Method and device for evaluating base fluorescence image definition, medium and apparatus

Abstract

The application discloses a base fluorescence image definition evaluation method and device, terminal equipment and medium, and relates to the technical field of image processing. The method comprises the following steps: removing noise interference contained in each of a plurality of base fluorescence images to generate smooth base fluorescence images; determining respective horizontal difference values and vertical difference values corresponding to each of the plurality of smooth base fluorescence images, and determining total difference values according to the horizontal difference values and the vertical difference values; determining respective brightness values corresponding to each of fluorescence clusters contained in the plurality of smooth base fluorescence images, and determining brightness median values based on the brightness values; determining real-time sharpness values corresponding to each of the plurality of smooth base fluorescence images based on the total difference values and the brightness median values, constructing a target sharpness curve based on the real-time sharpness values and image numbers corresponding to each of the plurality of smooth base fluorescence images, and determining a target base fluorescence image with the highest definition in the plurality of smooth base fluorescence images according to the target sharpness curve.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of image processing, in particular to a base fluorescence image definition evaluation method, a terminal device, a computer readable storage medium and an apparatus. BACKGROUND

[0002] Since different bases in a gene sequence will produce different brightness fluorescence clusters, the technical personnel mainly complete the detection of the gene sequence by obtaining the base fluorescence image containing the fluorescence cluster. In the process of obtaining the base fluorescence image, the technical personnel mainly collects the base fluorescence image through the camera, and then evaluates the definition of the collected base fluorescence image, so as to save the image when it is determined that the collected base fluorescence image is in the clearest state.

[0003] The current method for evaluating the definition of the picture mainly adopts the edge detection of the picture, the infrared induction, the signal-to-noise ratio of the image and the corner point detection method. However, in the conventional case, although the above detection methods can determine the definition of the base fluorescence image, when the base fluorescence image appears a large area of bright spot, the light points are too sparse, the brightness is extremely low or the noise is too large and other extreme conditions, the definition of the base fluorescence image cannot be accurately evaluated through the above detection methods. SUMMARY

[0004] The main purpose of the present application is to provide a base fluorescence image definition evaluation method, a terminal device, a computer readable storage medium and an apparatus, which can more accurately evaluate the definition of the base fluorescence image.

[0005] To achieve the above purpose, the present application provides a base fluorescence image definition evaluation method, which comprises the following steps:

[0006] Removing the noise interference contained in each of the plurality of base fluorescence images to generate a plurality of smooth base fluorescence images;

[0007] Determining the respective horizontal difference value and vertical difference value corresponding to each of the plurality of smooth base fluorescence images, and determining the total difference value corresponding to each of the plurality of smooth base fluorescence images according to the respective horizontal difference value and vertical difference value;

[0008] Determining the respective brightness value corresponding to each of the fluorescence clusters contained in the plurality of smooth base fluorescence images, and determining the brightness median value corresponding to each of the plurality of smooth base fluorescence images based on the respective brightness value;

[0009] determine a real-time sharpness value corresponding to each of the plurality of smoothed base fluorescence images based on each of the difference total value and each of the luminance median value, and construct a target sharpness curve based on each of the real-time sharpness value and an image number corresponding to each of the plurality of smoothed base fluorescence images, and determine a target base fluorescence image with the highest definition from the plurality of smoothed base fluorescence images according to the target sharpness curve.

[0010] Further, the step of removing noise interference contained in each of the plurality of base fluorescence images to generate a smoothed base fluorescence image comprises:

[0011] determine a frequency domain corresponding to each of the plurality of base fluorescence images;

[0012] remove high-frequency components contained in each of the frequency domain to generate a smoothed base fluorescence image, preferably remove high-frequency components contained in each of the frequency domain to generate a smoothed base fluorescence image by a preset Fourier transform algorithm.

[0013] Further, the step of determining each horizontal difference value and each vertical difference value corresponding to each of the plurality of smoothed base fluorescence images comprises:

[0014] determine a pixel coordinate of each pixel point contained in each of the plurality of smoothed base fluorescence images;

[0015] determine a horizontal difference value corresponding to each of the pixel points based on each of the pixel coordinates, wherein the horizontal difference value is a difference value between the pixel point and other pixel points adjacent to the pixel point in a horizontal direction;

[0016] determine a vertical difference value corresponding to each of the pixel points based on each of the pixel coordinates, wherein the vertical difference value is a difference value between the pixel point and other pixel points adjacent to the pixel point in a vertical direction.

[0017] Further, the step of determining a luminance median value corresponding to each of the plurality of smoothed base fluorescence images based on each of the luminance value comprises:

[0018] sort each of the luminance value corresponding to each of the plurality of smoothed base fluorescence images to obtain a sorting result corresponding to each of the plurality of smoothed base fluorescence images;

[0019] determine a luminance median value corresponding to each of the plurality of smoothed base fluorescence images based on each of the sorting result.

[0020] Further, the step of constructing a target sharpness curve based on each of the real-time sharpness value and an image number corresponding to each of the plurality of smoothed base fluorescence images comprises:

[0021] determine an image number corresponding to each of the plurality of smoothed base fluorescence images, and construct an initial sharpness curve according to each of the image numbers and each of the real-time sharpness values;

[0022] perform weighted average on each of the real-time sharpness values based on the preset weight value and the initial sharpness curve to generate a target sharpness curve.

[0023] Further, the step of performing weighted average on each of the real-time sharpness values based on the preset weight value and the initial sharpness curve to generate a target sharpness curve comprises:

[0024] obtain the preset weight value, and perform weighted average on the real-time sharpness value based on the weight value and other real-time sharpness values adjacent to the real-time sharpness value in the initial sharpness curve to obtain a target sharpness value;

[0025] generate a target sharpness curve according to each of the target sharpness values and each of the image numbers.

[0026] Further, the step of determining a target base fluorescence image with the highest clarity from the plurality of smoothed base fluorescence images according to the target sharpness curve comprises:

[0027] determine a maximum sharpness value in the target sharpness curve, and determine a target image number corresponding to the maximum sharpness value in the target sharpness curve;

[0028] determine a smoothed base fluorescence image corresponding to the target image number as a target base fluorescence image with the highest clarity from the plurality of smoothed base fluorescence images.

