Self-adaptive underwater single-pixel imaging technology based on Fourier modulation

Abstract

The invention discloses a self-adaptive underwater single-pixel imaging technology based on Fourier modulation, belongs to the technical field of computational optical imaging, is used for ocean detection and improvement of ocean surveillance and defense efficiency, and adopts a self-designed LED array to replace an expensive DMD and a four-quadrant detector composed of common photodiodes to replace an expensive barrel detector. And high-speed illumination and parallel acceptance are realized while the cost is greatly reduced. The technical route comprises a high-speed underwater single-pixel imaging device, a high-speed Fourier single-pixel imaging algorithm and an adaptive sampling strategy based on Fourier single-pixel imaging. The high-speed single-pixel imaging device comprises a self-designed LED array light modulation module, a converging lens module and a receiving module. The high-speed Fourier single-pixel imaging algorithm comprises a binarization algorithm based on error diffusion and an algorithm based on adaptive compressed sensing. According to the innovative self-adaptive sampling strategy based on Fourier single-pixel imaging, a specific sampling path is generated by fusing circular sampling and random sampling according to the characteristics of an image in a Fourier spectrum, so that Fourier coefficients which have great influence on image quality are acquired as much as possible under water with low sampling rate and high turbidity, and the image quality is improved. Therefore, the high-efficiency imaging of the underwater target object is realized, and the imaging speed and quality are both considered.

Description

[0001] Technical field: The present invention discloses an adaptive underwater single-pixel imaging technology based on Fourier modulation, which belongs to the field of computational optical imaging technology.

[0002] Background technology: With the development of technology, marine safety and defense have received much attention. Clear underwater imaging technology will improve the efficiency of marine surveillance and defense, and will also help protect marine ecosystems and maintain sustainable development. However, due to the absorption of light by seawater and the scattering of light by tiny particles, traditional optical cameras cannot take into account both the presentation distance and imaging quality, and are difficult to meet the needs of marine exploration. As an important branch of computational optical imaging, single-pixel imaging has advantages such as high sensitivity and high energy collection rate compared with traditional imaging technology, thereby achieving the effect of no end flow and reducing the influence of backscattering, making it have broad prospects in underwater imaging of low sampling rate and high turbidity seawater. However, traditional single-pixel imaging technology has the following problems: (1) high cost, long imaging time, and low imaging quality; (2) the spatial light modulator (such as DMD) required for the single-pixel imaging system mainly relies on foreign imports; (3) single-pixel imaging is currently only in the laboratory stage and its development in China is limited, and it cannot be widely used. Summary of the invention:

[0003] 1. The purpose of the present invention is to address the shortcomings of the above-mentioned existing underwater imaging technologies and provide an underwater single-pixel imaging technology based on an innovative adaptive sampling strategy based on Fourier modulation to solve the problems of low sensitivity, slow imaging rate, and inability to achieve clear imaging in the existing technologies, while simplifying the imaging system and saving imaging costs.

[0004] 2. An underwater single-pixel imaging system based on Fourier modulation. The light modulation module consists of an FPGA control board and an LED array, which is used to pre-generate speckles and obtain the modulated light field corresponding to each speckle.

[0005] 3. The converging lens module, consisting of a first converging lens and a second converging lens, is used to collect the structured light generated by the LED array, increase the light intensity, and project it onto the underwater target object. It then converges the light transmitted or reflected by the object to improve the signal-to-noise ratio, thereby improving the imaging quality.

[0006] 4. The receiving module, consisting of a four-quadrant detector, a data acquisition card and a computer, is used to collect the light intensity information of the reflected or transmitted light of the target object in the water, and input it into the computer for calculation and processing to obtain the imaging image of the target object.

[0007] 5. Use the error diffusion algorithm to binarize the Fourier pattern for LED array modulation. Load the Fourier illumination pattern to the FPGA control board, control the LED array to generate a high-speed strobe structured light emission Fourier pattern, and project the modulated light through the imaging lens to the object plane in the highly turbid water.

[0008] 6. Use a four-quadrant detector to collect the light intensity sequence reflected from the surface of the object being measured and sample it through an adaptive sampling strategy

[0009] 7. Based on the projected and captured compressed sampling patterns, sub-images are reconstructed through compressed sensing and then reassembled to obtain the target image. The image is then denoised using a three-dimensional block matching algorithm.

