Visible light communication image high-speed transmission method based on compressed sensing

Abstract

The invention relates to the technical field of visible light communication, and discloses a visible light communication image high-speed transmission method based on compressed sensing, which comprises the following steps: connecting a control panel (FPGA) with an LED array (image source), a computer and a camera (CCD / CMOS), connecting the computer with the control panel and the camera, and installing an imaging lens in front of a camera photosensitive chip to form a system device. The method further comprises the following steps: S1, using an LED array as a signal source, and converting a coding signal and an image signal into a bright / dark state of the LED array; s2, sending a coding signal and a working instruction to an LED array through a control panel (FPGA), and sending an acquisition instruction to a camera at the same time; and S3, acquiring an image of the coding LED array by using a camera, and transmitting the image to a computer. According to the visible light communication image high-speed transmission method based on compressed sensing provided by the invention, low-cost high-speed image transmission is realized, and the quality and speed of image reconstruction are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of visible light communication, and in particular to a method for high-speed transmission of visible light communication images based on compressed sensing. Background Art

[0002] With the extensive application of the fifth generation of communication technology (5G), people are increasingly dependent on high-speed communication equipment in their lives and work. The requirements for data transmission rate of communication are increasing day by day, the usage of data traffic is increasing day by day, and the requirements for the reliability and stability of information transmission between current communication equipment are becoming more and more stringent. Therefore, in order to meet people's communication needs, it is urgent to research and develop new communication technologies. However, at present, traditional wireless radio frequency communication is facing a spectrum resource crisis, which has led to a bottleneck period in the development of current communication technology, limiting the improvement of data transmission rate of communication equipment. Therefore, solving the spectrum resource crisis is a vital task at present. Visible light communication uses optical signals to transmit data, and the spectrum resources of visible light are tens of thousands of times that of wireless transmission radio frequency communication, and it takes into account both communication and lighting. This means that there is a new direction for the development of high-speed transmission of information. Visible light communication has greater development potential in the future and is a communication method that can be used as an auxiliary to traditional wireless radio frequency.

[0003] In the signal transmission process of visible light communication, LED (Light Emitting Diode) is often used as the signal transmission source and PD (Photodiode Dector) is used as the receiver. Its working principle is to use the fast flashing ability of modulated LED light source to transmit information, which can not only realize the basic function of indoor lighting, but also provide high-speed indoor communication services. Compared with traditional communication technology, visible light communication has shown significant advantages of low cost and wide applicability.

[0004] However, if the LED array is used as the pixel array of the image, that is, at a certain moment, the light and dark information of the lamp beads in the LED array represents the information of a picture, then the receiving end needs to be replaced with a traditional CCD / CMOS camera (Charge-Coupled Device / Complementary Metal-Oxide-Semiconductor) to receive the image information sent by the LED. Since the shooting frame rate of ordinary CCD / CMOS is low (only a hundred frames at most), and the operating frequency of ordinary LED light sources is about megahertz level, that is, the operating frequency of the image emission source (LED) is much higher than the operating frequency of the image receiving end (CCD / CMOS). Therefore, the entire image information transmission process is forced to be difficult to increase in speed due to the low frame rate limit of CCD / CMOS. If a high-speed camera with a high frame rate is used, the cost of the entire communication equipment is too expensive, making visible light communication equipment unable to be widely used.

[0005] Therefore, in visible light communication technology, there is an urgent need for a method that can not only ensure low system equipment costs but also achieve high-speed image communication. Summary of the invention

[0006] In order to solve the above technical problems, the present invention provides a method for high-speed transmission of visible light communication images based on compressed sensing. The technical solution provided by the present invention is designed through the following ideas:

[0007] Visible light communication uses the fast flashing ability of LED light sources to transmit information, which can not only realize the basic function of indoor lighting, but also provide high-speed indoor communication services. Compared with traditional communication technologies, visible light communication has shown significant advantages of low cost and wide applicability. The visible light communication system consists of a transmitter, a visible light channel, and a receiver. In the visible light system, the transmission of information is achieved by the high-speed on-off switching of the LED. Specifically, the LED is driven to switch between the power state (representing "1") and the off state (representing "0"), thereby generating transmission information. Thereafter, the signal is channel coded and pre-equalized and transmitted through the visible light channel. The receiving end uses PD to receive the optical signal, then converts it into an electrical signal, and restores the original information through the demodulation process.

[0008] In visible light communication technology, if an LED array is used as an image pixel array and a CCD / CMOS is used as an image signal receiving end, since the flickering frequency of the LED is approximately at the megahertz level, while the acquisition frame rate of an ordinary CCD / CMOS is only a few hundred hertz, the mismatch in operating frequency forces the entire image transmission process to be reduced to a transmission speed of a hundred frames per second.

