, accurately correcting the received signal through phase compensation for each line of signal.

[0040] Figure 2 An exemplary flowchart illustrates a color synchronization and color difference correction method for digital decoding of FPV drones according to embodiments of the present disclosure. Firstly... Figure 2At frame S202, the analog image transmission signal from the FPV UAV is received, and the analog image transmission signal is digitally sampled to obtain the chromaticity signal of multiple sampling points in each row.

[0041] The receiver receives the analog image transmission signal from the FPV drone via an antenna. This signal, transmitted by the video transmission system, carries image and chromaticity information and is typically transmitted using standard composite video signal (CVBS), which includes luminance and chromaticity information. The received analog signal is first digitized by an analog-to-digital converter (ADC), converting the continuous analog signal into a discrete digital signal for subsequent processing. The ADC sampling process involves periodically sampling the analog signal, obtaining a digital value each time representing the signal's amplitude at a specific moment. During this process, the ADC's sampling rate (i.e., the number of samples per second) needs to satisfy the Nyquist theorem to ensure accurate signal reproduction. That is, the sampling rate should be greater than twice the signal's frequency.

[0042] In video signals, the chrominance signal carries color information and exists in the form of a sine wave: ,in, t is the frequency of the chroma signal, and t is time. Its frequency is related to the video standard (PAL or NTSC). For PAL, the frequency is 4.435 MHz; for NTSC, the frequency is 3.58 MHz. This means that each frame of video has a fixed frequency chroma signal related to the color of the image.

[0043] During the digitization process, the chroma signal of each line is decomposed into several sampling points. Assuming each line of video has N sampling points, each sampling point represents the chroma information at a certain time point in that line of video. The chroma signal of N sampling points is obtained for each line:

[0044] ;

[0045] in, Represents the discretized chroma signal. Indicates the sampling point. This refers to the frequency of the chrominance signal. Recording the values ​​of these sampling points yields the chrominance signal data for each row. Each sampling point can be represented as: , , ... These sampling points represent the discrete values ​​of the chroma signal in that row. Based on frequency... By considering the sampling rate, the time interval and corresponding chromaticity amplitude for each sampling point can be calculated.

[0046] Then in Figure 2In block S204, the phase error of each row is calculated based on the chromaticity signal of multiple sampling points in each row and the local oscillator signal of the receiving device.

[0047] At the receiving end, a local oscillator signal with the same frequency as the input chroma signal is generated. This oscillator signal has the same frequency as the received chroma signal, which is either PAL 4.435 MHz or NTSC 3.58 MHz. The oscillator signal is generated into two signal channels at the receiving end: a positive cross-channel (Q component) and an in-phase channel (I component). Specifically:

[0048] ;

[0049] );

[0050] in, This refers to the in-phase component of the local oscillator signal. These are the orthogonal components of the local oscillator signal. This represents the phase deviation between the receiver and the FPV drone. To address the phase deviation, the chromaticity signal from multiple sampling points in each row is multiplied by the local oscillator signal to obtain the high-frequency and low-frequency components:

[0051] ;

[0052] ;

[0053] in, and These are high-frequency components; the frequency of these signals is twice that of the original chroma signal. and It is the low-frequency component related to phase error, and it is the part related to phase error.

[0054] The signal obtained from the product calculation contains both high-frequency and low-frequency components. To extract the low-frequency components related to the phase deviation Δ, a low-pass filter is used to filter the signal, extracting the low-frequency components. The phase error is then calculated from the filtered signal using an arctangent operation. and In a signal, the phase error can be calculated using the arctangent operation (i.e., the four-quadrant arctangent, atan2 function):

[0055] ;

[0056] Here, atan2 is a function that calculates the angle of a point (x, y) on a two-dimensional plane. and These correspond to the y and x components, respectively, so the phase error can be obtained using atan2. In this way, the receiving device can extract the phase deviation from the filtered signal, and this error can be used for further phase correction or other signal processing operations.

[0057] Subsequently, in box S206, phase compensation is performed row by row based on the phase error of each row, and the phase-compensated chroma signal is digitally decoded.

[0058] The main purpose of phase compensation is to eliminate the phase deviation of the received signal relative to the local oscillator signal. Each line of the signal may contain random noise, which can affect phase compensation. To reduce the phase error caused by noise and instability, the phase error of multiple sampling points in each line can be averaged to obtain the mean phase error of each line:

[0059] ;

[0060] in, This represents the mean phase error for each row. This represents the phase error at each sampling point. This represents the number of sampling points within that row. By averaging the phase error of all sampling points within that row, noise fluctuations can be effectively smoothed out, making subsequent phase compensation more accurate. This is equivalent to the integrator reset operation of a Costa phase-locked loop.

[0061] Phase compensation is performed row by row based on the mean phase error. Specifically, each row of data is traversed, and a negative mean phase error is superimposed on the local oscillator signal. The phase compensation time for each row is 64 microseconds. During this time period, the phase error will be eliminated, ensuring the synchronization of each row of signals with the local oscillator signal. Figure 3 This is the digitally decoded image after phase compensation. Phase compensation is performed line by line to eliminate accumulated errors caused by crystal oscillator differences or other factors, ensuring that the phase of each line of signal is synchronized with the local oscillator signal. Figure 4 This is a color diagram of the original image, and... Figure 3 In comparison, the color of the phase-compensated image has a larger error than the original image. Therefore, color calibration compensation is required for the original CVBS data.

