Lensless microscopic imaging system single-frame self-focusing method

Abstract

The invention discloses a single-frame self-focusing method of a lensless microscopic imaging system, which comprises the following steps of: irradiating a sample by using a light source with a single wavelength, collecting light intensity distribution under the wavelength, carrying out back propagation on a collected light intensity graph by using an angular spectrum propagation formula, generating light field distribution of different defocusing surfaces in a pre-estimated defocusing distance range, and carrying out self-focusing on the light field distribution of the different defocusing surfaces in the pre-estimated defocusing distance range. The light field complex amplitude module values of different out-of-focus planes are subtracted from the root opening number of the collected light intensity distribution and then squared, all pixel values in all matrixes obtained through squaring are summed, each out-of-focus plane corresponds to one summed value, and the corresponding values on all the out-of-focus planes jointly form a one-dimensional matrix. Second-order derivation is carried out on the one-dimensional matrix, modulus values of curve distribution obtained after derivation are obtained, and the defocus distance corresponding to the maximum value in the finally obtained curve distribution is the final result. According to the invention, the focusing surface of the lensless microscopic imaging system can be rapidly and accurately determined under the condition of a single frame.

Description

Technical Field

[0001] The invention relates to a self-focusing method in lens-free microscopic imaging, and in particular to a self-focusing method based on a single-frame image. Background Art

[0002] With the development of modern science and technology, optical microscopy technology plays an increasingly important role in biomedicine, materials science, microelectronics and other fields. Traditional microscopes rely on optical lenses for magnification and focusing, and obtain high-resolution and high-magnification microscopic images through complex optical designs. However, traditional optical microscopy systems have limitations such as large size, high price, and complex structure, especially in terms of portability and miniaturization applications.

[0003] In order to solve these problems, lensless imaging technology came into being. The lensless imaging system does not rely on lens components, but directly records the light field information of the object through the principles of light diffraction / scattering, and uses computational algorithms to restore the microscopic image of the object. Lensless imaging can not only greatly simplify the optical system and reduce costs, but also achieve high-resolution imaging with a large field of view. Especially in fields that require portable devices such as medical testing, food safety, and environmental monitoring, lensless imaging has broad application prospects. However, in the practical application of lensless imaging technology, how to accurately achieve automatic focusing of the sample is an important issue. Traditional microscopic imaging systems rely on manual or automatic adjustment of the distance between the objective lens and the sample to achieve precise focusing, but this method is not suitable for lensless imaging systems. Since the lensless system does not contain a traditional imaging lens, the light field information of the sample will be recorded on the imaging sensor in the form of a diffraction image, resulting in large differences in images on different defocus planes. Therefore, finding an efficient and accurate focusing method suitable for lensless imaging has become one of the research hotspots.

[0004] At present, the self-focusing methods in lensless microscopy can be roughly divided into two categories according to the number of collected images: focusing methods based on multi-frame images and focusing methods based on single-frame images. The focusing method based on multi-frame images needs to collect images under different parameters multiple times, such as collecting multiple frames of images under different wavelengths of illumination, and gradually adjust the focus plane through a wavelength-dependent reconstruction algorithm so that the imaging results of all wavelengths can achieve the best focus on a certain plane. However, there are some significant shortcomings in the multi-frame focusing method. First, the multiple image acquisition process under different channels increases the complexity and time cost of the method, especially in the real-time imaging scenario, which cannot meet the requirements of high efficiency and speed. Secondly, calculating the consistency of the reconstructed data under different channels increases the data processing time. The focusing method based on a single-frame image generally estimates the focus plane using a clarity discrimination factor, which depends on information such as image contrast and gradient, and is easily affected by factors such as noise and illumination changes, resulting in low focusing accuracy. In addition, due to the conjugate image problem in the lensless imaging system, these conjugate images often interfere with the calculation of the clarity discrimination factor, further reducing the focusing effect.

