CN111062889A - Light intensity correction method for Fourier laminated microscopic imaging technology - Google Patents
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Abstract
A light intensity correction method for a Fourier laminated microscopic imaging technology can achieve the effect of correcting image brightness, and further achieve the purpose of correcting light intensity inconsistency errors. The method comprises the following steps: (1) collecting an original image to form an image data set; (2) setting an image intensity multiple change interval [ A, B ], setting an initial value of an intensity correction coefficient corresponding to the acquired original image as 1, transforming the numerical value of the intensity correction coefficient, and adjusting the intensity of the image; sequentially changing the initial image intensity correction coefficient value according to the value in the interval [ A, B ] and t, multiplying each measured image by different intensity correction coefficients, and calculating a primary evaluation function after each change; through a plurality of iterations, the most appropriate brightness multiple value is found; (3) adjusting each low-resolution image according to the most appropriate brightness multiple value to finish the brightness correction of the image; (4) and carrying out high-resolution reconstruction on the corrected image to obtain a reconstructed image.
Description
Technical Field
The invention relates to the technical field of microscopic imaging, in particular to a light intensity correction method for a Fourier laminated microscopic imaging technology.
Background
The microscopic imaging technology is a technology for observing the morphological structure and the characteristics of a tiny object by using an optical system or electronic equipment, and the Fourier laminated microscopic imaging technology (FPM) can break through the limitation of the numerical aperture of an objective lens of an imaging system in a calculation and reconstruction mode, simultaneously realizes large-field-of-view and super-resolution imaging, and is widely applied to the aspects of cytology, biology, medicine and the like.
The current research shows that the FPM adopts the illuminating light with consistent illuminating brightness to provide plane waves at different angles and respectively illuminates the sample, the light intensity of the illuminating light at each angle reaching the sample is consistent under an ideal condition, and the original frequency proportion relation of each part of the sample is kept among the recovered sub-frequency components.
However, there are a number of illumination non-uniformity types in current systems, and error sources include: the current flowing through the LED lamp is unstable, the resistance of different LED lamp beads is different, and the heat dissipation function of the LED lamp is reduced, the brightness is reduced and the like as the service life is prolonged. These all result in different intensities of incident light at different angles reaching the sample surface, resulting in poor quality of reconstructed high resolution images.
At present, the method for solving the problems is mainly to compensate from an algorithm, and generally achieves the purpose of error correction by reducing the amplitude difference of a measured image and a target complex amplitude image or the amplitude difference of the measured image and the target complex amplitude image, but when the acquired original image has a large illumination non-uniform error or a sub-spectrum has a non-linear error during reconstruction, many correction methods cannot achieve a good correction effect.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides a light intensity correction method for a Fourier laminated microscopy imaging technology, which can realize the effect of correcting the brightness of an image and further achieve the aim of correcting the light intensity inconsistency errors.
The technical scheme of the invention is as follows: the light intensity correction method for the Fourier laminated microscopic imaging technology comprises the following steps:
(1) collecting an original image to form an image data set;
(2) setting an image intensity multiple change interval [ A, B ], setting an initial value of an intensity correction coefficient corresponding to the acquired original image as 1, and changing the numerical value of the intensity correction coefficient on the basis to adjust the intensity of the image; the adjustment method comprises the steps that the initial image intensity correction coefficient value is sequentially changed according to values in intervals [ A and B ] and a certain step length t, each measured image is multiplied by different intensity correction coefficients, and an evaluation function is calculated after each change; finding the most appropriate brightness multiple value through a process of iteratively finding the optimal evaluation function and the optimal brightness multiple for a plurality of times;
(3) adjusting each low-resolution image according to the most appropriate brightness multiple value to finish the brightness correction of the image;
(4) and carrying out high-resolution reconstruction on the corrected image to obtain a reconstructed image.
The invention achieves the aim of correcting the light intensity by setting a series of intensity correction coefficients and continuously adjusting the intensity value of each image, and the influence of uneven illumination intensity on a reconstruction result can be weakened by reconstructing the corrected image, so that the effect of correcting the image brightness can be realized, and the aim of correcting the inconsistent error of the light intensity can be further achieved.
Drawings
Fig. 1 is an acquired original image.
FIG. 2 is a reconstructed image without illumination non-uniformity error correction.
