Progressive image transmission method suitable for power transmission line in non-signal area

Abstract

The invention discloses a progressive image transmission method suitable for a power transmission line in a non-signal area, and relates to the technical field of image processing. Comprising the following steps: constructing and training a target detection model, carrying out pruning training on the target detection model to obtain a structured stripe pruning model, and training the model again by adopting a mixed precision training method to complete pruning; the method comprises the steps of firstly performing compression processing on a to-be-transmitted image, removing redundant information in the image, then transferring an original image from a spatial domain to a frequency domain through Fourier transform, then gradually transmitting data to Beidou from a low-frequency level to a high-frequency level in a layered manner after frequency coefficient division, and reducing the data volume by using a Base64 compression algorithm so as to improve the data transmission efficiency. And finally, the original image is decoded and restored at the receiving end, so that the contradiction of low communication load between the picture big data and the short message is solved, the picture transmission time is shortened, and the efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of image transmission, and in particular to a progressive image transmission method suitable for power transmission lines in no-signal areas. Background Art

[0002] Image transmission refers to the process of transferring image data from one location to another. This data can be static pictures or dynamic videos. The transmission can be done through wired or wireless means. The key to image transmission is to minimize the transmission time and required bandwidth while maintaining image quality. Image transmission technology is an important part of modern communication and information technology. With the development of the Internet and multimedia technology, image transmission has become a key part of daily life and work.

[0003] However, since there are still a large number of signal-free areas in my country, images cannot be transmitted through the Internet in these areas, while Beidou short message communication can transmit data in signal-free areas. Therefore, how to use Beidou short message to transmit images has become an important research topic.

[0004] At present, for Beidou civilian cards, short message communication has two disadvantages, namely, the sending interval is not less than 30 seconds / time, and the short message length is not more than 1750 bytes of data; due to the above constraints, the short messages sent by civilian cards are generally used in scenarios with low sending frequency and small data volume. Therefore, the vast majority of Beidou short message application scenarios currently use text as the information carrier. There is a contradiction between large image data and low load of short messages, resulting in long image transmission time and low transmission efficiency. Therefore, the present invention proposes a progressive image transmission method suitable for power transmission lines in signal-free areas to solve the problems existing in the prior art. Summary of the Invention

[0005] In response to the above problems, the purpose of the present invention is to propose a progressive image transmission method suitable for power transmission lines in signal-free areas, so as to solve the problem that most of the current Beidou short message application scenarios use text as the information carrier, and there is a contradiction between big image data and low load of short messages, resulting in long image transmission time and low transmission efficiency.

[0006] To achieve the purpose of the present invention, the present invention is implemented by the following technical solution: a progressive image transmission method suitable for power transmission lines in a no-signal area, comprising the following steps: Step 1: Obtain the image to be transmitted, compress it, and remove redundant information in the compressed image to obtain the original image; Step 2: Perform a two-dimensional Fourier transform on the original image to convert the original image from the spatial domain to the frequency domain to obtain the frequency domain coefficient matrix; Step 3: Divide the frequency coefficients of the frequency domain coefficient matrix into different levels according to frequency, including a low-frequency level and a high-frequency level; Step 4: According to the frequency domain layer division order, the frequency domain coefficients are gradually layered and transmitted from the low frequency layer to the high frequency layer; Step 5: After the receiving end receives the frequency domain coefficients of the layered transmission, it performs inverse Fourier transform on the frequency domain coefficients and gradually reconstructs the image. After the image reconstruction is completed, the image transmission is completed.

[0007] A further improvement is that in step 1, the specific steps of compressing the image to be transmitted are: using differential pulse code modulation plus Huffman coding to perform lossless compression on the image to be transmitted, and removing redundant information by encoding the prediction error.

[0008] A further improvement is that in step 2, the frequency domain coefficient matrix includes all frequency components of the original image.

[0009] A further improvement is that in step three, the low-frequency layer contains the main structural information of the original image, and the high-frequency layer contains the detail information of the original image.

[0010] A further improvement is that in step three, the JPEG compression algorithm is used to quantize and compress each frequency domain level, and the Base64 compression algorithm is used to reduce the amount of data.

[0011] A further improvement is that in step three, the low-frequency layer is in the center and the high-frequency layers are distributed around the low-frequency layer.

