A fast single-pixel imaging method based on galvanometer scanning

Abstract

The application discloses a kind of fast single-pixel imaging methods based on galvanometer scanning, including by the slice and reconstruction of Hadamard matrix to obtain innovative scanning base map;Utilize the modulation process of the continuous scanning of galvanometer to traverse target image, reduce the number of mask patterns that need to be modulated;Based on the way of differential measurement, obtain the Hadamard coefficient of each scanning base map, including obtaining the light intensity value after differential modulation using positive Hadamard scanning base map and negative Hadamard scanning base map, calculate to obtain the Hadamard coefficient of target image;After obtaining the Hadamard coefficient of target image, form Hadamard spectrum, and inverse transform is carried out to the Hadamard spectrum, obtain the reconstructed target image.The application solves the problem of traditional single-pixel imaging technology modulation mask quantity and large memory consumption, shortens the generation time length and imaging time of mask pattern, expands the application prospect of single-pixel imaging technology, especially in industrial parts detection and medical imaging and the like field.

Description

Technical Field

[0001] This invention relates to the field of single-pixel imaging technology, and in particular to a fast single-pixel imaging method based on galvanometer scanning. Background Technology

[0002] Traditional passive Hadamard single-pixel imaging technology uses a light source to illuminate the object to be imaged. The light reflected from the object is focused by a lens or lens group onto the surface of a spatial light modulator with a pre-set structured illumination pattern. Different regions of the object will produce different light intensity variations according to their different characteristics. This series of light intensity values ​​is reflected or transmitted to the photosensitive surface of a single-point detector. The light signal is converted into an electrical signal and stored through a data acquisition device. This method obtains the Hadamard spectrum of the target area through differential measurement and then uses a reconstruction algorithm to reconstruct the image of the object.

[0003] The shortcomings of existing technologies are that traditional single-pixel imaging technologies suffer from problems such as a large number of modulation patterns, long generation time, large memory resource consumption, long preloading time, long modulation time, and low DMD availability. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the existing technology. To achieve the above objective, a fast single-pixel imaging method based on galvanometer scanning is adopted to solve the problems mentioned in the background technology.

[0005] A fast single-pixel imaging method based on galvanometer scanning includes the following steps:

[0006] Step S1: Reconstruct the Hadamard base map by slicing it according to the required resolution of the target to generate a scanning base map;

[0007] Step S2: The modulation process of accurately traversing the target region using the periodic and continuous scanning characteristics of the galvanometer;

[0008] Step S3: Based on differential measurement, capture the light intensity value modulated by the positive and negative Hadamard scan base maps;

[0009] Step S4: Calculate and obtain the Hadamard coefficients at the corresponding frequency points to form the Hadamard spectrum;

[0010] Step S5: Perform an inverse transform on the Hadamard spectrum to obtain the reconstructed target image.

[0011] As a further technical solution of the present invention, the specific steps in step S1 include:

[0012] By studying and analyzing the Hadamard matrix, we can slice the rows or columns of the Hadamard matrix to obtain several first-order row or column vectors.

[0013] The slices are reconstructed by copying to obtain an innovative scan base map, denoted as D. M The scanning base map consists of M column vectors, each denoted as d. M :

[0014] D M =[d1,d2,···,d M ].

[0015] As a further technical solution of the present invention, the specific steps in step S2 include:

[0016] The scanning characteristics of the galvanometer are used to traverse multiple first-order modulation columns in the target region;

[0017] The horizontal resolution of the scan base map depends on the required image resolution.

[0018] As a further technical solution of the present invention, the specific steps in steps S3 and S4 include:

[0019] By employing differential measurement and adapting to the structural characteristics of digital micromirror arrays (DMDs), the mirrors of the DMD are tilted at different angles during operation to reflect or retain light information in the light trap, thereby obtaining a specific coded illumination pattern.