[0009] However, Snapshot Compressive Imaging (SCI) is a technology that uses a low-speed camera to capture and reconstruct high-speed motion scenes. The advantages of the SCI system are:

[0010] (1) Fast acquisition speed: An important advantage of SCI is its high acquisition speed. In multi-dimensional data acquisition tasks, only two-dimensional compressed observations need to be acquired, which means that the SCI system can provide acceleration for the low acquisition speed of CCD / CMOS in the image transmission task of visible light communication;

[0011] (2) High acquisition throughput: The SCI system acquires two-dimensional compressed observations in a single exposure mode. Under the premise of ensuring acquisition speed, it can give full play to the acquisition capability of the two-dimensional camera sensor, so that all the image information contained in the LED array can be acquired through a single exposure;

[0012] (3) Low complexity, low hardware cost, and small size: The SCI system uses a simple hardware structure, only collects two-dimensional compressed observations, and reconstructs three-dimensional or multi-dimensional data, thereby reducing system complexity and size and reducing costs;

[0013] (4) Low storage and low bandwidth requirements: Imaging systems that directly collect multidimensional data usually require a large amount of storage space and large data transmission bandwidth, which is mainly due to the large amount of multidimensional image data collected. The SCI system only needs to store and transmit the collected two-dimensional compressed observations and reconstruct the multidimensional images at the back end. This method greatly reduces the bandwidth requirements and storage costs of multidimensional data transmission.

[0014] In this way, the multiple advantages of the SCI system can be utilized to solve the problem of receiving frequency limitation of image transmission in visible light communication, so as to achieve high-speed image transmission tasks.

[0015] Based on the above research ideas, the present invention proposes a high-speed transmission method for visible light communication images based on compressed sensing.

[0016] The high-speed transmission method of visible light communication images based on compressed sensing provided by the present invention is composed of a system device by connecting a control board (FPGA) with an LED array (image source), a computer, and a camera (CCD / CMOS), connecting the computer with the control board and the camera, and installing an imaging lens in front of a camera photosensitive chip. The method also includes the following steps:

[0017] S1, using the LED array as a signal source, converting the coded signal and the image signal into the light / dark state of the LED array;

[0018] S2, sending coded signals and working instructions to the LED array through the control board (FPGA), and sending acquisition instructions to the camera at the same time;

[0019] S3, using a camera to collect an image of the coded LED array and transmitting it to a computer;

[0020] S4, the computer reads the collected image information and inputs it into the reconstruction network for image reconstruction;

[0021] S5. Use the snapshot compression imaging (SCI) system image reconstruction method based on deep learning to reconstruct the image.

[0022] Preferably, the function of the LED array is to convert the received coded signal and image signal into the bright / dark state of the light emitting diode array, thereby serving as a signal source in the visible light communication system, and transmitting it to the receiving end in optical form; the function of the computer is to send the coded signal to the control board; modulate the working parameters of the camera; read the image information collected by the camera and input it into the reconstruction network for image reconstruction; the function of the control board (FPGA) is to receive the coded signal from the computer; send the coded signal to the LED array; send the working instruction to the LED array; send the acquisition instruction to the camera; the function of the imaging lens is to image the image of the coded LED array on the photosensitive chip of the camera; the function of the camera is to expose and collect the dynamic coded LED array image imaged on the photosensitive chip through the control of the control board and the computer, and transmit it to the computer.

[0023] Preferably, in the system device, the FPGA is connected to the LED array, and the LED array is composed of microprocessor boards connected in series, and the microprocessor on the back of the board controls all LEDs on the front of the board.

[0024] Preferably, the functions of the microprocessor are: receiving the coded signal from the control board; storing the coded signal from the control board; receiving the working instruction from the control board; and setting the on and off state of the LED group.

[0025] Preferably, in step S2, the signal sent to the LED array causes the LED array to follow the time sequence t 1 ...t n Play the images containing the coded information sequentially.

[0026] Preferably, the image reconstruction step in step S5 includes inputting the collected compressed two-dimensional image and known randomly distributed encoding matrix information into a reconstruction network, and reconstructing the high-speed LED array image through an algorithm.

[0027] Preferably, in the process of image reconstruction using a snapshot compression imaging (SCI) system image reconstruction method based on deep learning, image prior features are learned through big data training, and the model input-output mapping relationship is obtained to obtain a fast and high-quality reconstructed image.

[0028] Preferably, the snapshot compression imaging (SCI) system image reconstruction method based on deep learning in step S5 includes: an end-to-end deep neural network (End-to-End), a deep unfolding neural network (Deep-unfolding) or a plug-and-play algorithm framework (Plug-and-Play, PnP).

[0029] Preferably, the method of reconstructing the compressed image is not limited to using the above deep learning algorithm, and any algorithm that can reconstruct a compressed spectral image, such as a traditional iterative algorithm, may also be used.

