A differential-based white light lensless single-frame weak-conjugate reconstruction method

Abstract

The application provides a differential-based white light lensless single-frame weakly conjugate reconstruction method, which can realize weakly conjugate image reduction and improve single-frame imaging resolution in a white light lensless imaging system without using additional elements and complex algorithms. The method comprises the following steps: step one, obtaining spectral distribution information of a system light source by using a spectrometer and performing differential processing to obtain a reconstruction wavelength; step two, performing preprocessing on a collected single-frame image by using a hologram average value reduction method; step three, generating light intensity diagrams of different defocusing surfaces by using an angular spectrum propagation formula, and determining a defocusing distance range based on a definition discrimination factor; and step four, calculating differential distribution on different focal planes in the distance range obtained in step three based on numerical differentiation, and obtaining a final result by selection. The application can reduce the requirement of spectral width of a traditional lensless microscope, effectively reduce the cost of the system, improve the imaging resolution of the white light lensless microscope, and reduce the weakly conjugate image in the case of single-frame image collection.

Description

Technical Field

[0001] This invention relates to the field of lensless microscopy imaging technology, and in particular to a differential white light lensless single-frame weak conjugate reconstruction method. Background Technology

[0002] Since its invention in the late 16th century, the optical microscope has been used for microscopic observation, such as biomedical detection and analysis, and the observation of microscopic particles. With the rapid development of semiconductor and other technologies, phase-contrast microscopes, differential interference microscopes, and confocal microscopes have gradually emerged. These microscopes have greatly improved our understanding of the microscopic world, providing strong evidence for disease diagnosis and drug development, and have become indispensable tools in modern clinical medicine and biopharmaceuticals. A key characteristic of these optical microscopic results is their "what you see is what you get" imaging mode. However, a significant drawback is that this mode is limited by the developmental bottlenecks of hardware devices, hindering further improvements in imaging results. Furthermore, without innovation in the function and performance of microscopic imaging systems, the entire system has become increasingly expensive, bulky, and complex. Therefore, while ensuring image quality, a lensless microscopic imaging system has emerged. This system is low-cost, small in size, and easy to operate, providing a fast and inexpensive point-of-care diagnostic tool for regions with limited resources.

[0003] Lensless microscopy, as a novel large-field-of-view, high-resolution microscopy technique, overcomes the contradiction between simultaneously achieving high resolution and large field of view, and has experienced rapid development in the last decade or so. A key factor enabling the entire system to achieve low cost and small size is the "lensless" design. It abandons the expensive optical lenses of traditional microscopy systems, relying on the sample's internal absorption or refractive index differences (which can cause phase differences) for label-free imaging, thus greatly simplifying the sample preparation process. In lensless microscopy, a key factor limiting reconstruction quality (such as resolution) is the coherence of the light source in the imaging system (including temporal and spatial coherence). LED light sources have a smaller size, but their temporal and spatial coherence is relatively worse than laser light sources. Therefore, to obtain better imaging results, a certain amount of system size and cost is generally sacrificed by using lasers as the system light source, or the system complexity is slightly increased by adding filters to the LED light source. Furthermore, lensless microscopes generally employ a coaxial transmission structure, meaning that the object beam modulated by the object and the reference beam are coaxial. Combined with the elimination of lenses in the system structure, the acquired images are non-focused intensity images. Traditionally, angular spectral propagation is used to backpropagate the acquired image to obtain the intensity map of the object on the focal plane. Since ordinary image sensors only record intensity information and lose the object's phase information, the backpropagated image contains conjugate images superimposed on the actual object image. To remove these conjugate images, i.e., to recover the object's phase information, Aydogan Ozcan et al. proposed several methods for removing conjugate images (recovering phase), such as multi-angle illumination, multi-wavelength illumination, and multi-height displacement, to obtain multiple diffraction images of the object, thereby using corresponding algorithms to achieve phase recovery. However, these methods rely on precise mechanical movements, such as a 1-arc-second precise rotation stage, or tunable multi-wavelength light sources (requiring high-precision wavelength-tunable lasers). These mechanical structures increase system cost and reduce robustness; algorithmically, they require acquiring multiple intensity maps and corresponding iterative algorithms, significantly increasing reconstruction time. Therefore, how to achieve lensless deconjugate imaging using only a simple algorithm based on a low-cost lensless microscopy system with simple structure and easy experimental operation (such as a lensless basic structure based on a white light source) has become a technical challenge that must be overcome in lensless microscopy technology. Summary of the Invention

[0004] To address the technical challenges of high light source coherence requirements, large data acquisition volumes, and relatively complex algorithms in current lensless microscopy, a differential-based single-frame weak conjugate reconstruction method for white light lensless microscopy is proposed.