Fig. 3 is a reconstructed image with illumination non-uniformity error correction added.
FIG. 4 is a flow chart of an optical intensity correction method for Fourier stacked microscopy imaging techniques according to the present invention.
Detailed Description
In the FPM system, the reconstruction quality is affected by the illumination intensity, when the illumination intensity reaching the sample surface is not uniform, an illumination non-uniformity error is generated, and the intensity of each original image needs to be corrected, so that the image intensity is closer to the true intensity value. The invention achieves the aim of light intensity correction by setting a series of intensity correction coefficients and continuously adjusting the intensity value of each image, and can weaken the influence of uneven illumination intensity on the reconstruction result by reconstructing the corrected image.
The traditional FPM reconstruction method is to directly perform multiple GS reconstruction on an uncorrected image. Firstly, a high-resolution initial estimation image is constructed, Fourier transform is carried out on the high-resolution initial estimation image to obtain an initial estimation frequency spectrum, a subregion frequency spectrogram is searched on the initial estimation frequency spectrum, inverse Fourier transform is carried out on the subregion frequency spectrogram to obtain a target complex amplitude image, then the amplitude part of the target complex amplitude image is directly replaced by the collected original image, the phase part is kept unchanged, Fourier transform is carried out on the obtained new target complex amplitude image, and the frequency spectrogram of the corresponding position on the initial estimation frequency spectrogram is updated. And then replacing the next sub-spectrum until the replacement of all sub-spectrums is completed, and thus, one iteration is completed.
As shown in fig. 4, the method for correcting light intensity of fourier stacked microscopy imaging technology of the present invention comprises the following steps:
(1) collecting an original image to form an image data set;
(2) setting an image intensity multiple change interval [ A, B ], setting an initial value of an intensity correction coefficient corresponding to the acquired original image as 1, and changing the numerical value of the intensity correction coefficient on the basis to adjust the intensity of the image; the adjustment method comprises the steps that the initial image intensity correction coefficient value is sequentially changed according to values in intervals [ A and B ] and a certain step length t, each measured image is multiplied by different intensity correction coefficients, and an evaluation function is calculated after each change; finding the most appropriate brightness multiple value through a process of iteratively finding the optimal evaluation function and the optimal brightness multiple for a plurality of times;
(3) adjusting each low-resolution image according to the most appropriate brightness multiple value to finish the brightness correction of the image;
(4) and (4) carrying out high-resolution reconstruction on the corrected image, such as GS iterative reconstruction, so as to obtain a reconstructed image.
The invention achieves the aim of correcting the light intensity by setting a series of intensity correction coefficients and continuously adjusting the intensity value of each image, and the influence of uneven illumination intensity on a reconstruction result can be weakened by reconstructing the corrected image, so that the effect of correcting the image brightness can be realized, and the aim of correcting the inconsistent error of the light intensity can be further achieved.
Preferably, the evaluation function in step (2) is the square of the difference between the intensity values of the target complex amplitude image and the measured image, and the calculation method is as follows: firstly, carrying out primary reconstruction by using a traditional GS reconstruction method to obtain a high-resolution image as an initial estimation value, carrying out Fourier transform on the high-resolution image to obtain an initial estimation frequency spectrum, searching a sub-region spectrogram on the initial estimation frequency spectrum, carrying out inverse Fourier transform on the sub-region spectrogram to obtain a target complex amplitude image I1And the intensity value is recorded as Er1The corresponding measured image is marked as I2And the intensity value is recorded as Er2The initial evaluation function value is recorded as Er ═ Er (Er)1-Er2)2And recording Er as an optimal evaluation function Erbest(ii) a When the image is adjusted by the brightness correction coefficient, a new measurement image I is obtained2newThe intensity value is recorded as Er2newUpdating the target complex amplitude image by using the new measurement image to obtain a new target complex amplitude image I1newAnd the intensity value is recorded as Er1newCalculating new evaluation function value Ernew＝(Er1new-Er2new)2When Ernew＜ErbestThen ErnewIs recorded as ErbestThe corresponding intensity correction coefficient is the optimal correction coefficient when Ernew＞ErbestIn time, ErbestAnd is not changed.
Preferably, in the step (2), through a process of searching the optimal evaluation function and the optimal brightness multiple through multiple iterations, the most appropriate brightness multiple value of each image is found.