[0030] Compared with the related art, the high-speed transmission method of visible light communication images based on compressed sensing provided by the present invention has the following beneficial effects:

[0031] (1) The present invention proposes a visible light communication image transmission method based on compressed sensing, which realizes high-speed transmission of visible light communication images;

[0032] (2) The present invention achieves low-cost high-speed image transmission by combining the encoding method of single-exposure compression imaging technology with the flashing mode of visible light communication LED array;

[0033] (3) The present invention realizes high-speed encoding of images in the visible light domain by combining a method of encoding image information by combining a compressed sensing high-speed encoding method with an LED image array for visible light image transmission;

[0034] (4) In the method of the present invention, the quality and speed of image reconstruction are improved by acquiring the encoded compressed LED image array and using a single-exposure compression imaging algorithm to perform video reconstruction. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 A schematic diagram of a system device for high-speed transmission of visible light communication images based on compressed sensing provided by the present invention;

[0036] Figure 2 Schematic diagram of the device for controlling the LED matrix with FPGA. DETAILED DESCRIPTION

[0037] The scheme of the present invention is further described below in conjunction with the accompanying drawings and implementation modes.

[0038] The system device of the present invention is as follows Figure 1 As shown, the control board (FPGA) is connected to the LED array (image source), the computer, and the camera (CCD / CMOS), and the computer is connected to the control board and the camera. The imaging lens is installed in front of the camera photosensitive chip.

[0039] In this device,

[0040] The function of the LED array is to convert the received coded signal and image signal into the light / dark state of the light emitting diode array, which is used as the signal source in the visible light communication system, and transmit it to the receiving end in an optical form;

[0041] The functions of the computer are: sending coded signals to the control board; modulating the working parameters of the camera; reading the image information collected by the camera and inputting it into the reconstruction network for image reconstruction;

[0042] The functions of the control board (FPGA) are: receiving coded signals from the computer; sending coded signals to the LED array; sending working instructions to the LED array; sending acquisition instructions to the camera;

[0043] The function of the imaging lens is to image the image of the coded LED array onto the photosensitive chip of the camera;

[0044] The function of the camera is to expose and collect the dynamic coded LED array image formed on the photosensitive chip through the control of the control board and the computer, and transmit it to the computer.

[0045] FPGA controls the LED matrix Figure 2 As shown, the FPGA is connected to the LED array, and the LED array is composed of microprocessor boards connected in series. The microprocessor on the back of the board controls all the LEDs on the front of the board.

[0046] In this device,

[0047] The functions of the microcontroller are: receiving the coded signal from the control board; storing the coded signal from the control board; receiving the working instruction from the control board; and setting the on and off state of this group of LEDs.

[0048] When the system is working, the computer loads n randomly distributed "0" and "1" matrix coding information onto the control board FPGA, and modulates the camera to be in a suitable working state. At a certain moment, the control board sends signals to the camera and the LED array at the same time. The signal sent to the LED array causes the LED array to play the image containing the coding information in sequence according to the time sequence t1...tn. (The circular pattern in the coded LED array in the figure represents a single light-emitting diode, the dark color represents that the light-emitting diode is not lit at this time, and the light color represents that the light-emitting diode is lit at this time). The signal sent to the camera by another channel triggers the camera to expose and collect the coded LED array image with time sequence changes. The collected compressed image is stored on the computer side, waiting for the next step of image reconstruction.

[0049] When reconstructing the obtained two-dimensional compressed image, the snapshot compression imaging (SCI) system image reconstruction method based on deep learning can be used, which has a strong feature extraction capability. Generally, by training and learning image prior features through big data, the model input-output mapping relationship is obtained, and a fast and high-quality reconstructed image can be obtained. For example:

[0050] (1) End-to-End Deep Neural Network (End-to-End);

[0051] (2) Deep-unfolding neural network;

[0052] (3) Plug-and-Play algorithm framework (PnP).

[0053] Here is the general model of the compressed sensing algorithm:

[0054] y=Ax+g (1)

[0055] Among them, A is the sensing matrix, g is the observation noise, x represents the approximate vector in the noise-free model, and y is the output image result.

[0056] The method of reconstructing the compressed image in the present invention is not limited to using the above deep learning algorithm, and all algorithms that can reconstruct the compressed spectral image, such as traditional iterative algorithms, can also be used.

[0057] Specifically, during the reconstruction process, the collected compressed two-dimensional image and the known randomly distributed coding matrix information are input into the reconstruction network, and the high-speed LED array image is reconstructed through the algorithm to form a high-frame rate reconstructed video.