[0005] The inventive concept of this invention is as follows: a differential-based single-frame weak conjugate reconstruction method for white light without lenses. First, a function is constructed to fit the spectral distribution of the light source. The fitted function is then differentially processed to obtain the reconstructed wavelength. Next, the acquired single-frame image is preprocessed using the hologram subtraction average method. Then, the defocus distance range is determined based on the sharpness discrimination factor. Finally, the light intensity difference distribution on different focal planes within the defocus distance range is calculated, and the optimal result is obtained.

[0006] To achieve the above-mentioned objectives, the present invention employs the following technical solution: a differential-based method for reconstructing weak conjugate single-frame white light without lenses, comprising the following steps:

[0007] 1. Obtain the spectral distribution information of the system's white light source using a spectrometer, propose a specified function for fitting, and perform difference processing on the fitted function to obtain the reconstructed wavelength;

[0008] 2. Preprocess the acquired single-frame images using the hologram subtraction average method;

[0009] 3. Generate light intensity maps of different defocus surfaces using the angular spectrum propagation formula, and determine the defocus distance range based on the sharpness discrimination factor;

[0010] 4. Based on the numerical difference and the preprocessed acquired image, calculate the difference distribution on different focal planes within the distance range obtained in step three, and select the best result to obtain the final result.

[0011] Preferably, step 1 specifically includes the following steps:

[0012] 1.1 Use a spectrometer to measure the white light source and derive the wavelength and its corresponding relative light intensity data.

[0013] 1.2 The light intensity varies with different wavelengths, and the existing white light source has a non-standard Gaussian distribution. Therefore, the following function is specified to fit the relative light intensity data.

[0014]

[0015] The wavelength of light. This represents the relative intensity distribution of the spectrum. , , The coefficients are to be fitted. For the order, The number of maxima in the data to be fitted should be 1-3 times the number of maxima. Actual white light sources may have color casts, as they are essentially composed of a mixture of multiple primary colors. The value is generally a positive integer greater than 1.

[0016] 1.3 The fitted function pairs The partial derivative is noted as And determine the distribution after partial derivatives. The wavelength value corresponding to the maximum value in the middle is the wavelength required for subsequent reconstruction. If we want to find the distribution after partial derivatives... If there are multiple maximum values ​​of equal value, that is, multiple wavelength values, then one of them is selected as the reconstructed wavelength.

[0017] Preferably, step 2 specifically includes the following process:

[0018] Considering that the object under test is a weakly diffractive object, the specific process of this step is as follows: the directly acquired light intensity map is... , The coordinates are the discrete images acquired by the imaging sensor, and are all positive integers. Using the formula... Obtain the processed holographic image, where,

[0019]

[0020] and These are the number of pixels in the horizontal and vertical directions of the discretized image acquired by the imaging sensor, respectively, both being positive integers.

[0021] Preferably, step 4 specifically includes the following steps:

[0022] 4.1 The defocus distance range determined in step 3 is: ( ),by The step size (the step size can be chosen based on actual needs) This generates light intensity maps at different distances within the defocus range. , , This represents rounding down; (specifically, yes ( The light intensity map generated at point ) yes ( The light intensity map generated at ().

[0023] 4.2, in Difference is performed on the generated intensity map in the direction, that is... The distribution map obtained by subtracting adjacent light intensity distributions is denoted as . ;

[0024] 4.3, in Utilize clarity discrimination factors or prior knowledge to select the optimal result.