[0020] The Hadamard coefficients Q(u,v) of each scan base map are obtained based on differential measurement:

[0021] Q(u,v)=Y + -Y -

[0022] Among them, Y + and Y - These represent the light intensity values ​​corresponding to the target image after differential modulation by the positive and negative Hadamard scan base maps, respectively. The expression for obtaining the light intensity value is:

[0023]

[0024] In the above formula, Y(N) is the light intensity value, i·K is the number of measurements corresponding to each coded pattern, K is the number of times the light intensity value is repeatedly collected in each modulation process, N is the modulation of the Nth coded pattern and target information, l is the number of light intensity values ​​discarded that belong to the transition state of the digital micromirror array (DMD), and y(x) is the original light intensity value received by the photodetector after being modulated by each mask pattern.

[0025] After calculating the Hadamard coefficients corresponding to the target image using the difference method, the Hadamard spectrum is obtained:

[0026] Q = [Q1, Q2, Q3, ..., QM ].

[0027] As a further technical solution of the present invention, the specific steps in step S5 include:

[0028] The reconstructed target image can be obtained by performing an inverse transform on the Hadamard spectrum.

[0029] P(x,y)=H -1 {Q(u,v)}

[0030] The formula for its reconstruction process is:

[0031] P = H·Q.

[0032] Compared with the prior art, the present invention has the following technical advantages:

[0033] By employing the aforementioned technical solution, an innovative mask pattern is achieved through slicing and reconstructing the Hadamard matrix. The column modulation technique reduces the number of masks required for imaging to 1 / N. Since the Hadamard matrix is ​​a square matrix, only N*N target areas can be reconstructed. However, this technique breaks this limitation; column scanning enables image modulation of non-square targets. Furthermore, periodic galvanometer scanning traverses the target area to complete image reconstruction. The extremely small number of masks significantly reduces the memory consumption and generation / burning time of the pre-loaded mode. Simultaneously, the reduced number of masks leads to a faster modulation process, reducing the imaging time to T / N compared to traditional HIS. Unlike traditional HIS, which is limited to 256*256 resolution due to the 22K memory limit of the DMD, this invention's advantages in modulation technology greatly improve the utilization rate of the DMD, enabling one-time image reconstruction at higher resolutions and significantly improving the imaging efficiency of single-pixel imaging. Attached Figure Description

[0034] The specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings:

[0035] Figure 1 This is a schematic diagram illustrating the steps of a fast single-pixel imaging method according to an embodiment of this application;

[0036] Figure 2 This is a schematic diagram illustrating the principle of obtaining the Hadamard coefficient according to an embodiment of this application.

[0037] Figure 3 This is a schematic diagram illustrating the principle of generating a scan base map according to an embodiment of this application.

[0038] Figure 4 This is a diagram of the experimental apparatus according to an embodiment of this application;

[0039] Figure 5 These are numerical simulation reconstruction results at different sampling rates according to embodiments disclosed in this application;

[0040] Figure 6 This is a reconstruction result diagram based on a fast scan, representing an embodiment disclosed in this application. Detailed Implementation

[0041] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0042] Please refer to Figure 1 A fast single-pixel imaging method based on galvanometer scanning is proposed. This method uses a linear laser mounted on a galvanometer to achieve a precise scanning optical path. Combined with an innovative slice-based reconstruction of the scanning base map, it traverses the partial modulation of the single-pixel imaging, thereby reducing the modulation pattern by 1 / N. The method includes the following steps:

[0043] In this embodiment, as Figure 2 As shown, the fast scanning modulation scheme proposed in this embodiment is based on Hadamard single-pixel imaging. This technique acquires the Hadamard spectrum of the target image and then reconstructs the target image using inverse Hadamard transform. Each row of the target is encoded and modulated by the corresponding shaded portion of each scanning base image. The lateral resolution of the scanning base image depends on the image resolution requirements. After completing multiple scanning cycles, a series of Hadamard coefficients are obtained, thus forming the Hadamard spectrum. Figure 2 The diagram illustrates the principle of obtaining the Hadamard coefficient, and its formula is as follows:

[0044] Q i =P / i·D M

[0045] Among them, Q i Here, D is the Hadamard coefficient, P is the target image, and D is the target image. M For the innovative scanning basis map, the scanning basis map in this implementation is obtained by slicing and copying the Hadamard matrix for reconstruction. Firstly, orthogonal transformation is an important mathematical tool in image processing. It simplifies calculations, ensures that signals from different bases remain independent after transformation, and allows for a more complete and accurate understanding and analysis of signals. Orthogonality is expressed as:

[0046]

[0047] In the above formula, For H NThe transpose of the Hadamard matrix, E, is an orthogonal square matrix. Any two rows (or two columns) of the Hadamard matrix are orthogonal. This orthogonal square matrix consists of +1 and -1 elements, ensuring that signals with different bases remain independent after transformation. The Hadamard matrix H... N Represented as:

[0048]

[0049] Among them, h N It is the Nth row vector of the Hadamard matrix. This is the transpose of the row vector. This implementation designs a Hadamard base map that conforms to a fast scanning mode based on the transformation of the Hadamard matrix. Slicing the original N-order Hadamard base map by rows (or columns) yields N distinct first-order row (or column) vectors, expressed as:

[0050]

[0051] Step S1: Reconstruct the Hadamard base map by slicing it according to the required resolution of the target to generate a scanning base map. The scanning base map is denoted as D. M The scanning base map consists of M column vectors, each denoted as d. M :

[0052] D M =[d1,d2,···,d M ]

[0053] In this embodiment, a specific implementation step is to use Hadamard single-pixel imaging technology to quickly scan and collect light intensity through the scanning base map reconstructed by DMD projection slicing, and obtain a 256x256 resolution target image of the target through inverse transformation.

[0054] Step S2: The modulation process of precisely traversing the target region using the periodic and continuous scanning characteristics of the galvanometer. Specifically, the scanning characteristics of the galvanometer are used to traverse multiple first-order modulation columns of the target region; wherein, the lateral resolution of the scanning base map depends on the image resolution requirements.

[0055] In this embodiment, a specific implementation step is as follows:

[0056] Step S3: Based on differential measurement, capture the modulated light intensity value obtained from the positive and negative Hadamard scan base maps. The specific steps include:

[0057] By employing differential measurement and adapting to the structural characteristics of digital micromirror arrays (DMDs), the mirrors of the DMD are tilted at different angles during operation to reflect or retain light information in the light trap, thereby obtaining a specific coded illumination pattern.

[0058] Step S4: Calculate and obtain the Hadamard coefficients at the corresponding frequency points to construct the Hadamard spectrum; wherein, the specific steps in steps S3 and S4 include:

[0059] The Hadamard coefficients Q(u, v) of each scan base map are obtained based on differential measurement:

[0060] Q(u, v) = Y + -Y -

[0061] Among them, Y + and Y - These represent the light intensity values ​​corresponding to the target image after differential modulation by the positive and negative Hadamard scan base maps, respectively. The expression for obtaining the light intensity value is:

[0062]

[0063] In the above formula, Y(N) is the light intensity value, i·K is the number of measurements corresponding to each coded pattern, K is the number of times the light intensity value is repeatedly collected in each modulation process, N is the modulation of the Nth coded pattern and target information, l is the number of light intensity values ​​discarded that belong to the transition state of the digital micromirror array (DMD), and y(x) is the original light intensity value received by the photodetector after being modulated by each mask pattern.

[0064] In this embodiment, a specific implementation step is as follows: Figure 3 The diagram illustrates the principle of scanning basemap generation. It's an example of generating a scanning basemap by reconstructing a slice of an 8th-order Hadamard matrix, with M column vectors constituting one scanning basemap. The scanning basemap designed in this implementation is denoted as D. M Modulation of the target image region is achieved through scanning by a precision optical system, combined with multi-frame projection by the DMD, and synchronization of the driving and acquisition devices. Besides the projection speed of the DMD, a faster scanning device means a higher imaging rate. The scanning base map consists of multiple column vectors, each denoted as d. M :

[0065] D M =[d1,d2,···,d M ]

[0066] To enhance the anti-interference capability of Hadamard single-pixel imaging, differential measurement is typically employed. The differential mode is well-suited to the structural characteristics of the DMD (Digital Microdisk). During operation, the DMD tilts its mirrors at different angles to reflect or retain light information in the optical trap, thus realizing a specific coded illumination pattern. Differential HSI (Hyper-Hyper-Intensity Sequencing) is a manifestation of HSI, allowing the acquisition of individual Hadamard coefficients Q(u, v) through differential measurement.