[0029] In addition, to achieve the above-mentioned purpose, the present application also provides an evaluation device for clarity of base fluorescence images, which comprises:

[0030] a noise removal module configured to remove noise interference contained in each of a plurality of base fluorescence images to generate a smoothed base fluorescence image;

[0031] a difference calculation module configured to determine each of horizontal difference values and each of vertical difference values corresponding to each of the plurality of smoothed base fluorescence images, and determine a total difference value corresponding to each of the plurality of smoothed base fluorescence images according to each of the horizontal difference values and each of the vertical difference values;

[0032] a brightness calculation module configured to determine a brightness value corresponding to each of fluorescence clusters contained in each of the plurality of smoothed base fluorescence images, and determine a brightness median value corresponding to each of the plurality of smoothed base fluorescence images based on each of the brightness values;

[0033] The image screening module is configured to determine a real-time sharpness value corresponding to each of the plurality of smoothed base fluorescence images based on each of the difference total values and each of the brightness medium values, construct a target sharpness curve based on each of the real-time sharpness values and an image number corresponding to each of the plurality of smoothed base fluorescence images, and determine a target base fluorescence image with the highest definition from the plurality of smoothed base fluorescence images according to the target sharpness curve.

[0034] In addition, the application also provides a terminal device to achieve the above-mentioned purposes, which comprises a memory, a processor, and a base fluorescence image definition evaluation program stored in the memory and executable on the processor. The base fluorescence image definition evaluation program, when executed by the processor, implements the steps of the base fluorescence image definition evaluation method as described above.

[0035] In addition, the application also provides a computer readable storage medium to achieve the above-mentioned purposes, which stores a base fluorescence image definition evaluation program. The base fluorescence image definition evaluation program, when executed by a processor, implements the steps of the base fluorescence image definition evaluation method as described above.

[0036] The base fluorescence image definition evaluation method, terminal device, computer readable storage medium and apparatus provided by the embodiments of the application generate smoothed base fluorescence images by removing noise interference contained in each of a plurality of base fluorescence images; determine each horizontal difference value and each vertical difference value corresponding to each of the plurality of smoothed base fluorescence images, and determine a difference total value corresponding to each of the plurality of smoothed base fluorescence images according to each of the horizontal difference values and each of the vertical difference values; determine a brightness value corresponding to each of the fluorescence clusters contained in each of the plurality of smoothed base fluorescence images, and determine a brightness medium value corresponding to each of the plurality of smoothed base fluorescence images based on each of the brightness values; determine a real-time sharpness value corresponding to each of the plurality of smoothed base fluorescence images based on each of the difference total values and each of the brightness medium values, construct a target sharpness curve based on each of the real-time sharpness values and an image number corresponding to each of the plurality of smoothed base fluorescence images, and determine a target base fluorescence image with the highest definition from the plurality of smoothed base fluorescence images according to the target sharpness curve.

[0037] In this embodiment, the terminal device first acquires a plurality of base fluorescence images captured by the camera during runtime, removes noise interference contained in each of the plurality of base fluorescence images to generate a plurality of smoothed base fluorescence images, then determines the pixel coordinates corresponding to each pixel point in each of the plurality of smoothed base fluorescence images, and determines the horizontal difference value and the vertical difference value corresponding to each of the plurality of smoothed base fluorescence images based on the pixel coordinates, further calculates the total difference value corresponding to each of the plurality of smoothed base fluorescence images according to the acquired horizontal difference value and vertical difference value, then cuts each of the plurality of smoothed base fluorescence images to determine the fluorescence clusters contained in each of the plurality of smoothed base fluorescence images and determine the brightness value corresponding to each of the fluorescence clusters, further determines the median brightness value corresponding to each of the plurality of smoothed base fluorescence images according to the brightness values, and finally determines the real-time sharpness value corresponding to each of the plurality of smoothed base fluorescence images based on the total difference value and the median brightness value corresponding to each of the plurality of smoothed base fluorescence images, and constructs a target sharpness curve based on the image number and the real-time sharpness value corresponding to each of the plurality of smoothed base fluorescence images, and further determines the target base fluorescence image with the highest clarity in the plurality of smoothed base fluorescence images based on the target sharpness curve.

[0038] Thus, the present application eliminates the noise interference contained in the base fluorescence image, and excludes the influence of ambient light on the base fluorescence image based on the real-time sharpness value of the base fluorescence image, constructs a target sharpness curve according to the real-time sharpness value and the image number corresponding to each of the plurality of base fluorescence images, thereby determining the target base fluorescence image with the highest clarity in the plurality of base fluorescence images based on the target sharpness curve, which achieves the technical effect of more accurately evaluating the clarity of the base fluorescence image. BRIEF DESCRIPTION OF DRAWINGS

[0039] Figure 1 is a structural schematic diagram of a terminal device of a hardware runtime environment involved in the embodiment scheme of the present application;

[0040] Figure 2 is a flowchart of the first embodiment of the base fluorescence image clarity evaluation method of the present application;

[0041] Figure 3 is a base fluorescence image schematic diagram involved in an embodiment of the base fluorescence image clarity evaluation method of the present application;

[0042] Figure 4 is a base fluorescence image denoising effect schematic diagram involved in an embodiment of the base fluorescence image clarity evaluation method of the present application;

[0043] Figure 5 is a comparison schematic diagram of the initial sharpness curve and the target sharpness curve involved in an embodiment of the base fluorescence image clarity evaluation method of the present application;

[0044] Figure 6 A schematic diagram of the fluorescence cluster segmentation effect involved in an embodiment of the base fluorescence image definition evaluation method of the present application is shown in the figure.

[0045] Figure 7 A schematic diagram of the functional modules involved in an embodiment of the base fluorescence image definition evaluation method of the present application is shown in the figure.

[0046] The implementation, functional features and advantages of the present application will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0047] It should be understood that the specific embodiments described herein are merely intended to explain the present application and are not intended to limit the present application.

[0048] Reference Figure 1 , Figure 1 A schematic diagram of the terminal device structure of the hardware running environment involved in the embodiment of the present application is shown in the figure.