[0005] Therefore, how to quickly and accurately determine the focal plane with the least amount of data (i.e., in a single frame) without relying on traditional edge detection factors or data consistency is an important challenge facing lensless microscopy technology. Summary of the invention

[0006] Purpose of the invention: In view of the above-mentioned prior art, a single-frame self-focusing method for a lensless microscopic imaging system is proposed, which can achieve accurate acquisition of the reconstructed distance in lensless single-frame microscopic imaging.

[0007] Technical solution: A single-frame self-focusing method for a lensless microscopic imaging system, comprising:

[0008] Step 1: Use a single wavelength light source to illuminate the sample and collect the single frame diffraction light intensity distribution I of the sample;

[0009] Step 2: Estimate the defocus range of the imaging system, and use the angular spectrum propagation formula to perform back propagation on the collected light intensity distribution I within the range to generate the light field distribution at different defocus distances;

[0010] Step 3: The square root of the complex amplitude modulus of the light field on different defocus planes generated by back propagation and the collected light intensity distribution Subtract first and then square;

[0011] Step 4: For each matrix obtained by squaring step 3, sum the elements and then perform two derivatives. The defocus distance corresponding to the maximum value in the obtained curve distribution is the final defocus distance.

[0012] Furthermore, the step 2 includes the following specific steps:

[0013] The estimated defocus distance range is z1~z m , with step as the step length, z1~z m The defocus distance within the range is traversed, and the collected light intensity distribution I is back-propagated using the angular spectrum propagation formula to generate the light field distribution U at different distances 1 ~U n ,n=floor[(z m -z1) / step]+1, floor means taking downward, and the step size step ranges from 0.1μm to 5μm.

[0014] Furthermore, the step 3 includes the following specific steps:

[0015] Step 3.1: The light field distribution U obtained in step 2 1 ~U n Take the modulus value |U 1 |~|U n |;

[0016] Step 3.2: Subtract the square root of the acquired light intensity distribution from the value after taking the modulus value, and record them in sequence as

[0017] Step 3.3: Square the values ​​obtained in 3.2 and record them as D in order. 1 ~D n .

[0018] Furthermore, the step 4 includes the following specific steps:

[0019] Step 4.1: For D obtained in step 3 1 ~D n Each element in the matrix is ​​summed up, and the result is recorded as ∑∑D 1 ~∑∑D n ;

[0020] Step 4.2: For ∑∑D 1 ~∑∑D n First, perform a derivation, and the derivation results are recorded as ∑∑D' 1 ~∑∑D' n-1 ;

[0021] Step 4.3: For ∑∑D' 1 ~∑∑D' n-1 Derivation is performed again, and the derivative results are recorded as ∑∑D" 1 ~∑∑D” n-2 ;

[0022] Step 4.4: ∑∑D” 1 ~∑∑D”n-2 Take the modulus, and record it in sequence as |∑∑D" 1 |~|∑∑D” n-2 |;

[0023] Step 4.5: |∑∑D” 1 |~|∑∑D” n-2 |The serial number corresponding to the maximum value in is recorded as k, then z1+(k+1)×step is the final defocus distance.

[0024] Beneficial effect: The present invention first uses a single wavelength light source to illuminate the sample, collects the light intensity distribution under the wavelength, and then uses the angular spectrum propagation formula to reversely propagate the collected light intensity map (the square root of the light intensity map value, i.e., the complex amplitude), and generates light field distributions of different defocus planes within the estimated defocus distance range. Then, the light field complex amplitude modulus values ​​of different defocus planes are first subtracted and then squared from the square root of the collected light intensity distribution, and then all pixel values ​​in each matrix obtained by the square are summed, and finally each defocus plane corresponds to a sum value, and the corresponding values ​​on all defocus planes together form a one-dimensional matrix (i.e., a discrete one-dimensional function). The one-dimensional matrix is ​​second-order differentiated, and the curve distribution after the differentiation is modulo-valued, and the defocus distance corresponding to the maximum value in the curve distribution finally obtained is the final result.