[0067] Q(u, v) = Y + -Y1

[0068] Among them, Y + and Y - These represent the light intensity values ​​corresponding to the target image after differential modulation by the positive and negative Hadamard scan base maps, respectively. The expression for obtaining the light intensity value is:

[0069]

[0070] In the above formula, Y(N) is a set of light intensity values, i·K is the number of measurements corresponding to each coded pattern, K is the number of times the light intensity value is repeatedly collected in each modulation process, N is the modulation of the Nth coded pattern and target information, l is the number of light intensity values ​​discarded that belong to the transition state of the digital micromirror array (DMD), and y(x) is the original light intensity value received by the photodetector after being modulated by each mask pattern.

[0071] After calculating the Hadamard coefficients corresponding to the target image using the difference method, the Hadamard spectrum is obtained:

[0072] Q = [Q1, Q2, Q3, ..., Q M ].

[0073] Step S5: Perform an inverse transform on the Hadamard spectrum to obtain the reconstructed target image.

[0074] In this embodiment, the reconstructed target image can be obtained by performing an inverse transform on the Hadamard spectrum:

[0075] P(x,y)=H -1 {Q(u,v)}

[0076] The formula for its reconstruction process is:

[0077] P = H·Q.

[0078] In this example, the galvanometer traverses all regions (N*M) of the image during rapid scanning, performing 1 / 2N measurements per frame. Therefore, when using the scanning base map proposed in this embodiment for Hadamard single-pixel imaging, only 2N coded patterns are needed, reducing the number of preloaded modes by 1 / N compared to traditional Hadamard imaging techniques. This significantly reduces loading time and modulation time required for imaging. The row-by-row (column) modulation imaging characteristic means that the imaging method proposed in this embodiment is no longer limited to a square target area in terms of resolution, and no longer requires partitioned measurements and stitching to be compatible with image reconstruction at different resolutions.

[0079] like Figure 4As shown in the diagram, this is the experimental setup for the rapid column scanning single-pixel imaging experiment in this embodiment. The light source is a 650nm wavelength externally focused laser with a power of 50mW, fixed using a multi-axis displacement stage with a micrometer head. The laser beam illuminates a galvanometer driven by a stable, continuous triangular wave signal. The driving signal voltage and frequency values ​​form a certain mathematical logic relationship with the scanning area size and scanning speed, generating a continuous and periodic precision optical scanning area. In other words, rapid scanning of the optical path is achieved through synchronous coordination between hardware devices, illuminating the target area image. The illumination light signal carrying target information is synchronously reflected onto a DMD micromirror with a preset coded pattern. A fixed photodetector captures changes in light intensity, converting the light signal into an electrical signal, which is then synchronously acquired using an oscilloscope.

[0080] To verify the effectiveness of the reconstructed images, numerical simulations were conducted using two images of "Bird" and "flower" with different features and complexities at a resolution of 512*768 to simulate the proposed method. Structural Similarity (SSIM), a widely accepted metric in digital image processing, was used to quantitatively analyze the reconstruction performance of the proposed method in principle. The SSIM value ranges from -1 to 1; a value closer to 1 indicates a closer reconstructed image to the original. Its expression is:

[0081]

[0082] Among them, u i and u j These are the average values ​​of the original image and the reconstructed image, respectively. and σj 2 The variances of i and j are σ and j, respectively. ij It is the covariance of i and j.