Preferably, in the step (4), the image is reconstructed, and the FPM algorithm reconstruction is performed on the acquired multiple low-resolution images.
Preferably, in the step (4), the image reconstruction is performed by a GS phase recovery algorithm in a phase recovery algorithm to perform super-resolution reconstruction.
Taking the GS phase recovery algorithm as an example (but not limited to adopting this way), the step (4) includes the following sub-steps:
(4.1) carrying out interpolation processing on the image shot by the central LED lamp on the LED array to be used as an initial estimation value of a space domain;
(4.2) carrying out Fourier transform on the interpolated image to obtain a frequency domain initial estimation value;
(4.3) selecting a sub-region from the obtained spectrogram to perform inverse Fourier transform to obtain a target complex amplitude image, wherein the target complex amplitude image comprises amplitude information and phase information;
(4.4) keeping the phase information of the target complex amplitude image unchanged, and replacing the amplitude information of the actual image shot by the LED lamp at the corresponding position on the LED array with the amplitude information of the actual image to obtain an updated target complex amplitude image;
(4.5) carrying out Fourier transform on the updated target complex amplitude image to obtain an updated spectrogram, and replacing a corresponding sub-spectrum region of the initial spectrogram by the updated spectrogram;
(4.6) repeating the steps (4.3) - (4.5) to complete the updating of all sub-spectrums;
and (4.7) repeating the steps (4.3) to (4.6) to converge the result, obtaining a high-resolution frequency spectrum image with enhanced image high-frequency information, and then performing inverse Fourier transform to obtain a high-resolution image in a space domain.
Preferably, the method further comprises a step (5), and the result is verified, after comparing the original low-resolution-ratio image, the reconstructed image without illumination non-uniformity error correction and the reconstructed image with illumination non-uniformity error correction, it is found that the quality of the reconstructed image is deteriorated due to illumination non-uniformity errors, and after correction, the resolution is improved, and the background of the image is more uniform.
For better illustrating the objects and advantages of the present invention, the following detailed description of the present invention is provided in conjunction with the accompanying drawings and examples.
Example 1:
because the current flowing through the LED lamp is unstable, the resistance of different LED lamp beads is different, the heat dissipation function of part of LED lamps is reduced along with the prolonging of the service time, the errors of brightness attenuation and the like can cause the errors of inconsistent light intensity reaching the surface of a sample, and the errors can be effectively corrected by adopting a light intensity correction method which can be used for a Fourier laminated micro-imaging technology. The light source used in this embodiment is an LED array. The size of an LED array participating in illumination is 31 multiplied by 31, the distance between LED lamps is 2.5mm, the distance from the LED array to a sample is 96mm, the wavelength of illumination light is 630nm, the numerical aperture of an objective lens is 0.09, an image acquisition device is a CCD camera, and the size of an imaging pixel is 2.45 mu m. LED lamps at different positions on an LED array collect a sub-aperture image, a certain degree of brightness error exists between each sub-aperture image, and when the collected original image is directly used for reconstruction, the quality of the reconstructed image is reduced. An error correction method is required to correct this error.
The image enhancement method for the Fourier stack microscopy imaging technology disclosed by the embodiment comprises the following specific steps:
the method comprises the following steps: collecting 961 original low resolution images of the image data set
Step two: and performing primary original GS iterative reconstruction on 961 original images to obtain an initial estimation image, performing Fourier transform to obtain a high-resolution spectrogram, wherein the high-resolution spectrogram is used as an initial estimation frequency spectrum and is used for correcting the illumination unevenness error.
Step three: sorting original images, performing brightness correction from a first image, selecting a corresponding sub-spectrum image from a high-resolution spectrogram, performing inverse Fourier transform to obtain a target complex amplitude image I1And the intensity value is recorded as Er1The first image is marked as I2And the intensity value is recorded as Er2The initial evaluation function value is recorded as Er ═ Er (Er)1-Er2)2And recording Er as an optimal evaluation function Erbest。
Step four: setting a variation interval [0.4, 1.2 ] of brightness correction coefficient]Step size is 0.01, brightness correction coefficient C is changed from 0.4, each time the brightness correction coefficient C is increased by 0.01 until 1.2 is finished, original low-resolution image is changed according to brightness correction coefficient, and new measurement image I is obtained after each change2newThe intensity value is recorded as Er2newUpdating the target complex amplitude image by using the new measurement image to obtain a new target complex amplitude image I1newAnd the intensity value is recorded as Er1newCalculating new evaluation function value Ernew＝(Er1new-Er2new)2When Ernew＜ErbestThen ErnewIs recorded as ErbestThe corresponding intensity correction coefficient is the optimal correction coefficient when Ernew＞ErbestIn time, ErbestAnd is not changed.