[0058] Compared with the prior art, the high-speed transmission method of visible light communication images based on compressed sensing proposed in the present invention has the following beneficial effects:

[0059] Solve the contradiction between cost and speed: When traditional visible light communication improves the image transmission speed, if a high-speed camera with a high frame rate is used, the cost of the entire communication equipment will be too expensive. The method proposed in the present invention can achieve high-speed image communication while ensuring the low cost of system equipment, thus overcoming the problem of difficulty in balancing cost and speed in traditional visible light communication;

[0060] Improve image transmission speed: By utilizing the advantages of single exposure compressed imaging (SCI) technology, such as fast acquisition speed, high acquisition throughput, low complexity, low hardware cost and small size, low storage and low bandwidth requirements, the problem of image transmission speed being difficult to improve due to the low acquisition frame rate of CCD / CMOS is solved, and high-speed image transmission in visible light communication is realized;

[0061] Innovative coding and transmission methods: A technology combining the coding method of single-exposure compression imaging technology with the flashing mode of LED arrays for visible light communication, and a method combining the high-speed coding method of compressed sensing with the coded image information of LED image arrays for visible light image transmission are proposed to achieve high-speed coding of images in the visible light field, thus improving the efficiency and quality of image transmission;

[0062] Flexible image reconstruction method: The reconstruction method of compressed images in the present invention is not limited to a specific deep learning algorithm, and traditional iterative algorithms can also be used. This flexibility provides more options for image reconstruction and improves the reliability and effectiveness of image reconstruction.

[0063] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for high-speed transmission of visible light communication images based on compressed sensing, characterized in that: The method uses a control board FPGA to connect with an LED array, a computer, and a camera CCD / CMOS, the computer is connected with the control board and the camera, and an imaging lens is installed in front of a camera photosensitive chip to form a system device. The method also includes the following steps: S1, using the LED array as a signal source, converting the coded signal and the image signal into the light / dark state of the LED array; S2, sending coded signals and working instructions to the LED array through the control board FPGA, and sending acquisition instructions to the camera at the same time; S3, using a camera to collect an image of the coded LED array and transmitting it to a computer; S4, the computer reads the collected image information and inputs it into the reconstruction network for image reconstruction; S5. Use the snapshot compression imaging SCI system image reconstruction method based on deep learning to reconstruct the image.

2. The method for high-speed transmission of visible light communication images based on compressed sensing according to claim 1, characterized in that: The LED array is used to convert the received coded signal and image signal into the light / dark state of the light emitting diode array, thereby serving as a signal source in the visible light communication system, and transmit it to the receiving end in an optical form; The functions of the computer are: sending coded signals to the control board; modulating the working parameters of the camera; reading the image information collected by the camera and inputting it into the reconstruction network for image reconstruction; The functions of the control board FPGA are: receiving coded signals from the computer; sending coded signals to the LED array; sending working instructions to the LED array; sending acquisition instructions to the camera; The function of the imaging lens is to image the image of the coded LED array onto the camera's photosensitive chip; The function of the camera is to expose and collect the dynamic coded LED array image formed on the photosensitive chip through the control of the control board and the computer, and transmit it to the computer.

3. The method for high-speed transmission of visible light communication images based on compressed sensing according to claim 1, characterized in that: In the system device, the FPGA is connected to the LED array, and the LED array is composed of microprocessor boards connected in series. The microprocessor on the back of the board controls all the LEDs on the front of the board.

4. The method for high-speed transmission of visible light communication images based on compressed sensing according to claim 3, characterized in that: The functions of the microprocessor are: receiving the coding signal from the control board; storing the coding signal from the control board; receiving the working instruction from the control board; and setting the on and off state of the LED group.

5. The method for high-speed transmission of visible light communication images based on compressed sensing according to claim 1, characterized in that: In step S2, the signal sent to the LED array causes the LED array to follow the time sequence t1...t n Play the images containing the coded information sequentially.

6. The method for high-speed transmission of visible light communication images based on compressed sensing according to claim 1, characterized in that: The image reconstruction step in step S5 includes inputting the collected compressed two-dimensional image and known randomly distributed encoding matrix information into a reconstruction network, and reconstructing a high-speed LED array image through an algorithm.

7. The method for high-speed transmission of visible light communication images based on compressed sensing according to claim 1, characterized in that: In the process of image reconstruction using the snapshot compression imaging (SCI) system image reconstruction method based on deep learning, the image prior features are learned through big data training, and the model input-output mapping relationship is obtained to obtain a fast and high-quality reconstructed image.

8. The method for high-speed transmission of visible light communication images based on compressed sensing according to claim 1, characterized in that: The image reconstruction method of the snapshot compression imaging SCI system based on deep learning in step S5 includes: an end-to-end deep neural network, a deep unfolding neural network or a plug-and-play algorithm framework.

9. The method for high-speed transmission of visible light communication images based on compressed sensing according to claim 1, characterized in that: The method of reconstructing the compressed image is not limited to using the above deep learning algorithm, and any algorithm that can reconstruct a compressed spectral image, such as a traditional iterative algorithm, can also be used.

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