[0049] It should be noted that, Figure 1 The schematic diagram of the structure of the hardware running environment of the terminal device can be shown in the figure. The terminal device of the embodiment of the present application can be the terminal device of the base fluorescence image definition evaluation method of the present application, and the terminal device can be a mobile terminal, a data storage control terminal, a PC or a portable computer, etc.

[0050] As Figure 1 shown, the terminal device can include a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to realize the connection and communication between the components. The user interface 1003 can include a display screen (Display), an input unit such as a keyboard (Keyboard), and an optional user interface 1003 can also include a standard wired interface, a wireless interface. The network interface 1004 can optionally include a standard wired interface, a wireless interface (such as a wireless fidelity (WIreless-FIdelity, WI-FI) interface). The memory 1005 can be a high-speed random access memory (RAM) memory, and can also be a stable non-volatile memory (Non-Volatile Memory, NVM), such as a magnetic disk memory. The memory 1005 can also be a storage device independent of the aforementioned processor 1001.

[0051] Those skilled in the art can understand, Figure 1The structure shown in the figure does not constitute a limitation on the terminal device, and can include more or fewer components, or combine certain components, or different component arrangements.

[0052] As shown in Figure 1 The memory 1005 as a storage medium can include an operating system, a data storage module, a network communication module, a user interface module, and a base fluorescence image sharpness evaluation program.

[0053] In the terminal device shown in Figure 1 In the terminal device shown in the figure, the network interface 1004 is mainly used for data communication with other devices; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the terminal device of the present application can be arranged in the terminal device, and the terminal device calls the base fluorescence image sharpness evaluation program stored in the memory 1005 through the processor 1001, and performs the following operations:

[0054] Remove the noise interference contained in each of the plurality of base fluorescence images to generate a smooth base fluorescence image;

[0055] Determine the respective horizontal difference value and the respective vertical difference value corresponding to each of the plurality of smooth base fluorescence images, and determine the difference total value corresponding to each of the plurality of smooth base fluorescence images according to the respective horizontal difference value and the respective vertical difference value;

[0056] Determine the respective brightness value corresponding to each of the fluorescence clusters contained in the plurality of smooth base fluorescence images, and determine the brightness median value corresponding to each of the plurality of smooth base fluorescence images based on the respective brightness value;

[0057] Determine the real-time sharpness value corresponding to each of the plurality of smooth base fluorescence images based on the respective difference total value and the respective brightness median value, and construct a target sharpness curve based on the respective real-time sharpness value and the image number corresponding to each of the plurality of smooth base fluorescence images, and determine the target base fluorescence image with the highest sharpness in the plurality of smooth base fluorescence images according to the target sharpness curve.

[0058] Further, the processor 1001 calls the base fluorescence image sharpness evaluation program stored in the memory 1005, and can also perform the following operations:

[0059] Determine the frequency domain corresponding to each of the plurality of base fluorescence images;

[0060] Remove the high frequency components contained in each of the frequency domains to generate a smooth base fluorescence image, preferably remove the high frequency components contained in each of the frequency domains to generate a smooth base fluorescence image by a preset Fourier transform algorithm.

[0061] Further, the processor 1001 invokes the evaluation program of base fluorescence image definition stored in the memory 1005, and can further perform the following operations:

[0062] Determine the pixel coordinates of each pixel point included in each of the plurality of smoothed base fluorescence images.

[0063] Determine the horizontal difference value corresponding to each of the pixel points based on each of the pixel coordinates, wherein the horizontal difference value is the difference value between the pixel point and other pixel points adjacent to it in the horizontal direction.

[0064] Determine the vertical difference value corresponding to each of the pixel points based on each of the pixel coordinates, wherein the vertical difference value is the difference value between the pixel point and other pixel points adjacent to it in the vertical direction.

[0065] Further, the processor 1001 invokes the evaluation program of base fluorescence image definition stored in the memory 1005, and can further perform the following operations:

[0066] Sort each of the brightness values corresponding to each of the plurality of smoothed base fluorescence images to obtain a sorting result corresponding to each of the plurality of smoothed base fluorescence images.

[0067] Determine the brightness median value corresponding to each of the plurality of smoothed base fluorescence images based on each of the sorting results.

[0068] Further, the processor 1001 invokes the evaluation program of base fluorescence image definition stored in the memory 1005, and can further perform the following operations:

[0069] Determine the image number corresponding to each of the plurality of smoothed base fluorescence images, and construct an initial sharpness curve according to each of the image numbers and each of the real-time sharpness values.

[0070] Based on the preset weight value and the initial sharpness curve, the real-time sharpness values are weighted and averaged to generate a target sharpness curve.

[0071] Further, the processor 1001 invokes the evaluation program of base fluorescence image definition stored in the memory 1005, and can further perform the following operations:

[0072] Obtain a preset weight value, and based on the weight value and other real-time sharpness values adjacent to the real-time sharpness value in the initial sharpness curve, the real-time sharpness value is weighted and averaged to obtain a target sharpness value;

[0073] Generate a target sharpness curve according to each of the target sharpness values and each of the image numbers.

[0074] Furthermore, the processor 1001 can call the base fluorescence image sharpness evaluation program stored in the memory 1005, and can also perform the following operations:

[0075] Determine the maximum sharpness value within the target sharpness curve, and determine the target image number corresponding to the maximum sharpness value within the target sharpness curve;

[0076] The smoothed base fluorescence image corresponding to the target image number is determined as the target base fluorescence image with the highest clarity among the multiple smoothed base fluorescence images.

[0077] Based on the above hardware structure, the overall concept of the method for evaluating the sharpness of base fluorescence images in this application is proposed.