[0012] A further improvement is that in step 4, the low-frequency layer is transmitted first to enable the receiving end to reconstruct the basic outline of the image, and then the high-frequency layer is transmitted to gradually increase the image details at the receiving end.

[0013] A further improvement is that in step 5, each time the receiving end receives a new frequency domain level, it performs an inverse transformation to update the image.

[0014] The beneficial effects of the present invention are as follows: the present invention first compresses the image to be transmitted and eliminates redundant information in the image, then converts the original image from the spatial domain to the frequency domain through Fourier transform, and then divides the frequency coefficients into levels, and gradually transmits the data to Beidou in layers from the low-frequency level to the high-frequency level, and uses the Base64 compression algorithm to reduce the amount of data. Finally, the present invention decodes at the receiving end to restore the original image, which solves the contradiction between large image data and low short message communication load, reduces image transmission time, and improves efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0016] Figure 1 It is a flow chart of the progressive image transmission method applicable to power transmission lines in no-signal areas of the present invention. DETAILED DESCRIPTION

[0017] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention. Example

[0018] See also Figure 1 This embodiment provides a progressive image transmission method applicable to power transmission lines in a no-signal area, comprising the following steps: Step 1: Compress the image and obtain the original image by removing redundant information Obtain the image to be transmitted and perform lossless compression on it using differential pulse code modulation (DPCM) plus Huffman coding. Redundant information is removed by encoding the prediction error to obtain the original image. Step 2: Obtain the frequency domain coefficient matrix by performing a two-dimensional Fourier transform on the original image Perform a two-dimensional Fourier transform on the original image to convert the original image from the spatial domain to the frequency domain to obtain a frequency domain coefficient matrix, which contains all the frequency components of the original image; Step 3: Divide the frequency coefficients of the frequency domain coefficient matrix according to frequency The frequency coefficients of the frequency domain coefficient matrix are divided into different levels according to frequency, including low-frequency level and high-frequency level. The low-frequency level contains the main structural information of the original image, and the high-frequency level contains the details of the original image. The low-frequency level is in the center, and the high-frequency level is distributed around the low-frequency level. The JPEG compression algorithm is then used to quantize and compress each frequency domain level, and the Base64 compression algorithm is used to reduce the amount of data. Step 4: Layer the frequency domain coefficients according to the frequency domain level division order According to the frequency domain layer division order, the frequency domain coefficients are gradually transmitted layer by layer from low frequency layer to high frequency layer. The low frequency layer is transmitted first, so that the receiving end can reconstruct the basic outline of the image. Then the high frequency layer is transmitted, so that the image details at the receiving end are gradually increased and the image quality is continuously improved. Step 5: The receiving end performs inverse Fourier transform on the frequency domain coefficients and reconstructs the image After the receiving end receives the frequency domain coefficients of the layered transmission, it performs an inverse Fourier transform on the frequency domain coefficients. Each time the receiving end receives a new frequency domain level, it performs an inverse transform to update the image and gradually reconstruct the image. Once the image reconstruction is completed, the image transmission is completed. Example