[0062] Finally, in box S208, color calibration compensation is performed on the original CVBS signal based on the chromaticity difference between the digitally decoded signal and the actual analog signal.

[0063] A CVBS signal consists of two parts: luminance information (Y) and chrominance information (C). The luminance signal level typically ranges from 0% to 100%. First, let's define the specified level amplitudes of the CVBS signal in the PAL format: Synchronization level: amplitude 0% (representing the synchronization signal, used for synchronizing the scanning process). Black level: amplitude 30% (representing the black parts of the image). White level: amplitude 100% (representing the white parts of the image). Figure 5 This is a schematic diagram of the original CVBS data.

[0064] like Figure 5 As shown, chromaticity signals involve both negative and positive values, but actual display devices can only process positive signals (such as LCD and CRT monitors). If the signal range includes negative values, the display effect may be inaccurate or exhibit problems such as color cast or insufficient contrast, thus affecting the image display quality.

[0065] To eliminate the impact of negative values ​​on image display, the original CVBS signal needs to be compensated and corrected by adjusting the minimum value of all its signals to be greater than zero, thus ensuring that the entire signal range is within the positive range. Specifically, the minimum value of the decoded original CVBS signal is identified, and a compensation value is calculated based on this minimum value. The compensation value is added to the original CVBS signal so that its minimum value is greater than 0, resulting in the color-corrected CVBS signal. After compensation, the compensated image can be viewed on a display screen or monitor to ensure that the image colors are correct and close to the actual analog signal. Alternatively, tools such as an oscilloscope can be used to measure the compensated CVBS signal to check whether the chroma signal meets expectations and whether all values ​​are within a reasonable range. If a significant error is still found in the chroma signal, the compensation value can be adjusted until the chroma error is minimized.

[0066] Figure 6 This is a schematic diagram of the corrected CVBS data. (Example:) Figure 6 As shown, after compensation and adjustment, the signal meets the following requirements: all signal values ​​are positive, and the signal amplitude range should be appropriately adjusted to between the synchronization level, black level, and white level in the PAL standard, i.e., synchronization level corresponds to 0%, black level corresponds to 30%, and white level corresponds to 100%. The calibrated signal can ensure the consistency of color reproduction and display, and is no longer affected by color deviation caused by negative values.

[0067] Finally, the compensated signal can be input to the display device. On the display device, the compensated signal can accurately reproduce the colors, ensuring that the black, white, and chromatic portions of the image meet expectations.

[0068] Figure 7A schematic block diagram of a color synchronization and color difference correction apparatus for digital decoding of FPV drones according to an embodiment of the present disclosure is shown. Figure 7 As shown, the device 700 may include a processor 710 and a memory 720 storing a computer program. When the computer program is executed by the processor 710, the device 700 is made capable of performing actions such as... Figure 2 The steps of the method are shown. In one example, device 700 may be a computer device or a cloud computing node. Device 700 can receive analog image transmission signals from an FPV drone, digitally sample the analog image transmission signals to obtain chroma signals of multiple sampling points per row; calculate the phase error of each row based on the chroma signals of multiple sampling points per row and the local oscillator signal of the receiving device; perform phase compensation row by row based on the phase error of each row, and digitally decode the phase-compensated chroma signals; and perform color calibration compensation on the original CVBS signal according to the chroma difference between the digitally decoded signal and the actual analog signal.

[0069] In embodiments of this disclosure, processor 710 may be, for example, a central processing unit (CPU), a microprocessor, a digital signal processor (DSP), a processor based on a multi-core processor architecture, etc. Memory 720 may be any type of memory implemented using data storage technologies, including but not limited to random access memory, read-only memory, semiconductor-based memory, flash memory, disk storage, etc.

[0070] Furthermore, in embodiments of this disclosure, device 700 may also include input device 730, such as a keyboard, mouse, etc., for example, inputting analog image transmission signals from an FPV drone. Additionally, device 700 may also include output device 740, such as a display, for example, displaying images after color synchronization and color difference correction.

[0071] In other embodiments of this disclosure, a computer-readable storage medium storing a computer program is also provided, wherein the computer program, when executed by a processor, is capable of performing the following functions: Figure 2 The steps of the color synchronization and color difference correction method for digital decoding of FPV UAVs are shown.

[0072] In summary, the color synchronization and color difference correction method and apparatus for digital decoding of FPV UAVs according to the embodiments of this disclosure simplify the color synchronization process by using SDR (Software Defined Radio) technology to achieve digital decoding, avoid the complexity of traditional phase-locked loops, and significantly improve image quality by independently calculating the phase error of each line and performing accurate color compensation, thereby reducing image distortion and color deviation caused by phase errors.