Step five: and finding the most suitable brightness multiple value of each image through the process of searching the optimal evaluation function and the optimal brightness multiple through five iterations. And adjusting each low-resolution image according to the most appropriate brightness multiple value to finish the brightness correction of the image.
Step six: image reconstruction, namely performing FPM algorithm reconstruction on a plurality of collected low-resolution images, selecting a classical GS phase recovery algorithm for super-resolution reconstruction, and comprising the following steps:
[1] performing interpolation processing on an image shot by a central LED lamp on the LED array to serve as an initial estimation value of a space domain;
[2] carrying out Fourier transform on the interpolated image to obtain a frequency domain initial estimation value;
[3] selecting a sub-region from the obtained spectrogram to perform Fourier inverse transformation to obtain a target complex amplitude image, wherein the target complex amplitude image comprises amplitude information and phase information;
[4] keeping the phase information of the target complex amplitude image unchanged, and replacing the amplitude information of the actual image shot by the LED lamp at the corresponding position on the LED array to obtain an updated target complex amplitude image;
[5] performing Fourier transform on the updated target complex amplitude image to obtain an updated spectrogram, and replacing a corresponding sub-spectrum region of the initial spectrogram by the updated spectrogram;
[6] repeating the steps from [3] to [5] to complete the updating of all sub-spectrums;
[7] and (4) repeating the steps (3) to (6) to converge the result, obtaining a high-resolution frequency spectrum image with enhanced image high-frequency information, and then performing inverse Fourier transform to obtain a high-resolution image in a space domain.
Step seven: the result is tested, the original low-resolution image is shown in fig. 1, the reconstructed image without illumination unevenness error correction is shown in fig. 2, and the reconstructed image with illumination unevenness error correction is shown in fig. 3; through comparison, the quality of a reconstructed image is deteriorated due to the uneven illumination error, the resolution is improved after the image is corrected, and meanwhile, the image background is more uniform.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention in any way, and all simple modifications, equivalent variations and modifications made to the above embodiment according to the technical spirit of the present invention still belong to the protection scope of the technical solution of the present invention.
Claims (7)
1. A light intensity correction method for Fourier laminated microscopic imaging technology is characterized in that: which comprises the following steps:
(1) collecting an original image to form an image data set;
(2) setting an image intensity multiple change interval [ A, B ], setting an initial value of an intensity correction coefficient corresponding to the acquired original image as 1, and changing the numerical value of the intensity correction coefficient on the basis to adjust the intensity of the image; the adjustment method comprises the steps that the initial image intensity correction coefficient value is sequentially changed according to values in intervals [ A and B ] and a certain step length t, each measured image is multiplied by different intensity correction coefficients, and an evaluation function is calculated after each change; finding the most appropriate brightness multiple value through a process of iteratively finding the optimal evaluation function and the optimal brightness multiple for a plurality of times;
(3) adjusting each low-resolution image according to the most appropriate brightness multiple value to finish the brightness correction of the image;
(4) and carrying out high-resolution reconstruction on the corrected image to obtain a reconstructed image.