[0025] Compared with the prior art, the present invention has the following significant advantages: 1. The present method can avoid the problem of selecting the maximum / minimum value required when using edge detection factors to judge the focal plane of different types of samples. 2. It can avoid the multi-frame data required by the data consistency method, thereby reducing the complexity of the system. 3. It has more advantages in terms of scope of application and calculation efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 A schematic diagram of the basic structure of a system to which the present invention is applicable;

[0027] Figure 2 is an overall flow chart of the method of the present invention;

[0028] Figure 3 The distribution of intensity / phase objects at the focusing / defocusing distance, where (a) is the light intensity distribution of an intensity object, (b) is the image distribution of the intensity object at Z2=800μm when the wavelength is λ=516μm, (c) is the phase distribution of a phase object, and (d) is the image distribution of the intensity object at Z2=800μm when the wavelength is λ=516μm;

[0029] Figure 4 =∑∑D n The normalized curve relationship between the sequence number n, where (a) is Figure 3 The intensity object shown in (a) corresponds to ∑∑Dn The normalized curve relationship between and sequence number n, (b) is Figure 3 The phase object shown in (c) corresponds to ∑∑D n The normalized curve relationship with the sequence number n;

[0030] Figure 5 =∑∑D' n-1 The normalized curve relationship between the sequence number n, where (a) is Figure 3 The intensity object shown in (a) corresponds to ∑∑D' n-1 The normalized curve relationship between and sequence number n, (b) is Figure 3 The phase object shown in (c) corresponds to ∑∑D' n-1 The normalized curve relationship with the sequence number n;

[0031] Figure 6 =|∑∑D” n-2 | and the curve relationship between the sequence number n, where (a) is Figure 3 The intensity object shown in (a) corresponds to |∑∑D” n-2 The normalized curve relationship between | and the sequence number n, (b) is Figure 3 The phase object shown in (c) corresponds to |∑∑D” n-2 |The normalized curve relationship between | and the sequence number n. DETAILED DESCRIPTION

[0032] The present invention will be further explained below in conjunction with the accompanying drawings.

[0033] A single-frame self-focusing method for a lensless microscopic imaging system is applicable to a lensless microscopic imaging system, the basic structure of which consists of three parts: a partially coherent or coherent light source (monochrome), a sample, and an image sensor. According to the present invention, a monochromatic light source is used as the illumination light source of the lensless microscope, which is directly placed above the sample, and the light emission center position of the light source is located on the optical axis of the entire imaging system.

[0034] like Figure 1 As shown, the distance Z1 between the monochromatic light source of the lensless microscopic imaging system and the upper surface of the sample is generally between 5 and 20 cm, and the distance Z2 between the image sensor of the camera and the sample is generally between 1 μm and 2 mm. If the spatial coherence of the monochromatic light source used is relatively poor, that is, the luminous area of ​​the light source is relatively large, the value of Z1 / Z2 can be increased to improve the spatial coherence of the light source. On this basis, the determination of the defocus distance in the entire imaging reconstruction process is the problem to be solved by the present invention.

[0035] The method of the present invention can quickly and accurately determine the focus plane of an object by using only single frame data without using edge detection factors. Figure 2As shown, a single-frame self-focusing method of a lensless microscopic imaging system based on non-similarity of the present invention comprises the following steps:

[0036] Step 1: Irradiate the sample with a light source of a single wavelength to obtain a single-frame diffraction light intensity distribution of the sample at that wavelength.

[0037] Specifically, firstly, the wavelength of the light source is measured using a spectrometer to obtain a wavelength λ.

[0038] Secondly, obtain the single-frame diffraction light intensity distribution of the sample under the wavelength. For non-contact lensless imaging, the entire imaging process can be regarded as the interference complex amplitude generated by the light scattered by the sample to be measured and the light not modulated by the sample. The light field carrying the object information will be captured by the sensor after propagating a certain distance. When the wavelength generated by the light source is λ, the diffraction light intensity distribution I of the sample can be obtained, I = I (x h ,y h ), (x h ,y h ) are the coordinates of the discretized image collected by the image sensor, and are all positive integers. Figure 3 As shown in the figure, when the sample to be measured is an intensity object, the intensity distribution of the object on the focusing plane is as follows: Figure 3 As shown in (a), when the light source with a wavelength of λ is illuminated and the defocus distance is Z2, the collected light intensity distribution I is as follows: Figure 3 When the sample to be measured is a phase object, its phase distribution is as follows: Figure 3 As shown in (c), when the light source with a wavelength of λ is illuminated and the defocus distance is Z2, the collected light intensity distribution I is as follows: Figure 3 Here, the wavelength λ is 516 μm and the defocus distance is Z2 = 800 μm.