[0010] 8. Use the adaptive compressed sensing algorithm to reconstruct the image. The specific implementation method is as follows:

[0011] Step 1: Obtain the Fourier coefficients of sea surface fluctuations using the statistical wave model;

[0012] Step 2: Using the Fourier coefficients as prior knowledge, adjust the regularization parameters in the TVL1-L2 algorithm;

[0013] Step 3: Define a new total variable TV in the TVL-L2 algorithm Fourier (u), which can be expressed as:

[0014]

[0015] This term is based on the gradient of the Fourier transform of the image to be restored;

[0016] Step 4: Restore the image by minimizing the objective function containing the total variation term TV_Fourier, where the objective function is:

[0017]

[0018] Among them, f is the observation data, L is the coefficient transformation matrix, and λ and μ are regularization parameters that can be adjusted according to the Fourier characteristics of sea surface fluctuations.

[0019] 9. This system combines the circular sampling method and the variable density sampling method to independently design an adaptive sampling strategy: combining the circular sampling method and the variable density sampling method, performing the first sampling under the condition of undersampling rate, and analyzing the first sampling results to calculate the mean of the absolute value of the Fourier coefficient in each sector, and recording the angles of the first few sectors with the highest mean; then performing the second sampling based on the analysis results, sampling in the directions with the highest mean; finally, if there are any remaining sampling points, they are distributed from low frequency to high frequency using the circular sampling method

[0020] 10. The underwater single-pixel imaging system according to claim 4 is characterized by the light modulation module, which is specifically manifested as: the LED array uses 16 8×8 LED panels through circuit design and welding to form a 32×32 LED dot matrix, which realizes parallel scanning under FPGA control. Compared with the traditional 32×32 LED integrated panel, its modulation rate is increased by nearly 16 times.

[0021] 11. Compared with the prior art, the beneficial effects of the present invention include: through the independently designed LED array and FPGA controlled high-speed parallel scanning state, the modulation rate is increased by 16 times, the modulation pattern emission rate is accelerated, thereby reducing the underwater single-pixel imaging time and achieving high-speed imaging of the target object to be imaged underwater. By introducing Fourier modulation into the LED array, based on the characteristic that the spatial information of the image is concentrated in the low-frequency part in the Fourier domain, by focusing on the low-frequency and high-frequency information in the Fourier transform domain, it is possible to take into account both imaging quality and speed, making up for the defects of random modulation and Hadamard modulation that cannot take into account both imaging time and imaging quality, so that single-pixel imaging in water can achieve high-quality imaging in a short time, thus laying a technical foundation for real-time ocean detection. The adaptive sampling strategy independently designed in this application ensures the real-time performance of Fourier underwater single-pixel imaging while retaining more detailed information. It can achieve high-speed and high-quality underwater target imaging in low-sampling and high-turbidity water and obtain clear images, ensuring the real-time and clarity of underwater imaging. A complete set of low-cost, high-speed, high-quality ocean single-pixel imaging methods is proposed. Description of the drawings:

[0022] 1. Figure 1 It is a single-pixel imaging system.

[0023] 2. Figure 2 It is the optimal sampling path of the adaptive sampling strategy at different sampling rates.

[0024] 3. Figure 3 This is the optimal path generation process of the adaptive sampling strategy when the sampling rate is 0.1.

[0025] 4. Figure 4 are the image restoration results under different sampling rates.

[0026] 5. Figure 5 This is a single-pixel imaging flow chart based on binary illumination.

[0027] 6. Figure 6 These are the image restoration results of different binarization methods.

[0028] 7. The reference numerals include: 1-LED matrix, 2-photodiode, 3-first converging lens, 4-second converging lens, 5-strong scattering medium, 6-object, 7-data acquisition card, 8-FPGA, 9-computer. Specific implementation method:

[0029] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention are described clearly and completely below. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without inventive effort fall within the scope of protection of the present invention.

[0030] An underwater single-pixel imaging system based on Fourier modulation, a light modulation module, composed of an FPGA control board 8 and an LED array 1, is used to preform speckles and obtain the modulated light field corresponding to each speckle.