2. The method of claim 1, wherein the intensity of the light is corrected by a Fourier transform tomographyCharacterized in that: the evaluation function in the step (2) is the square of the difference value between the intensity values of the target complex amplitude image and the measured image, and the calculation method is as follows: firstly, carrying out primary reconstruction by using a traditional GS reconstruction method to obtain a high-resolution image as an initial estimation value, carrying out Fourier transform on the high-resolution image to obtain an initial estimation frequency spectrum, searching a sub-region spectrogram on the initial estimation frequency spectrum, carrying out inverse Fourier transform on the sub-region spectrogram to obtain a target complex amplitude image I1And the intensity value is recorded as Er1The corresponding measured image is marked as I2And the intensity value is recorded as Er2The initial evaluation function value is recorded as Er ═ Er (Er)1-Er2)2And recording Er as an optimal evaluation function Erbest(ii) a When the image is adjusted by the brightness correction coefficient, a new measurement image I is obtained2newThe intensity value is recorded as Er2newUpdating the target complex amplitude image by using the new measurement image to obtain a new target complex amplitude image I1newAnd the intensity value is recorded as Er1newCalculating new evaluation function value Ernew＝(Er1new-Er2new)2When Ernew＜ErbestThen ErnewIs recorded as ErbestThe corresponding intensity correction coefficient is the optimal correction coefficient when Ernew＞ErbestIn time, ErbestAnd is not changed.
3. The light intensity correction method for fourier stacked microscopy imaging technique as claimed in claim 2, characterized in that: in the step (2), the most suitable brightness multiple value of each image is found through a process of iteratively searching the optimal evaluation function and the optimal brightness multiple for multiple times.
4. The light intensity correction method for fourier stacked microscopy imaging technique as claimed in claim 3, characterized in that: and (4) reconstructing the image, namely performing FPM algorithm reconstruction on the collected low-resolution images.
5. The light intensity correction method for fourier stacked microscopy imaging technique as claimed in claim 4, wherein: in the step (4), the image reconstruction is performed with super-resolution reconstruction by a GS phase recovery algorithm in the phase recovery algorithm.
6. The light intensity correction method for fourier stacked microscopy imaging technique as claimed in claim 5, characterized in that: the step (4) of performing super-resolution reconstruction by using a GS phase recovery algorithm comprises the following sub-steps:
(4.1) carrying out interpolation processing on the image shot by the central LED lamp on the LED array to be used as an initial estimation value of a space domain;
(4.2) carrying out Fourier transform on the interpolated image to obtain a frequency domain initial estimation value;
(4.3) selecting a sub-region from the obtained spectrogram to perform inverse Fourier transform to obtain a target complex amplitude image, wherein the target complex amplitude image comprises amplitude information and phase information;
(4.4) keeping the phase information of the target complex amplitude image unchanged, and replacing the amplitude information of the actual image shot by the LED lamp at the corresponding position on the LED array with the amplitude information of the actual image to obtain an updated target complex amplitude image;
(4.5) carrying out Fourier transform on the updated target complex amplitude image to obtain an updated spectrogram, and replacing a corresponding sub-spectrum region of the initial spectrogram by the updated spectrogram;
(4.6) repeating the steps (4.3) - (4.5) to complete the updating of all sub-spectrums;
and (4.7) repeating the steps (4.3) to (4.6) to converge the result, obtaining a high-resolution frequency spectrum image with enhanced image high-frequency information, and then performing inverse Fourier transform to obtain a high-resolution image in a space domain.
7. The light intensity correction method for fourier stacked microscopy imaging technique as claimed in claim 6, wherein: and (5) result testing, namely comparing the original low-resolution-ratio image, the reconstructed image which is not subjected to illumination non-uniform error correction and the reconstructed image which is subjected to illumination non-uniform error correction, finding that the quality of the reconstructed image is deteriorated due to illumination non-uniform errors, and improving the resolution and the background of the image more uniformly after the correction.
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| CN113724201B (en) * | 2021-08-03 | 2023-10-13 | 哈尔滨工程大学 | Image sensor correction effect quantitative evaluation method based on two-dimensional Fourier transform |
| CN113724202B (en) * | 2021-08-03 | 2023-10-13 | 哈尔滨工程大学 | Image sensor correction effect quantitative evaluation method based on one-dimensional Fourier transform |
| CN113671682A (en) * | 2021-08-23 | 2021-11-19 | 北京理工大学重庆创新中心 | Frequency domain light source position accurate correction method based on Fourier laminated microscopic imaging |
| CN113671682B (en) * | 2021-08-23 | 2023-05-23 | 北京理工大学重庆创新中心 | Frequency domain light source position accurate correction method based on Fourier laminated microscopic imaging |
| CN114998161A (en) * | 2022-06-02 | 2022-09-02 | 中国科学院西安光学精密机械研究所 | Fourier stack microscopy high-precision image reconstruction method based on perfect Fourier transform |
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