[0039] Step 2: Use the angular spectrum propagation formula to reverse the light intensity and generate the light field distribution of different defocus planes.

[0040] Considering that the data collected by the image sensor is discretized, the present invention uses angular spectrum propagation as the basic model of back propagation to obtain light field information on planes with different defocus distances. This model can keep the image size unchanged during digital processing. The specific process is as follows: First, in the air medium, for the light of wavelength λ in the lensless imaging system, the frequency domain effect transfer function of its free propagation is:

[0041]

[0042] Among them, (f x ,f y ) is the spatial coordinate (x h ,y h ) corresponds to the frequency domain coordinates.

[0043] Secondly, if Figure 3 As shown in the figure, the collected image distribution I carries the object information and is captured by the image sensor after propagating the distance Z2. Therefore, the entire reconstruction process can be recorded as:

[0044]

[0045] in, represents Fourier transform.

[0046] Next, estimate the defocus distance range of the imaging system Z2 = z1 ~ z m , traverse the defocus distance within this range with step as the step length. This is mainly because, in the actual process, due to the presence of surface glass on the surface of the image sensor, the actual distance between the object and the sensor is difficult to measure directly. Therefore, in the present invention, Z2 needs to estimate a rough range based on the actual system construction and empirical values, which can generally be 1μm to 2mm; step can be selected according to actual needs, and the generally selected range is 0.1μm to 5μm.

[0047] In this embodiment, z1 = 500 μm, z m =1000μm, step=1μm. Corresponding to the light intensity distribution I, the light field distribution U at n defocus positions can be obtained 1 ~U n , n = floor[(z m -z1) / step]+1, floor means round down:

[0048]

[0049] Step 3: Subtract the generated light field complex amplitude modulus on different defocus planes from the square root of the collected light intensity distribution.

[0050] Considering that the light field U has been calculated in step 2 1 ~U n , then we can get the modulus value of |U 1 |~|U n |; Then |U 1 |~|U n | and the square root of the collected light intensity distribution Subtract, in order: Finally, the calculated values ​​are squared and the results are recorded as D 1 ~D n ,in,

[0051] Step 4: For each matrix obtained by subtracting in step 3, sum the elements and perform two derivatives. The defocus distance corresponding to the maximum value in the curve distribution is the final result.

[0052] Specifically, for D obtained in step 3 1 ~D n Each element in the matrix is ​​summed, denoted as ∑∑D 1 ~∑∑D n :

[0053]

[0054] Wherein, M and N are the horizontal and vertical pixel numbers of the discretized image collected by the image sensor, respectively, and are both positive integers.

[0055] ∑∑D 1 ~∑∑D n is a set of discrete data related to n, Figure 4 (a) and Figure 4 (b) represents an intensity distribution such as Figure 3 (a) and a phase distribution such as Figure 3 (c) corresponds to ∑∑D 1 ~∑∑D n By taking the first derivative of this set of data, we can obtain a corresponding set of derivatives, denoted as ∑∑D' 1 ~∑∑D' n-1 ,like Figure 5 shown. Figure 5 (a) is an intensity distribution such as Figure 3 (a) corresponds to the normalized ∑∑D' n-1 The curvilinear relationship with the sequence number n; Figure 5 (b) is a phase distribution such as Figure 3 (c) corresponds to the normalized ∑∑D' n-1 The curve relationship between the sequence number n.

[0056] Next, for ∑∑D' 1 ~∑∑D' n-1 This set of data is derivatized again to obtain ∑∑D” 1 ~∑∑D” n-2 Such a set of data. 1 ~∑∑D” n-2 This set of data is modulo, recorded as |∑∑D" 1 |~|∑∑D” n-2 |, the curve corresponding to this set of data is as follows Figure 6 shown. Figure 6 (a) is an intensity distribution such as Figure 3(a) corresponds to the normalized |∑∑D” n-2 |The curve relationship between the sequence number n; Figure 6 (b) is a phase distribution such as Figure 3 (c) corresponds to the normalized |∑∑D” n-2 |The curve relationship between the sequence number n.