[0078] Because the four bases A (adenine), C (cytosine), G (guanine), and T (thymine) within a gene sequence produce fluorescent clusters of varying brightness, current gene sequence detection processes have shifted from detecting individual bases to detecting these fluorescent clusters. This detection involves capturing fluorescent images of the bases using a camera. The clarity of these images is then evaluated, and the image at its clearest point is saved. Please refer to [link to relevant documentation]. Figure 3 , Figure 3 This is a schematic diagram of a base fluorescence image involved in an embodiment of the method for evaluating the sharpness of base fluorescence images according to this application, as shown below. Figure 3 As shown, base fluorescence images are mainly composed of two types of pixels: high-brightness fluorescent clusters and low-brightness background. The fluorescent clusters appear as small bright spots with radii ranging from a few pixels. Therefore, the evaluation of the sharpness of base fluorescence images is relatively unique. Current methods for evaluating the sharpness of base fluorescence images mainly include edge detection, infrared sensing, signal-to-noise ratio, and corner detection. However, when base fluorescence images exhibit special conditions such as excessively large bright spots, sparse light spots, extremely low brightness, or excessive noise, the aforementioned evaluation methods cannot accurately assess the sharpness of the base fluorescence images.

[0079] To address the aforementioned issues, this application eliminates noise interference within base fluorescence images and excludes the influence of ambient light on base fluorescence images based on their real-time sharpness values. A target sharpness curve is constructed based on the real-time sharpness values ​​and the corresponding image numbers of multiple base fluorescence images. This method, which determines the clearest target base fluorescence image among multiple base fluorescence images based on the target sharpness curve, achieves a more accurate assessment of the clarity of base fluorescence images.

[0080] Based on the overall concept of the base fluorescence image definition evaluation method of the present application, various embodiments of the base fluorescence image definition evaluation method of the present application are proposed. It should be noted that in various embodiments of the base fluorescence image definition evaluation method of the present application, the execution subject of the base fluorescence image definition evaluation method of the present application can be the terminal device described above.

[0081] Please refer to Figure 2 , Figure 2 The flowchart of the first embodiment of the base fluorescence image definition evaluation method of the present application is shown in the figure.

[0082] It should be understood that although the logical order is shown in the flowchart, in some cases, the steps shown or described herein can of course be performed in an order different from that shown.

[0083] In this embodiment, the base fluorescence image definition evaluation method of the present application can include the following steps:

[0084] Step S10: removing noise interference contained in each of the plurality of base fluorescence images to generate a smoothed base fluorescence image;

[0085] In this embodiment, when the terminal device is running, it first acquires a plurality of base fluorescence images collected by the camera device, and processes the plurality of base fluorescence images through a pre-set algorithm model, thereby removing noise interference contained in each of the plurality of base fluorescence images and generating a smoothed base fluorescence image.

[0086] For example, a user first collects a plurality of base fluorescence images through a camera device, and inputs the plurality of base fluorescence images into a terminal device, and the terminal device inputs the acquired plurality of base fluorescence images into an image processing module configured in the terminal device, and processes the plurality of base fluorescence images through a pre-set image processing model in the image processing module, thereby removing noise interference contained in each of the plurality of base fluorescence images and generating a smoothed base fluorescence image.

[0087] Further, in a feasible embodiment, the above step S10 can specifically include:

[0088] Step S101: determining the frequency domain corresponding to each of the plurality of base fluorescence images;

[0089] Step S102: removing high-frequency components contained in each of the frequency domains to generate a smoothed base fluorescence image, preferably removing high-frequency components contained in each of the frequency domains to generate a smoothed base fluorescence image through a pre-set Fourier transform algorithm;

[0090] For example, after the terminal device inputs multiple base fluorescence images into the image processing module, the image processing module determines the frequency domain corresponding to each of the multiple base fluorescence images, and calls the image processing model to remove the high-frequency components in each frequency domain according to the preset Fourier transform algorithm, thereby achieving the effect of removing noise interference contained in the base fluorescence image and generating the corresponding smooth base fluorescence image.

[0091] It should be noted that, in this embodiment, in addition to removing high-frequency components using the Fourier transform algorithm, the image processing model can also remove high-frequency components using other algorithms such as preset wavelet filtering or spatial domain filtering algorithms.

[0092] In addition, please refer to Figure 4 , Figure 4 This is a schematic diagram illustrating the denoising effect of a base fluorescence image according to an embodiment of the method for evaluating the sharpness of base fluorescence images in this application. Figure 4 As shown, the curves in the original image are the initial sharpness curve S0 and the real-time sharpness curve S1 corresponding to multiple base fluorescence images without noise reduction processing. The curves in the smoothed image are the initial sharpness curve S0 and the real-time sharpness curve S1 corresponding to multiple base fluorescence images after noise reduction processing. A comparison of the original and smoothed images clearly shows that in the smoothed image, the peak corresponding to the clearest base fluorescence image has a more pronounced prominence. It should be noted that... Figure 4 The horizontal axis of both the original image and the smoothed image represents the image number, and the vertical axis represents the sharpness value.

[0093] Step S20: Determine the horizontal difference value and the vertical difference value corresponding to each of the multiple smooth base fluorescence images, and determine the total difference value corresponding to each of the multiple smooth base fluorescence images based on the horizontal difference value and the vertical difference value.

[0094] In this embodiment, the terminal device determines the pixel coordinates of each pixel in each of the multiple smooth base fluorescence images. The terminal device then determines the horizontal difference value and the vertical difference value of each pixel in the horizontal direction within the image based on the pixel coordinates. The terminal device then determines the total difference value corresponding to each of the multiple smooth base fluorescence images based on the horizontal difference value and the vertical difference value.

[0095] For example, after generating multiple smoothed base fluorescence images, the terminal device determines the pixel coordinates (y, x) of each pixel in each of the multiple smoothed base fluorescence images. Then, the terminal device determines the horizontal difference value D between each pixel and its horizontally adjacent pixels based on each pixel coordinate (y, x). x The vertical difference value D generated between the pixel and other pixels adjacent to it in the vertical direction.y The terminal device further adds each horizontal differential value D x and each vertical differential value D y corresponding to each of the plurality of smoothed base fluorescence images to obtain a total differential value D Sum .