[0025] Preferably, the distance between the white light source and the sample to be tested is... The distance between the sample to be tested and the imaging sensor The ratio between them satisfies the following conditions:

[0026]

[0027] in, The diameter of the white light source. The smallest size that needs to be identified in the sample to be tested is the highest resolution to be tested.

[0028] Compared with the prior art, the present invention has the following significant advantages: (1) It can further reduce the requirements of the time coherence of the light source in the existing lensless microscopic imaging system, thereby simplifying the system complexity and reducing the cost. (2) By using the hologram subtraction average method to preprocess the single-frame image acquired under white light, the reconstructed conjugate image can be weakened, thereby improving the background quality of lensless differential imaging. (3) Pre-determining the reconstruction distance range can speed up the subsequent differential reconstruction. (4) Performing differential processing within a reliable reconstruction distance range improves the resolution of single-frame reconstruction under low spatiotemporal coherence. Attached Figure Description

[0029] The accompanying drawings are provided to further illustrate the invention and form part of the specification.

[0030] Figure 1 This is a schematic diagram of the basic structure of the system to which this invention applies.

[0031] Figure 2 This is the overall flowchart of the differential-based white light lensless single-frame weak conjugate reconstruction method.

[0032] Figure 3 The images show the reconstruction results of a lensless single-frame weak conjugate reconstruction method based on difference, where (a) represents the theoretically reconstructed high-resolution image; (b) shows the curve after fitting the white light source distribution and the distribution curve after difference; (c) is the defocused image acquired in the simulation; (d) is the image after preprocessing the acquired defocused image; (d1) is the reconstruction distance range curve determined based on angular spectrum propagation; (d2)-(d4) are the difference results on different surfaces within the reconstruction distance range (in this special case, (d3)). (This is the final reconstruction result).

[0033] Figure 4 The actual distribution curve of a white light source composed of a mixture of multiple primary colors.

[0034] Figure 5 In special cases The results are compared between the traditional method (direct angular spectrum propagation), the differential imaging method without preprocessing, and the results of this invention. (a) represents the result after direct angular spectrum propagation using the traditional method; (b) represents the result of direct differential reconstruction without preprocessing; and (c) represents the reconstruction result based on this invention. Detailed Implementation

[0035] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings. Of course, the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0036] This invention discloses a differential-based white-light lensless single-frame weak conjugate reconstruction method for lensless microscopy imaging systems. The basic structure of this system typically consists of three parts: a partially coherent or coherent light source, a sample, and an imaging sensor. Based on this invention, the temporal coherence of the light source can be extended to a white light source. The white light source, serving as the illumination source for the lensless microscope, is directly positioned above the sample, and the emission center of the light source is located on the optical axis of the entire imaging system.

[0037] Combination Figure 1 The distance between the white light source and the upper surface of the sample in the lensless microscopic imaging system of this invention is... Generally in Between the imaging sensor and the sample Generally in Between them, because the spatial coherence of a typical white light source is also poor, the larger Spatial coherence can be improved without adding any optical elements (such as pinholes). Based on this, the temporal coherence of the light source becomes a limitation of lensless microscopy.

[0038] Based on this invention, the parameter requirements of each component in the entire lensless imaging system can be greatly reduced without adding additional components. Combined with... Figure 2 The present invention proposes a differential-based method for reconstructing weak conjugate single-frame white light without lenses, the steps of which include:

[0039] Step 1: Use a spectrometer to obtain the spectral distribution information of the white light source of the system, propose a specified function for fitting, and perform difference processing on the fitted function to obtain the reconstructed wavelength.

[0040] Specifically, the first step is to use a spectrometer to measure the white light source, which will yield curve data of wavelength and normalized relative light intensity.

[0041] Next, analyze the curve data. Combined with... Figure 3In diagram (b), the curve distribution theoretically follows a rectangular function. Therefore, taking the partial derivative of this function yields two impulse functions. These impulse functions correspond to two wavelengths, either of which can be used as the wavelength for subsequent reconstruction. Combined with... Figure 4 White light sources may exhibit significant color casts, resulting in a non-standard function distribution with multiple extreme points in the derived curve. Therefore, a fitting function needs to be constructed for practical applications. In this invention, the following fitting function is constructed for the distribution of most white light sources:

[0042]

[0043] The wavelength of light. This represents the relative intensity distribution of the spectrum. , , The coefficients are to be fitted. For the order, This represents the number of maxima in the data to be fitted; in actual experiments, to achieve higher fitting accuracy, The value is typically set to three times the number of maxima in the data to be fitted.