[0019] This embodiment verifies the progressive image transmission method for power transmission lines in a no-signal area provided in the first embodiment. The expected image quality is psnr_ref=28, the default encoding quality parameter q=38, and the image resolution is wxh, assuming that w is approximately twice the value of h. Step 1: Since color images have three channels and grayscale images have one channel, to simplify the calculation, this embodiment converts the image into a grayscale image. Grayscale images only contain brightness information. The specific operations are as follows: A1: Use the cv2.imread function of the OpenCV library to read the image file; A2: Use the cv2.IMREAD_GRAYSCALE flag to convert the image to a grayscale image, reducing computational complexity and focusing on brightness information; Step 2: Perform a two-dimensional Fourier transform on the image to convert it to the frequency domain. The Fourier transform can represent the image in the spatial domain as a combination of sine and cosine waves of different frequencies. Through the Fourier transform, the spectrum of the image is obtained, which shows the amplitude and phase of different frequency components. The specific operations are as follows: B1: Use the np.fft.fft2 function of the NumPy library to perform a two-dimensional Fourier transform; B2: Use the np.fft.fftshift function to move the low-frequency components to the center of the spectrum for easier observation and processing; Step 3: To achieve progressive image transmission, this embodiment divides the frequency domain coefficients into multiple levels based on frequency. Low-frequency components contain basic image structure information, while high-frequency components contain image detail information. By prioritizing the transmission of low-frequency components, the basic image structure can be restored within a limited bandwidth, while gradually increasing the image details. Generate a mask to divide the frequency domain into layers, each layer corresponding to a different frequency range. The role of the mask is to select specific areas in the frequency domain for layer-by-layer processing and transmission. The specific operations are as follows: C1: Use concentric circle masks to divide the frequency domain into multiple levels, each level contains components of different frequency ranges; C2: The radius of the mask increases proportionally with the number of levels to ensure that the frequency range included in each level gradually increases; Quantize and compress each frequency domain level, using the Base64 compression algorithm to reduce the amount of data. The specific operations are as follows: D1: Use Base64 to compress data; D2: compresses the real part and the imaginary part separately to reduce the amount of transmitted data; Step 4: Transmit the frequency domain coefficients step by step in the order of the frequency domain layers, first transmitting the low frequency layers, and then transmitting the high frequency layers in sequence; Step 5: The receiver performs an inverse Fourier transform based on the received frequency domain levels and gradually reconstructs the image. The specific operations are as follows: E1: decompresses the received frequency domain level data; E2: Recover the real and imaginary parts and synthesize them into complex frequency domain data; After the received frequency domain layer data is decompressed, it is accumulated layer by layer and inverse Fourier transformed to reconstruct the image.

[0020] The quality of the reconstructed image is evaluated by the PSNR and SSIM indicators. The image reconstructed layer by layer will gradually approach the original image. The PSNR and SSIM values ​​will gradually increase as more frequency domain layers are added. The higher the PSNR value, the smaller the difference between the surface reconstructed image and the original image, and the closer the SSIM value is to 1, indicating that the reconstructed image is more similar to the original image in structure.

[0021] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A progressive image transmission method suitable for power transmission lines in signal-free areas, characterized in that: The following steps are involved: Step 1: Obtain the image to be transmitted, compress the image to be transmitted, and remove redundant information in the compressed image to obtain the original image; Step 2: Perform a two-dimensional Fourier transform on the original image to convert the original image from the spatial domain to the frequency domain to obtain the frequency domain coefficient matrix; Step 3: Divide the frequency coefficients of the frequency domain coefficient matrix into different levels according to the frequency, including a low-frequency level and a high-frequency level; Step 4: According to the frequency domain layer division order, the frequency domain coefficients are gradually layered and transmitted from the low frequency layer to the high frequency layer; Step 5: After the receiving end receives the frequency domain coefficients of the layered transmission, it performs inverse Fourier transform on the frequency domain coefficients and gradually reconstructs the image. After the image reconstruction is completed, the image transmission is completed.

2. According to claim 1, a progressive image transmission method suitable for power transmission lines in no-signal areas is characterized by: In the step 1, the specific steps of compressing the image to be transmitted are: using differential pulse code modulation plus Huffman coding to perform lossless compression on the image to be transmitted, and removing redundant information by encoding the prediction error.

3. The progressive image transmission method applicable to power transmission lines in no-signal areas according to claim 1, characterized in that: In the step 2, the frequency domain coefficient matrix includes all frequency components of the original image.

4. The progressive image transmission method applicable to power transmission lines in areas without signals according to claim 1, characterized in that: In the step three, the low-frequency layer contains the main structural information of the original image, and the high-frequency layer contains the detail information of the original image.

5. The progressive image transmission method applicable to power transmission lines in areas without signals according to claim 1, characterized in that: In the step three, the JPEG compression algorithm is used to quantize and compress each frequency domain level, and the Base64 compression algorithm is used to reduce the amount of data.

6. The progressive image transmission method applicable to power transmission lines in areas without signals according to claim 1, characterized in that: In the step three, the low-frequency layer is in the center, and the high-frequency layer is distributed around the low-frequency layer.

7. The progressive image transmission method applicable to power transmission lines in areas without signals according to claim 1, characterized in that: In the step 4, the low-frequency layer is transmitted first, so that the receiving end reconstructs the basic outline of the image, and then the high-frequency layer is transmitted, so that the image details at the receiving end are gradually increased.

8. The progressive image transmission method applicable to power transmission lines in areas without signals according to claim 1, characterized in that: In the step 5, each time the receiving end receives a new frequency domain level, it performs an inverse transformation to update the image.

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