[0096] Further, in an available embodiment, the step of "determining each horizontal differential value and each vertical differential value corresponding to each of the plurality of smoothed base fluorescence images" in the step S20 can specifically include:

[0097] Step S201: determining pixel coordinates of each pixel point included in each of the plurality of smoothed base fluorescence images;

[0098] Step S202: determining a horizontal differential value corresponding to each of the pixel points based on each of the pixel coordinates, wherein the horizontal differential value is a differential value between the pixel point and another pixel point adjacent to the pixel point in a horizontal direction;

[0099] Step S203: determining a vertical differential value corresponding to each of the pixel points based on each of the pixel coordinates, wherein the vertical differential value is a differential value between the pixel point and another pixel point adjacent to the pixel point in a vertical direction;

[0100] For example, the terminal device first determines pixel coordinates (y, x) of each pixel point included in each of the plurality of smoothed base fluorescence images, and simultaneously determines a preset differential interval k = 1, and then determines a pixel point (y, x + 1) adjacent to the pixel point (y, x) in a horizontal direction and a pixel point (y + 1, x) adjacent to the pixel point (y, x) in a vertical direction according to the differential interval k = 1, and then determines a preset horizontal differential formula as:

[0101] D x(y，x) = |I(y, x) - I(y, x + 1)|;

[0102] and then performs differential calculation on the pixel point (y, x) and the pixel point (y, x + 1) adjacent to the pixel point (y, x) in the horizontal direction according to the horizontal differential formula to determine a horizontal differential value D x(y，x) corresponding to the pixel point (y, x).

[0103] Meanwhile, the terminal device determines a preset vertical differential formula as:

[0104] D y(y，x) = |I(y, x) - I(y + 1, x)|;

[0105] Further, the terminal device differentiates the pixel point (y, x) and a pixel point (y+1, x) adjacent to the pixel point (y, x) in the vertical direction according to a vertical difference formula to determine a vertical difference value D corresponding to the pixel point (y, x) y(y，x) .

[0106] It should be noted that in the embodiment, the terminal device can differentiate two pixel points spaced by multiple pixels on the same horizontal line or vertical line in addition to differentiating two adjacent pixel points. For example, when the preset differentiation interval k=2 by the technician, the terminal device can differentiate the pixel point (y, x) and a pixel point (y+2, x) spaced by 2 pixels in the vertical direction to obtain a vertical difference value D corresponding to the pixel point (y, x) y(y，x) It can be understood that the technician can arbitrarily set or modify the specific value of the differentiation interval, which is not limited in the present application.

[0107] Step S30: determining the respective luminance values of the fluorescence clusters contained in the plurality of smoothed base fluorescence images, and determining the respective luminance median values of the plurality of smoothed base fluorescence images based on the respective luminance values;

[0108] In the embodiment, the terminal device respectively segments the plurality of smoothed base fluorescence images to determine the fluorescence clusters contained in the plurality of smoothed base fluorescence images, and determine the respective luminance values of the fluorescence clusters, and then determines the respective luminance median values of the plurality of smoothed base fluorescence images based on the respective luminance values.

[0109] For example, please refer to Figure 6 , Figure 6 The fluorescence cluster segmentation effect diagram involved in the embodiment of the base fluorescence image clarity evaluation method of the present application, the terminal device segments the plurality of smoothed base fluorescence images by using the preset binary segmentation method, thereby extracting the fluorescence clusters contained in the plurality of smoothed base fluorescence images, and generating a segmentation effect diagram as shown in Figure 6 , and then the terminal device determines the respective luminance values of the fluorescence clusters in the segmentation effect diagram, sorts the respective luminance values to obtain a sorting result, and determines the respective luminance median values M of the plurality of smoothed base fluorescence images according to the sorting result.

[0110] It should be noted that the binary segmentation method represents that the non-binary image is calculated to become a binary image, so as to convert the gray image into a binary image, which is the simplest method for image segmentation, and is generally used for separating the target and the background. The process of the binary segmentation method mainly includes: setting the pixel gray value greater than a certain critical gray value as a gray maximum value, and setting the value less than the value as a gray minimum value, so as to realize binary, and the commonly used binary methods include but are not limited to: double peak method, P parameter method, iteration method and OTSU method and the like. In addition to the binary segmentation method, the application can also segment the image based on clustering to extract the fluorescent clusters contained in the image, that is, in the embodiments of the application, the skilled person can select any segmentation method based on the demand, and the application does not limit this.

[0111] Further, in a feasible embodiment, the step of "determining the median value of the brightness corresponding to each of the plurality of smoothed base fluorescence images based on the brightness values" in step S30 can specifically include:

[0112] Step S301: sorting each of the brightness values corresponding to each of the plurality of smoothed base fluorescence images to obtain a plurality of sorting results corresponding to each of the plurality of smoothed base fluorescence images;

[0113] Step S302: determining the median value of the brightness corresponding to each of the plurality of smoothed base fluorescence images based on each of the sorting results;

[0114] Exemplarily, for example, the terminal device first determines the brightness values corresponding to each of the plurality of smoothed base fluorescence images, sorts the brightness values according to the numerical value to generate a sorting result, and then determines the median of the brightness values based on the sorting result, and determines the brightness value corresponding to the median as the median value of the brightness corresponding to the smoothed base fluorescence image.

[0115] Step S40: determining the real-time sharpness value corresponding to each of the plurality of smoothed base fluorescence images based on each of the difference total values and each of the median values of the brightness, and constructing a target sharpness curve based on each of the real-time sharpness values and the image number corresponding to each of the plurality of smoothed base fluorescence images, and determining the target base fluorescence image with the highest definition in the plurality of smoothed base fluorescence images according to the target sharpness curve;

[0116] In this embodiment, the terminal device divides the difference total value corresponding to each of the plurality of smoothed base fluorescence images by the median value of the brightness, thereby obtaining the real-time sharpness value corresponding to each of the plurality of smoothed base fluorescence images, and then determines the image number corresponding to each of the plurality of smoothed base fluorescence images, and generates a target sharpness curve according to each of the image numbers and each of the real-time sharpness values, and determines the target base fluorescence image with the highest definition in the plurality of smoothed base fluorescence images according to the target sharpness curve.