[0044] Finally, the fitted function pairs The partial derivative is noted as And determine the distribution after partial derivatives The wavelength value corresponding to the maximum value in the middle is the wavelength required for reconstruction in the subsequent step four. If we want to find the distribution after partial derivatives... If there are multiple maximum values ​​of equal value, corresponding to multiple wavelength values, then one of them is selected as the reconstructed wavelength. .

[0045] Step two: The entire lensless imaging process can be viewed as the interference complex amplitude generated by the light scattered by the object under test and the unmodulated reference light passing directly through the sample. The light field carrying the object light information will propagate a distance and eventually be captured by the sensor. The directly acquired light intensity map is as follows: , The coordinates are the discrete images acquired by the imaging sensor, and are all positive integers. Assume... . and These refer to the complex light field distributions (i.e., the object light and the reference light) on the acquisition plane of the imaging sensor. The purpose of reconstruction in lensless imaging is to directly acquire the light intensity image from the imaging sensor. (i.e., the square of a complex number) reconstructs the amplitude and phase distribution of the object light. The square of the complex number leads to the loss of argument information. Therefore, to mitigate the conjugate image generated by this information loss during subsequent reconstruction, the specific process in this invention is as follows: using the formula... Obtain the processed holographic image, where,

[0046]

[0047] and These are the number of pixels in the horizontal and vertical directions of the discretized image acquired by the imaging sensor, respectively, both being positive integers.

[0048] Step 3: Considering that the data acquired by current image sensors is discrete, in order to keep the image size unchanged before and after the propagation process, this invention uses angular spectrum propagation as the basic method of back propagation to obtain the reconstruction information on each plane, and determines the approximate reconstruction distance based on the Sobel discriminant factor.

[0049] The specific process is as follows: First, obtain the frequency domain effect transfer function of free light propagation in the air in the system:

[0050]

[0051] Secondly, combining Figure 1 The acquired image distribution is the result of a light field carrying object light information propagating over a distance. The information collected later, therefore the entire reconstruction process can be recorded as follows:

[0052] .

[0053] in, for in the formula The value is negative, indicating the backward propagation distance of the acquired image. ,also In The value is generally 1. Corresponding The median of the range. Since the exact distance the object has traveled forward is unknown, therefore, for the purposes of this invention, Based on the actual system setup and experience, a general range is given here. For example.

[0054] Finally, with The step size (the step size can be chosen based on actual needs) ),Will The value of traverses the range of the above examples. 400 different Value. For these different Its clarity is quantified using the Sobel function as a standard:

[0055]

[0056] in, , , It is a convolution.

[0057] This way you can get 400 different ones. Value, these Values ​​and different defocus distances A curve is formed between these points, and the values ​​near the maximum value on this curve are selected. The range is used as the defocus distance range ( ).

[0058] Step four: Differentiate the axial light intensity and select the optimal solution as the final imaging result.

[0059] Specifically, firstly, based on the defocus distance range determined in step three... ( ),by The step size (the step size can be chosen based on actual needs) (This involves) generating light intensity maps at different distances within the defocus range using a pre-processed single-frame image. , , This represents rounding down to the nearest integer. yes ( The light intensity map generated at point ) yes ( The light intensity map generated at (). As a special case, its specific generation process can be recorded as follows:

[0060]

[0061] middle Values .

[0062] Secondly, obtain On a defocused surface Afterwards, Difference is performed on the generated intensity map in the direction, that is... Adjacent light intensity distributions subtract from each other, i.e. , can Obtain within range Amplitude difference distribution plot, can be denoted as Ultimately, it utilizes sharpness discrimination factors or prior knowledge, combined with Figure 3 From (d2) to (d4), the final selection can be made. The optimal result is found at this point.