[0031] The converging lens module, consisting of a first converging lens 3 and a second converging lens 4, is used to collect the structured light generated by the LED matrix 1, increase the light intensity, and project it onto the underwater target object 6. The light transmitted or reflected by the object 6 is then converged to improve the signal-to-noise ratio, thereby improving the imaging quality.

[0032] The receiving module is composed of a four-quadrant detector composed of a photodiode 2, a data acquisition card 7 and a computer 9. It is used to collect the light intensity information of the reflected or transmitted light of the underwater object 6, and input it into the computer 9 for calculation and processing to obtain the imaging image of the target object 6.

[0033] The error diffusion algorithm is used to binarize the Fourier pattern for modulation by the LED matrix 1. The Fourier illumination pattern is loaded into the FPGA control board 8, which controls the LED matrix 1 to generate a structured light emission Fourier pattern at high speed, and projects the modulated light through the imaging lenses 3 and 4 onto the object 6 plane in the highly turbid water.

[0034] The four-quadrant detector composed of photodiodes 2 collects the light intensity sequence reflected from the surface of the object 6 to be measured, and samples it through an adaptive sampling strategy

[0035] Based on the projected and captured compressed sampling patterns, sub-images are reconstructed through compressed sensing and then the sub-images are reassembled to obtain the target image, and the image is denoised using a three-dimensional block matching algorithm.

[0036] This system combines the circular sampling method and the variable density sampling method to independently design an adaptive sampling strategy: combining the circular sampling method and the variable density sampling method, performing the first sampling under the condition of undersampling rate, and analyzing the first sampling results to calculate the mean of the absolute value of the Fourier coefficient in each sector, and recording the angles of the first few sectors with the highest mean; then performing the second sampling based on the analysis results, sampling in the directions with the highest mean; finally, if there are any sampling points remaining, they are distributed from low frequency to high frequency using the circular sampling method

[0037] The image is reconstructed using the adaptive compressed sensing algorithm. The specific implementation method is as follows:

[0038] Step 1: Obtain the Fourier coefficients of sea surface fluctuations using the statistical wave model;

[0039] Step 2: Using the Fourier coefficients as prior knowledge, adjust the regularization parameters in the TVL1-L2 algorithm;

[0040] Step 3: Define a new total variable TV in the TVL-L2 algorithm Fourier (u), which can be expressed as:

[0041]

[0042] This term is based on the gradient of the Fourier transform of the image to be restored;

[0043] Step 4: Restore the image by minimizing the objective function containing the total variation term TV_Fourier, where the objective function is:

[0044]

[0045] Among them, f is the observation data, L is the coefficient transformation matrix, and λ and μ are regularization parameters that can be adjusted according to the Fourier characteristics of sea surface fluctuations.

[0046] The light modulation module is specifically as follows: LED matrix 1 uses 16 8×8 LED panels through circuit design and welding to form a 32×32 LED dot matrix, which realizes parallel scanning under FPGA control. Compared with the traditional 32×32 LED integrated panel, its modulation rate is increased by nearly 16 times.

[0047] 1-LED matrix, 2-photodiode, 3-first converging lens, 4-second converging lens, 5-strong scattering medium, 6-object, 7-data acquisition card, 8-FPGA control board, 9-computer

[0048] The control imaging system of the present invention is implemented as follows:

[0049] A single-pixel imaging system can be roughly divided into three parts: the transmitter, the optical path, and the receiver. The LED matrix, controlled by an FPGA, emits a specific pattern onto the LED matrix, thereby modulating the light field. The modulated light field passes through a lens and is illuminated by the target object. The target object reflects the light field, which is ultimately collected by a single-pixel detector. This data is then input to a computer via a data acquisition card. The computer then performs an inverse correlation operation on the Fourier transform pattern sequence loaded into the LED matrix and the light intensity signal from the single-pixel detector to reconstruct an image of the target object.