[0057] Finally, select |∑∑D" 1 |~|∑∑D” n-2 |The number corresponding to the maximum value in, such as when the number n = k, |∑∑D" k | is the maximum value, then z1+(k+1)×step is the final defocus distance. This corresponds to an intensity distribution such as Figure 3 (a), combined with Figure 6 (a), corresponding to the sequence number n = 299, that is, k = 299, |∑∑D" k | is the maximum value, then z1+(k+1)×step=500+300×1=800μm is the final defocus distance. This corresponds to a phase distribution such as Figure 3 (c), combined with Figure 6 (b), corresponding to the sequence number n = 299, that is, k = 299, |∑∑D” k | is the maximum value, then z1+(k+1)×step=500+300×1=800μm is the final defocus distance.

[0058] The present invention can reduce the reliance on the clarity discrimination factor in the single-frame refocusing of conventional lensless microscopic imaging, avoid the influence of the conjugate image on the defocus distance search accuracy, and make full use of the dissimilarity between the diffraction pattern and the focusing pattern, thereby effectively improving the refocusing accuracy and speed.

[0059] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A single-frame self-focusing method for a lensless microscopic imaging system, characterized in that: include: Step 1: Use a single wavelength light source to illuminate the sample and collect the single frame diffraction light intensity distribution I of the sample; Step 2: Estimate the defocus range of the imaging system, and use the angular spectrum propagation formula to perform back propagation on the collected light intensity distribution I within the range to generate the light field distribution at different defocus distances; Step 3: The square root of the complex amplitude modulus of the light field on different defocus planes generated by back propagation and the collected light intensity distribution Subtract first and then square; Step 4: For each matrix obtained by squaring step 3, sum the elements and then perform two derivatives. The defocus distance corresponding to the maximum value in the obtained curve distribution is the final defocus distance.

2. The single-frame self-focusing method of a lensless microscopic imaging system according to claim 1, characterized in that: The step 2 comprises the following specific steps: The estimated defocus distance range is z1~z m , with step as the step length, z1~z m The defocus distance within the range is traversed, and the collected light intensity distribution I is back-propagated using the angular spectrum propagation formula to generate the light field distribution U at different distances 1 ~U n , n = floor[(z m -z1) / step]+1, floor means taking downward, and the step size step ranges from 0.1μm to 5μm.

3. The single-frame self-focusing method of a lensless microscopic imaging system according to claim 1 or 2, characterized in that: The step 3 comprises the following specific steps: Step 3.1: The light field distribution U obtained in step 2 1 ~U n Take the modulus value |U 1 |~|U n |; Step 3.2: Subtract the square root of the acquired light intensity distribution from the value after taking the modulus value, and record them in sequence as Step 3.3: Square the values ​​obtained in 3.2 and record them as D in order. 1 ~D n .

4. The single-frame self-focusing method of a lensless microscopic imaging system according to claim 3, characterized in that: The step 4 comprises the following specific steps: Step 4.1: For D obtained in step 3 1 ~D n Each element in the matrix is ​​summed up, and the result is recorded as ∑∑D 1 ~∑∑D n ; Step 4.2: For ∑∑D 1 ~∑∑D n First, perform a derivation, and the derivation results are recorded as ∑∑D' 1 ~∑∑D' n-1 ; Step 4.3: For ∑∑D' 1 ~∑∑D' n-1 Derivation is performed again, and the derivative results are recorded as ∑∑D" 1 ~∑∑D” n-2 ; Step 4.4: ∑∑D” 1 ~∑∑D” n-2 Take the modulus, and record it in sequence as |∑∑D" 1 |~|∑∑D” n-2 |; Step 4.5: |∑∑D” 1 |~|∑∑D” n-2 |The serial number corresponding to the maximum value in is recorded as k, then z1+(k+1)×step is the final defocus distance.

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