[0117] For example, the terminal device determines the difference total value D of each of the plurality of smoothed base fluorescence images Sum The terminal device divides the difference total value D of each of the plurality of smoothed base fluorescence images by the brightness median value M corresponding to each of the plurality of base fluorescence images, to determine the real-time sharpness value SharpValue of each of the plurality of smoothed base fluorescence images, SharpValue = D / M. Sum Afterwards, the terminal device determines the image number corresponding to each of the plurality of smoothed base fluorescence images, and generates a target sharpness curve S1 according to the image number and the real-time sharpness value SharpValue of each of the plurality of smoothed base fluorescence images. Finally, the terminal device determines the target base fluorescence image with the highest sharpness from the plurality of smoothed base fluorescence images based on the generated target sharpness curve S1.

[0118] Further, in a possible implementation, the step of constructing a target sharpness curve based on the real-time sharpness value and the image number corresponding to each of the plurality of smoothed base fluorescence images in step S40 can specifically include:

[0119] Step S401: determining the image number corresponding to each of the plurality of smoothed base fluorescence images, and constructing an initial sharpness curve according to the image number and the real-time sharpness value of each of the plurality of smoothed base fluorescence images.

[0120] Step S402: performing weighted average on the real-time sharpness value based on a preset weight value and the initial sharpness curve, to generate a target sharpness curve.

[0121] For example, the terminal device first constructs an initial sharpness curve S0 based on the image number corresponding to each of the plurality of smoothed base fluorescence images and the real-time sharpness value SharpValue of each of the plurality of smoothed base fluorescence images. Afterwards, the terminal device obtains a preset weight value, and performs weighted average on the real-time sharpness value SharpValue in the initial sharpness curve S0 based on the weight value to generate a target sharpness value. Then, the terminal device generates a target sharpness curve S1 based on the image number and the target sharpness value of each of the plurality of smoothed base fluorescence images.

[0122] Further, in a possible implementation, step S402 can specifically include:

[0123] Step S4021: obtaining a preset weight value, and performing weighted average on the real-time sharpness value based on the weight value and other real-time sharpness values adjacent to the real-time sharpness value in the initial sharpness curve to obtain a target sharpness value.

[0124] Step S4022: generating a target sharpness curve according to the target sharpness value and the image number of each of the plurality of smoothed base fluorescence images.

[0125] Exemplarily, for example, the terminal device first reads the storage device to obtain the weight value preset by the technician, and performs weighted average on each real-time sharpness value SharpValue in the initial sharpness curve S0 and other real-time sharpness values adjacent to the real-time sharpness value SharpValue before and after the real-time sharpness value SharpValue based on the weight value, to obtain a target sharpness value after weighted average, and then the terminal device generates a target sharpness curve S1 as shown in Figure 5 .

[0126] It should be noted that, for details of the initial sharpness curve and the target sharpness curve, please refer to Figure 5 , Figure 5 The initial sharpness curve and the target sharpness curve involved in the embodiment of the method for evaluating the clarity of the base fluorescence image of the present application are compared as shown in Figure 5 . The peak values of the target sharpness curve S1 and the initial sharpness curve S0 generated after weighted average are not the same, that is, if the real-time sharpness values contained in the initial sharpness curve S0 are not weighted and averaged, and the clarity of the base fluorescence image is directly evaluated based on the initial sharpness curve S0, the most clear target base fluorescence image cannot be correctly selected, therefore, the target sharpness curve S1 generated after weighted average can more accurately evaluate the clarity of the base fluorescence image. It should be noted that, Figure 5 , the abscissa is the image number, and the ordinate is the sharpness value.

[0127] Further, in a feasible embodiment, the step of "determining the target base fluorescence image with the highest clarity from the plurality of smoothed base fluorescence images according to the target sharpness curve" in the step S40 can specifically include:

[0128] Step S403: determining the maximum sharpness value in the target sharpness curve, and determining the target image number corresponding to the maximum sharpness value in the target sharpness curve;

[0129] Step S404: determining the smoothed base fluorescence image corresponding to the target image number as the target base fluorescence image with the highest clarity from the plurality of smoothed base fluorescence images;

[0130] Exemplarily, for example, the terminal device first determines the maximum value in the target sharpness curve S1, to determine the target sharpness value corresponding to the maximum value as the maximum sharpness value, and determine the image number corresponding to the maximum sharpness value in the target sharpness curve S1, and then the terminal device determines the base fluorescence image corresponding to the image number as the target base fluorescence image with the highest clarity from the plurality of smoothed base fluorescence images.

[0131] In this embodiment, the terminal device first acquires a plurality of base fluorescence images collected by the camera during runtime, and processes the plurality of base fluorescence images through a preset algorithm model to remove noise interference contained in each of the plurality of base fluorescence images and generate smooth base fluorescence images. Then, the terminal device determines the pixel coordinates corresponding to each of the pixels contained in each of the plurality of smooth base fluorescence images. Then, the terminal device determines the horizontal difference value of each of the pixels in the horizontal direction in the image and the vertical difference value of each of the pixels in the vertical direction according to the pixel coordinates. Then, the terminal device determines the total difference value corresponding to each of the plurality of smooth base fluorescence images according to the horizontal difference values and the vertical difference values. Then, the terminal device segments each of the plurality of smooth base fluorescence images to determine the fluorescence clusters contained in each of the plurality of smooth base fluorescence images and determine the brightness value corresponding to each of the fluorescence clusters. Then, the terminal device determines the median brightness value corresponding to each of the plurality of smooth base fluorescence images based on the brightness values. Finally, the terminal device divides the total difference value corresponding to each of the plurality of smooth base fluorescence images by the median brightness value to obtain the real-time sharpness value corresponding to each of the plurality of smooth base fluorescence images. Then, the terminal device determines the image number corresponding to each of the plurality of smooth base fluorescence images and generates a target sharpness curve according to the image numbers and the real-time sharpness values. The terminal device determines the target base fluorescence image with the highest clarity from the plurality of smooth base fluorescence images according to the target sharpness curve.

[0132] Thus, the application eliminates the noise interference contained in the base fluorescence image, excludes the influence of ambient light on the base fluorescence image based on the real-time sharpness value of the base fluorescence image, constructs a target sharpness curve according to the real-time sharpness value and the image number corresponding to each of the plurality of base fluorescence images, and determines the target base fluorescence image with the highest clarity from the plurality of base fluorescence images based on the target sharpness curve, thereby achieving the technical effect of more accurately evaluating the clarity of the base fluorescence image.