[0050] The present invention's adaptive underwater single-pixel imaging technology based on Fourier modulation utilizes a self-designed LED array and FPGA-controlled high-speed parallel scanning to increase the modulation rate by 16 times, accelerating the modulation pattern emission rate, thereby reducing underwater single-pixel imaging time and enabling high-speed imaging of underwater targets. By introducing Fourier modulation into the LED array, the image's spatial information is concentrated in the low-frequency portion of the Fourier domain. By focusing both low-frequency and high-frequency information in the Fourier transform domain, both imaging quality and speed are balanced. This overcomes the limitations of random modulation and Hadamard modulation, which cannot balance imaging time and quality. This enables high-quality underwater single-pixel imaging in a short time, laying a technical foundation for real-time ocean detection. The self-designed adaptive sampling strategy ensures the real-time performance of Fourier underwater single-pixel imaging while retaining more detailed information. This enables high-speed, high-quality imaging of underwater targets in low-sampling, high-turbidity waters, producing clear images and ensuring both real-time and clarity of underwater imaging. This presents a comprehensive set of low-cost, high-speed, and high-quality ocean single-pixel imaging methods.

[0051] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents, and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. An adaptive underwater single-pixel imaging method based on Fourier modulation, characterized in that: The following steps are involved: Step 1: Use an error diffusion algorithm to binarize the Fourier pattern for modulation by the LED array. Load the Fourier illumination pattern onto the FPGA control board, which controls the LED array to generate a structured light emission Fourier pattern at high speed. This modulated light is then projected through an imaging lens onto an object plane in highly turbid water. Step 2: Use a four-quadrant detector to collect the light intensity sequence reflected from the surface of the object being measured, and sample it through an adaptive sampling strategy; Step 3: Based on the projected and captured compressed sampling patterns, sub-images are reconstructed through compressed sensing and then reassembled to obtain the target image, and the image is denoised using a three-dimensional block matching algorithm.

2. The underwater single-pixel imaging technology according to claim 1, characterized in that: Sampling is performed using an adaptive sampling strategy. The specific implementation method is as follows: the circular sampling method and the variable density sampling method are combined. Under the condition of undersampling rate, the first sampling is performed, and the results of the first sampling are analyzed to calculate the mean of the absolute value of the Fourier coefficient in each sector, and the angles of the first few sectors with the highest mean are recorded. Then, according to the analysis results, a second sampling is performed in the directions with the highest mean. Finally, if there are any remaining sampling points, they are distributed from low frequency to high frequency using the circular sampling method.

3. The underwater single-pixel imaging technology according to claim 1, characterized in that: The image is reconstructed using the adaptive compressed sensing algorithm. The specific implementation method is as follows: Step 1: Obtain the Fourier coefficients of sea surface fluctuations using the statistical wave model; Step 2: Using the Fourier coefficients as prior knowledge, adjust the regularization parameters in the TVL1-L2 algorithm; Step 3: Define a new total variable TV in the TVL-L2 algorithm Fourier (u), which can be expressed as: This term is based on the gradient of the Fourier transform of the image to be restored; Step 4: Restore the image by minimizing the objective function containing the total variation term TV_Fourier, where the objective function is: Among them, f is the observation data, L is the coefficient transformation matrix, and λ and μ are regularization parameters that can be adjusted according to the Fourier characteristics of sea surface fluctuations.

4. An underwater single-pixel imaging system based on Fourier modulation, characterized in that: The light modulation module, consisting of an FPGA control board and an LED array, is used to pre-generate speckles and obtain the modulated light field corresponding to each speckle. The converging lens module, consisting of a first converging lens and a second converging lens, is used to collect the structured light generated by the LED array, increase the light intensity, and project it onto the underwater target object. It then converges the light transmitted or reflected by the object to improve the signal-to-noise ratio and thus the imaging quality. The receiving module, consisting of a four-quadrant detector, a data acquisition card and a computer, is used to collect the light intensity information of the light reflected or transmitted by the target object in the water, and input it into the computer for calculation and processing to obtain the imaging image of the target object.

5. The underwater single-pixel imaging system according to claim 4, characterized in that: The light modulation module is specifically characterized by an LED array that uses 16 8×8 LED panels through circuit design and welding to form a 32×32 LED dot matrix. It achieves parallel scanning under FPGA control. Compared with the traditional 32×32 LED integrated panel, its modulation rate is nearly 16 times higher.

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