[0073] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatuses and methods according to various embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0074] Unless otherwise expressly indicated by the context, the singular form of words used herein and in the appended claims includes the plural form, and vice versa. Thus, when referring to the singular, the plural form of the corresponding term is generally included. Similarly, the terms “comprising” and “including” shall be interpreted as including rather than exclusively. Likewise, the terms “including” and “or” shall be interpreted as including unless such interpretation is expressly prohibited herein. Where the term “example” is used herein, particularly when it follows a set of terms, the “example” is merely exemplary and illustrative and should not be considered exclusive or extensive.

[0075] Further aspects and scope of adaptation become apparent from the description provided herein. It should be understood that various aspects of this application may be implemented individually or in combination with one or more other aspects. It should also be understood that the descriptions and specific embodiments herein are for illustrative purposes only and are not intended to limit the scope of this application.

[0076] Several embodiments of this disclosure have been described in detail above. However, it is obvious that those skilled in the art can make various modifications and variations to the embodiments of this disclosure without departing from the spirit and scope of this disclosure. The scope of protection of this disclosure is defined by the appended claims.

Claims

1. A color synchronization and color difference correction method for FPV drone digital decoding, characterized in that, The method comprises: receiving an analog video signal of the FPV drone, digitally sampling the analog video signal to obtain chrominance signals of multiple sampling points in each row; calculating a phase error of each row based on the chrominance signals of the multiple sampling points in each row and a local oscillator signal of the receiving end device, comprising: generating a local oscillator signal consistent with the frequency of the input chrominance signal at the receiving end, the local oscillator signal being divided into in-phase components and quadrature components, respectively represented as: F local_I = cos(ω SC t+Δ); F local_Q = sin(ω SC t+Δ); Wherein, F local_I is the in-phase component of the local oscillator signal, F local_Q is the quadrature component of the local oscillator signal, and Δ represents the phase deviation between the local oscillator signal of the receiving end and the chrominance signal of the FPV unmanned aerial vehicle. multiplying the chrominance signals of the multiple sampling points in each row with the local oscillator signal: F(t i ) × F local_I = [cos(2ω SC t+Δ)+cos( Δ)]; F(t i ) × F local_Q = [sin(2ω SC t+Δ)+sin( Δ)]; where cos(2ω SC t+Δ) and sin(2ω SC t+Δ) are high frequency components, and cos( Δ) and sin( Δ) are low frequency components related to the phase error; and filtering the signal using a low-pass filter to remove the high-frequency components and retain the low-frequency components, and calculating the phase error of the multiple sampling points in each row through an inverse tangent operation; performing phase compensation row by row based on the phase error of each row, and digitally decoding the phase-compensated chrominance signals; and performing color calibration compensation on the original CVBS signal according to the chrominance difference between the digitally decoded signal and the actual analog signal.

2. The method for color synchronization and color difference correction for FPV drone digitization decoding according to claim 1, characterized in that, The receiving of the analog video signal of the FPV drone, the digitally sampling of the analog video signal to obtain the chrominance signals of the multiple sampling points in each row comprises: converting the analog video signal of the FPV drone into a digital signal through an ADC, and obtaining the chrominance signals of N sampling points in each row: F(t i )=cos(ω SC t) where F(t i ) represents the discretized chrominance signal, t = t1, t2, t3,... t N denotes the sample point timestamp, ω SC is the frequency of the chrominance signal.

3. The method of color synchronization and color difference correction for FPV drone digitization decoding according to claim 1, characterized in that, The phase compensation row by row based on the phase error of each row, and the digitally decoding of the phase-compensated chrominance signals comprise: averaging the phase errors of the multiple sampling points in each row to obtain a mean phase error of each row: ； wherein, denotes the mean phase error per row, denotes the phase error per sample point, N is the number of sample points within the row; performing phase compensation row by row based on the mean phase error.

4. The color synchronization and color difference correction method for FPV drone digitization decoding according to claim 3, characterized in that, The phase compensation row by row based on the mean phase error comprises: traversing each row of data, and superimposing a negative mean phase error on the basis of the local oscillator signal, the phase compensation time of each row being 64 microseconds.

5. The method for color synchronization and color difference correction for FPV drone digitization decoding according to claim 1, characterized in that, The color calibration compensation on the original CVBS signal according to the chrominance difference between the digitally decoded signal and the actual analog signal comprises: identifying the minimum value of the decoded original CVBS signal, calculating a compensation value based on the minimum value of the original CVBS signal; and adding the compensation value to the original CVBS signal to make the minimum value greater than 0, and obtaining the CVBS signal after color correction.

6. A color synchronization and color difference correction device for FPV drone digital decoding, characterized in that, comprise: at least one processor; and at least one memory storing a computer program; wherein when the computer program is executed by the at least one processor, the apparatus performs the steps of the color synchronization and color difference correction method for digital decoding of the FPV drone according to any one of claims 1 to 5.

7. A computer readable storage medium storing a computer program, characterized in that, The computer program, when executed by a processor, implements the steps of the color synchronization and color difference correction method for digital decoding of the FPV drone according to any one of claims 1 to 5.

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