[0083] like Figure 5 As shown, the reconstruction results and corresponding structural similarity indices at different sampling rates (sap) in numerical simulation are displayed. As the sampling rate decreases, the image quality begins to degrade, and when the sampling rate is too low, mosaic artifacts will be introduced.

[0084] Table 1 Comparison of various parameters between traditional HIS and this technology

[0085]

[0086] Table 1 shows the performance of two techniques in image reconstruction through numerical comparison (the computing device used for the data in this table can be an NVIDIA GeForce RTX 4080 graphics card). The comparison demonstrates that this technique has significant advantages, greatly reducing the number of projection modulation patterns, thereby reducing the memory requirements and burning time of the pre-loading mode, and showing a clear advantage in reducing image reconstruction time. This implementation has made significant innovations in improving single-pixel imaging efficiency and reducing memory requirements.

[0087] like Figure 6 As shown in the figure, the reconstruction result based on fast scanning demonstrates the image reconstruction effect at a resolution of 256*256 under different complexity features. This implementation achieves modulation reconstruction of the target area using only 512 mask patterns. In contrast, traditional Hadamard single-pixel imaging technology requires 131,072 mask patterns, and even under 1% compression sampling, it requires 1,250 modulation patterns. The modulation scheme used in this implementation requires fewer masks than the traditional HIS undersampling method with 1% compression, demonstrating the great potential for reducing memory resource consumption and improving imaging efficiency in the field of single-pixel imaging.

[0088] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention. The scope of the invention is defined by the appended claims and their equivalents, all of which should be included within the scope of protection of the invention.

Claims

1. A fast single-pixel imaging method based on galvanometer scanning, characterized in that, Includes the following steps: Step S1: Reconstruct the Hadamard base map by slicing it according to the required resolution of the target to generate a scanning base map. The specific steps include: By studying and analyzing the Hadamard matrix, the columns of the Hadamard matrix are sliced ​​to obtain several first-order column vectors; The slice is reconstructed by copying to obtain an innovative scan base map, denoted as [missing information]. The scanning base map consists of M column vectors, each denoted as . : ； Step S2: The modulation process of accurately traversing the target region using the periodic and continuous scanning characteristics of the galvanometer; Step S3: Based on differential measurement, capture the light intensity value modulated by the positive and negative Hadamard scan base maps; Step S4: Calculate and obtain the Hadamard coefficients at the corresponding frequency points to construct the Hadamard spectrum. The specific steps include: By employing differential measurement and adapting to the structural characteristics of digital micromirror arrays (DMDs), the mirrors of the DMD are tilted at different angles during operation to reflect or retain light information in the light trap, thereby obtaining a specific coded illumination pattern. The Hadamard coefficients of each scan base map are obtained based on differential measurement. : in, and These represent the light intensity values ​​corresponding to the target image after differential modulation by the positive and negative Hadamard scan base maps, respectively. The expression for obtaining the light intensity value is: In the above formula, This is the light intensity value. It is the number of measurements corresponding to each coded pattern. It is the number of times the light intensity value is repeatedly sampled during each modulation process. It corresponds to the first The encoded pattern and target information are modulated. It refers to the number of light intensity values ​​discarded that belong to the transition state of the digital micromirror array (DMD). It is the original light intensity value received by the photodetector after being modulated by each mask pattern; After calculating the Hadamard coefficients corresponding to the target image using the difference method, the Hadamard spectrum is obtained: ； Step S5: Perform an inverse transform on the Hadamard spectrum to obtain the reconstructed target image.

2. The fast single-pixel imaging method based on galvanometer scanning according to claim 1, characterized in that, The specific steps in step S2 include: The scanning characteristics of the galvanometer are used to traverse multiple first-order modulation columns in the target region; The horizontal resolution of the scan base map depends on the required image resolution.

3. The fast single-pixel imaging method based on galvanometer scanning according to claim 1, characterized in that, The specific steps in step S5 include: The reconstructed target image can be obtained by performing an inverse transform on the Hadamard spectrum. The formula for its reconstruction process is: 。

Images