[0063] To test a differential-based single-frame weak conjugate reconstruction method for white light without lenses. Figure 3 In (c), the defocus resolution plate directly acquired in the simulation is a special case. Different methods are used to reconstruct it, and the results are compared. The reconstructed imaging results are as follows: Figure 5 As shown. Figure 5 In the middle (a), the result is obtained after the traditional method, i.e., direct angular spectrum propagation; Figure 5 In the middle (b), the result of differential imaging without preprocessing (i.e., the reconstruction result without step two) is shown. Figure 5 (c) Based on the reconstruction results of this invention. It can be found that... Figure 5 Both (b) and (c) provide more detailed information than (a), i.e., higher reconstruction resolution, while the reconstruction results based on the present invention... Figure 5 The medium (c) image provides better background information than the medium (b) image, while reducing the influence of the conjugate image, thus achieving a good signal-to-noise ratio.

[0064] The parameters described above are merely embodiments of the present invention and are 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 within the protection scope of the present invention.

Claims

1. A differential-based method for reconstructing weak conjugate single-frame white light without lenses, characterized in that, Includes the following steps: The spectral distribution information of the white light source of the lensless microscopy system is obtained and fitted with a function. The fitted function is then subjected to difference processing to obtain the reconstructed wavelength. The lensless microscopic imaging system includes a white light source, a sample to be tested, and an imaging sensor arranged from top to bottom, with the light emission center of the light source located on the optical axis of the entire imaging system. Preprocessing is performed on single-frame images acquired by the imaging sensor to obtain processed holographic images; The light intensity maps of different defocus surfaces are generated based on the original acquired image using the angular spectrum propagation formula, and the defocus distance range is determined based on the sharpness discrimination factor. Based on the acquired images after numerical difference processing and preprocessing, the difference distribution on different focal planes within the obtained distance range is calculated, and the best result is selected to obtain the final result; The process involves obtaining the spectral distribution information of the system's white light source using a spectrometer, proposing a specified function for fitting, and then performing differential processing to obtain the reconstructed wavelength. This includes the following steps: Using a spectrometer, the white light source is measured, and the wavelength and its corresponding relative light intensity data are derived. Use the following function to fit the relative light intensity data: ； The wavelength of light. This represents the relative intensity distribution of the spectrum. , , The coefficients to be fitted are... For the order, The number of maxima in the data to be fitted should be 1-3 times the number of maxima in the data to be fitted. The fitted function pairs Find the partial derivative and determine the wavelength value corresponding to the maximum value in the distribution after partial derivative. This wavelength value is the wavelength required for subsequent reconstruction. If the distribution function after partial derivative has multiple equal maximum values, corresponding to multiple wavelength values, then select one as the reconstruction wavelength.

2. The differential-based single-frame weak conjugate reconstruction method for white light without lenses according to claim 1, characterized in that... The preprocessing of the acquired single-frame image is performed using the hologram subtraction averaging method. Specifically, the light intensity map directly acquired by the imaging sensor is as follows: , The coordinates of the discretized image acquired by the imaging sensor are all positive integers; using the formula... Obtain the processed holographic image, where, ； and These are the number of pixels in the horizontal and vertical directions of the discretized image acquired by the imaging sensor, respectively, both being positive integers.

3. The differential-based single-frame weak conjugate reconstruction method for white light without lenses according to claim 1, characterized in that... The difference distribution on different focal planes within the selected distance range is calculated using numerical difference and preprocessed acquired images. The optimal result is then selected to obtain the final result, including the following steps: by As the step size, with To reconstruct the wavelength, a defocus distance range is generated. Light intensity map at different distances within , , This represents rounding down; yes The light intensity map generated at that location, yes The light intensity map generated at that location; exist Difference is performed on the generated intensity map in the direction, that is... The distribution map obtained by subtracting adjacent light intensity distributions is denoted as . ; exist Utilize clarity discrimination factors or prior knowledge to select the optimal result.

4. The differential-based single-frame weak conjugate reconstruction method for white light without lenses, as described in claim 1, is characterized in that... Distance between white light source and sample The distance between the sample to be tested and the imaging sensor The ratio between them satisfies the following conditions: ； in, The diameter of the white light source. The smallest size that needs to be identified in the sample to be tested is the highest resolution to be tested.

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