[0133] Further, to achieve the above-mentioned purpose, the application also provides a base fluorescence image clarity evaluation device, which is described in detail below. Figure 7 , Figure 7 An embodiment of the base fluorescence image clarity evaluation method of the application relates to a functional module schematic diagram, as shown in Figure 7 ,

[0134] The noise removal module 10 is configured to remove the noise interference contained in each of the plurality of base fluorescence images to generate smooth base fluorescence images.

[0135] The difference calculation module 20 is configured to determine the horizontal difference value and the vertical difference value corresponding to each of the plurality of smooth base fluorescence images, and determine the total difference value corresponding to each of the plurality of smooth base fluorescence images according to the horizontal difference value and the vertical difference value.

[0136] a brightness calculation module 30, configured to determine a respective brightness value of each fluorescent cluster contained in each of the plurality of smoothed base fluorescence images, and determine a respective brightness median value of each of the plurality of smoothed base fluorescence images based on the respective brightness value;

[0137] an image screening module 40, configured to determine a respective real-time sharpness value of each of the plurality of smoothed base fluorescence images based on the respective differential total value and the respective brightness median value, and construct a target sharpness curve based on the respective real-time sharpness value and an image number corresponding to each of the plurality of smoothed base fluorescence images, and determine a target base fluorescence image with the highest clarity from the plurality of smoothed base fluorescence images according to the target sharpness curve.

[0138] Further, the noise removal module 10 comprises:

[0139] a frequency determination unit, configured to determine a respective frequency domain of each of the plurality of base fluorescence images;

[0140] a high frequency removal unit, configured to remove a high frequency component contained in each of the frequency domains to generate a smoothed base fluorescence image, preferably by a preset Fourier transform algorithm to remove the high frequency component contained in each of the frequency domains to generate the smoothed base fluorescence image.

[0141] Further, the difference calculation module 20 comprises:

[0142] a coordinate determination unit, configured to determine a pixel coordinate of each pixel point contained in each of the plurality of smoothed base fluorescence images;

[0143] a horizontal difference unit, configured to determine a respective horizontal difference value of each of the pixel points based on the respective pixel coordinate, wherein the horizontal difference value is a difference value between the pixel point and another pixel point adjacent to the pixel point in a horizontal direction;

[0144] a numerical difference unit, configured to determine a respective vertical difference value of each of the pixel points based on the respective pixel coordinate, wherein the vertical difference value is a difference value between the pixel point and another pixel point adjacent to the pixel point in a vertical direction.

[0145] Further, the brightness calculation module 30 comprises:

[0146] a brightness sorting unit, configured to sort the respective brightness value of each of the plurality of smoothed base fluorescence images to obtain a sorting result corresponding to each of the plurality of smoothed base fluorescence images;

[0147] a median value determination unit, configured to determine a respective brightness median value of each of the plurality of smoothed base fluorescence images based on the respective sorting result.

[0148] Further, the image screening module 40 comprises:

[0149] The first constructing unit is configured to determine respective image numbers corresponding to the plurality of smoothed base fluorescence images, and construct an initial sharpness curve according to the respective image numbers and the respective real-time sharpness values;

[0150] The second constructing unit is configured to perform weighted average on the respective real-time sharpness values based on preset weight values and the initial sharpness curve, to generate a target sharpness curve.

[0151] Further, the second constructing unit comprises:

[0152] The sharpness weighting subunit is configured to obtain preset weight values, and perform weighted average on the real-time sharpness value based on the weight values and other real-time sharpness values adjacent to the real-time sharpness value in the initial sharpness curve, to obtain a target sharpness value;

[0153] The curve generating subunit is configured to generate a target sharpness curve according to the respective target sharpness values and the respective image numbers.

[0154] Further, the image screening module 40 further comprises:

[0155] The number determining unit is configured to determine a maximum sharpness value in the target sharpness curve, and determine a target image number corresponding to the maximum sharpness value in the target sharpness curve;

[0156] The target determining unit is configured to determine the smoothed base fluorescence image corresponding to the target image number as a target base fluorescence image with the highest definition in the plurality of smoothed base fluorescence images.

[0157] In addition, the present application also provides a terminal device, which has a base fluorescence image definition evaluation program executable on a processor, and the terminal device implements the steps of the base fluorescence image definition evaluation method according to any one of the above embodiments when executing the base fluorescence image definition evaluation program.

[0158] The specific embodiments of the terminal device of the present application are basically the same as the above-mentioned base fluorescence image definition evaluation method, and will not be repeated here.

[0159] In addition, the present application also provides a computer readable storage medium, which stores a base fluorescence image definition evaluation program, and the base fluorescence image definition evaluation program implements the steps of the base fluorescence image definition evaluation method according to any one of the above embodiments when executed by a processor.

[0160] The specific embodiments of the computer readable storage medium of the present application are basically the same as the above-mentioned base fluorescence image definition evaluation method, and will not be repeated here.

[0161] It should be noted that in this paper, the term "includes", "contains" or any other variant thereof is intended to cover non-exclusive inclusion, so that the process, method, article or system including a series of elements not only includes those elements, but also includes other elements not explicitly listed, or includes elements inherent to such process, method, article or system. Without more limitations, the element defined by the sentence "includes a" does not exclude the presence of other identical elements in the process, method, article or system including the element.

[0162] The above-mentioned serial numbers of the embodiments of the present application are only for description, not representing the advantages and disadvantages of the embodiments.

[0163] Through the above description of the embodiments, those skilled in the art can clearly understand that the above-mentioned embodiment method can be realized by software and necessary general hardware platform, of course, it can also be realized by hardware, but in many cases, the former is a better embodiment. Based on such understanding, the technical solutions of the present application can be embodied in the form of software product, which is stored in a storage medium (such as ROM / RAM, magnetic disc, optical disc) as described above, including a plurality of instructions for making a terminal device (which can be a terminal device of the base fluorescence image definition evaluation method of the present application, and the terminal device can be a mobile terminal, data storage control terminal, PC or portable computer terminal) execute the method described in each embodiment of the present application.

[0164] The above is only the preferred embodiment of the present application, and does not limit the patent scope of the present application, and any equivalent structure or equivalent process transformation using the content of the present application specification and drawings, or direct or indirect application in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A method of evaluating base fluorescence image sharpness, characterized by, The base fluorescence image definition evaluation method comprises the following steps: Removing noise interference contained in each of the plurality of base fluorescence images to generate a smoothed base fluorescence image; Determining each corresponding horizontal difference value and vertical difference value of each of the plurality of smoothed base fluorescence images, and determining a difference total value corresponding to each of the plurality of smoothed base fluorescence images according to each of the horizontal difference value and the vertical difference value; Determining each corresponding brightness value of each fluorescent cluster contained in the plurality of smoothed base fluorescence images, and determining a brightness median value corresponding to each of the plurality of smoothed base fluorescence images based on each of the brightness value; Based on each of the difference total value and the brightness median value, determining a real-time sharpness value corresponding to each of the plurality of smoothed base fluorescence images, and determining an image number corresponding to each of the plurality of smoothed base fluorescence images, and constructing an initial sharpness curve according to each of the image number and the real-time sharpness value; based on a preset weight value and the initial sharpness curve, the real-time sharpness value is weighted and averaged to generate a target sharpness curve, and the target base fluorescence image with the highest definition is determined in the plurality of smoothed base fluorescence images according to the target sharpness curve.

2. The method of claim 1, wherein the method comprises: The step of removing noise interference contained in each of the plurality of base fluorescence images to generate a smoothed base fluorescence image comprises: Determining the frequency domain corresponding to each of the plurality of base fluorescence images; Removing high-frequency components contained in each of the frequency domains to generate a smoothed base fluorescence image, and removing high-frequency components contained in each of the frequency domains to generate a smoothed base fluorescence image by a preset Fourier transform algorithm.

3. The method of claim 1, wherein the method further comprises: determining a number of pixels in the base fluorescence image that have a value greater than a predetermined threshold value; and determining a ratio of the number of pixels to a total number of pixels in the base fluorescence image. The step of determining each corresponding horizontal difference value and vertical difference value of each of the plurality of smoothed base fluorescence images comprises: Determining the pixel coordinates of each pixel point contained in each of the plurality of smoothed base fluorescence images; Based on each of the pixel coordinates, determining each corresponding horizontal difference value of each of the pixel points, wherein the horizontal difference value is the difference value between the pixel point and other pixel points adjacent in the horizontal direction; Based on each of the pixel coordinates, determining each corresponding vertical difference value of each of the pixel points, wherein the vertical difference value is the difference value between the pixel point and other pixel points adjacent in the vertical direction.

4. The method of claim 1, wherein the method further comprises: determining a number of pixels in the base fluorescence image that have a value greater than a predetermined threshold value; and determining a ratio of the number of pixels to a total number of pixels in the base fluorescence image. The step of determining each corresponding brightness median value of each of the plurality of smoothed base fluorescence images based on each of the brightness value comprises: Sorting each of the brightness values corresponding to each of the plurality of smoothed base fluorescence images to obtain a sorting result corresponding to each of the plurality of smoothed base fluorescence images; Based on each of the sorting results, determining a brightness median value corresponding to each of the plurality of smoothed base fluorescence images.

5. The method of claim 4, wherein the method further comprises: determining a number of pixels in the base fluorescence image that have a value greater than a predetermined threshold value; and determining a ratio of the number of pixels to a total number of pixels in the base fluorescence image. The step of weighting and averaging each of the real-time sharpness values based on a preset weight value and the initial sharpness curve to generate a target sharpness curve comprises: Obtaining a preset weight value, and weighting and averaging the real-time sharpness value based on the weight value and other real-time sharpness values adjacent to the real-time sharpness value in the initial sharpness curve to obtain a target sharpness value; Generating a target sharpness curve according to each of the target sharpness values and each of the image numbers.

6. The method of claim 1, wherein the method further comprises: determining a fluorescence intensity of the base at the base position; and determining a fluorescence intensity of the base at the base position in the reference image. The step of determining the target base fluorescence image with the highest definition from the plurality of smoothed base fluorescence images according to the target sharpness curve comprises: determining a maximum sharpness value within the target sharpness curve, and determining a target image number corresponding to the maximum sharpness value within the target sharpness curve; determining the smoothed base fluorescence image corresponding to the target image number as the target base fluorescence image with the highest definition from the plurality of smoothed base fluorescence images.

7. A device for evaluating the sharpness of base fluorescence images, characterized in that, The device comprises: a noise removal module configured to remove noise interference contained in each of the plurality of base fluorescence images to generate a smoothed base fluorescence image; a difference calculation module configured to determine a horizontal difference value and a vertical difference value corresponding to each of the plurality of smoothed base fluorescence images, and determine a total difference value corresponding to each of the plurality of smoothed base fluorescence images according to the horizontal difference value and the vertical difference value; a brightness calculation module configured to determine a brightness value corresponding to each of the fluorescence clusters contained in each of the plurality of smoothed base fluorescence images, and determine a brightness median value corresponding to each of the plurality of smoothed base fluorescence images based on the brightness value; an image screening module configured to determine a real-time sharpness value corresponding to each of the plurality of smoothed base fluorescence images based on the total difference value and the brightness median value, and construct a target sharpness curve based on the real-time sharpness value and an image number corresponding to each of the plurality of smoothed base fluorescence images, and determine a target base fluorescence image with the highest definition from the plurality of smoothed base fluorescence images according to the target sharpness curve, wherein the image screening module is specifically configured to determine the image number corresponding to each of the plurality of smoothed base fluorescence images, and construct an initial sharpness curve according to the image number and the real-time sharpness value; and perform weighted average on the real-time sharpness value based on a preset weight value and the initial sharpness curve to generate the target sharpness curve.

8. A terminal device, comprising: The terminal device comprises a memory, a processor, and a base fluorescence image definition evaluation program stored on the memory and executable on the processor, and the base fluorescence image definition evaluation program, when executed by the processor, implements the steps of the base fluorescence image definition evaluation method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a base fluorescence image definition evaluation program, and the base fluorescence image definition evaluation program, when executed by a processor, implements the steps of the base fluorescence image definition evaluation method according to any one of claims 1 to 6.

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