Image correction method and device, electronic equipment and computer readable storage medium

Abstract

Embodiments of the present application provide an image correction method and device, electronic equipment and computer readable storage medium, and relate to the technical field of computers. The method comprises: obtaining a preset image correction coefficient of the radiation detector; and performing correction processing on the image to be corrected according to the image correction coefficient to obtain a target image after correction. The image correction coefficient is determined by a first image and a second image photographed by a first radiation intensity and a second radiation intensity, that is, the image to be corrected is corrected by two bright-state image templates. Since the error caused by the scintillator defect is small when two bright-state image templates are used, the accuracy of the image correction coefficient can be improved, and the accuracy of the corrected image is improved.

Description

Technical Field

[0001] This application relates to the field of computer technology, and more specifically, to an image correction method, apparatus, electronic device, and computer-readable storage medium. Background Technology

[0002] In the field of digital imaging, X-ray detectors are typically used to convert X-ray energy into digital images. For example, X-ray detectors can be applied in medical diagnosis, industrial inspection, security checks, and other scenarios.

[0003] The manufacturing process of X-ray detectors is complex, requiring high precision and strict adherence to process flow. Even minor fluctuations during production can affect the output image. However, in practical applications, process variations are unavoidable in X-ray detector manufacturing, leading to inconsistencies in components such as the scintillator, dirt, and differences between IC channels. All of these factors can cause deviations in the pixel parameters of the images captured by the X-ray detector.

[0004] Therefore, correcting the images captured by the X-ray detector has become a technical problem that needs to be solved. Summary of the Invention

[0005] The purpose of this application is to at least solve one of the aforementioned technical defects, particularly the technical defect that the pixel parameters of images captured by the X-ray detector are deviated.

[0006] According to one aspect of this application, an image correction method is provided, the method comprising:

[0007] Acquire an image to be corrected; wherein the image to be corrected includes an image captured by a ray detector;

[0008] Obtain the preset image correction coefficients of the ray detector;

[0009] The image correction coefficient is determined based on a first image and a second image pre-captured by the ray detector; the first image and the second image are captured by the ray detector through a first ray intensity and a second ray intensity, respectively; both the first ray intensity and the second ray intensity are not zero;

[0010] The image to be corrected is processed according to the image correction coefficients to obtain the corrected target image.

[0011] Optionally, the method further includes:

[0012] Obtain the first pixel parameters of the pixels in the first image and the second pixel parameters of the pixels in the second image;

[0013] Determine a first average parameter of the first pixel parameter, and determine a second average parameter of the second pixel parameter;

[0014] The image correction coefficient is determined based on the proportional relationship between the first difference and the second difference; wherein the first difference includes the difference between the first pixel parameter and the second pixel parameter; and the second difference includes the difference between the first average parameter and the second average parameter.

[0015] Optionally, the step of performing correction processing on the image to be corrected according to the image correction coefficients to obtain the corrected target image includes:

[0016] Based on the image correction coefficient, the third pixel parameter of the pixel in the image to be corrected is corrected to obtain the corrected pixel parameter.

[0017] The target image is obtained based on the corrected pixel parameters.

[0018] Optionally, the step of correcting the third pixel parameter according to the image correction coefficient to obtain the corrected pixel parameter includes:

[0019] Determine the third difference between the third pixel parameter and the first pixel parameter;

[0020] The corrected pixel parameters are determined based on the product of the image correction coefficient and the third difference.

[0021] Optionally, the step of correcting the third pixel parameter according to the image correction coefficient to obtain the corrected pixel parameter includes:

[0022] Determine the third difference between the third pixel parameter and the first pixel parameter;

[0023] Determine the product of the image correction coefficient and the third difference.

[0024] The corrected pixel parameters are determined based on the sum of the product value and the first average parameter.

[0025] Optionally, the step of correcting the third pixel parameter according to the image correction coefficient to obtain the corrected pixel parameter includes:

[0026] Obtain the fourth pixel parameter, wherein the fourth pixel parameter is determined based on the pixel parameters of the image captured by the ray detector at the third ray intensity;

[0027] Determine the fourth difference between the third pixel parameter and the fourth pixel parameter;

[0028] The corrected pixel parameters are determined based on the product of the image correction coefficient and the fourth difference.

[0029] Optionally, the first image and the second image are images taken by the X-ray detector under no-load conditions, which include situations where there is no target object to be photographed.

[0030] According to another aspect of this application, an image correction apparatus is provided, the apparatus comprising:

[0031] The first acquisition module is used to acquire the image to be corrected; wherein, the image to be corrected includes an image captured by a ray detector;

[0032] The second acquisition module is used to acquire the preset image correction coefficients of the ray detector;

[0033] The image correction coefficient is determined based on a first image and a second image pre-captured by the ray detector; the first image and the second image are captured by the ray detector through a first ray intensity and a second ray intensity, respectively; both the first ray intensity and the second ray intensity are not zero;

[0034] The correction module is used to perform correction processing on the image to be corrected according to the image correction coefficients to obtain the corrected target image.

[0035] According to another aspect of this application, an electronic device is provided, the electronic device comprising:

[0036] A memory, a processor, and a computer program stored in the memory, characterized in that the processor executes the computer program to implement the steps of the image correction method according to any one of the first aspects of this application.

[0037] For example, in a third aspect of this application, a computing device is provided, comprising: a processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other via the communication bus;

[0038] The memory is used to store at least one executable instruction that causes the processor to perform an operation corresponding to the image correction method shown in the first aspect of this application.

[0039] According to another aspect of this application, a computer-readable storage medium is provided having a computer program stored thereon, characterized in that, when the computer program is executed by a processor, it implements the steps of the image correction method according to any one of the first aspects of this application.

[0040] For example, in a fourth aspect of the present application, a computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the image correction method shown in the first aspect of the present application.

[0041] According to one aspect of this application, a computer program product or computer program is provided, comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the methods provided in various alternative implementations of the first aspect described above.

[0042] The beneficial effects of the technical solution provided in this application are:

[0043] In this embodiment, a preset image correction coefficient of the X-ray detector is obtained; based on the image correction coefficient, the image to be corrected is corrected to obtain the corrected target image. The image correction coefficient is determined based on a first image and a second image captured by the X-ray detector at a first X-ray intensity and a second X-ray intensity. This method of determining the image correction coefficient using the first and second images captured at the first and second X-ray intensities, i.e., using two bright-state image templates to correct the image to be corrected, reduces the error caused by scintillator defects when using two bright-state image templates, thus improving the accuracy of the image correction coefficient and consequently enhancing the accuracy of the corrected image. Attached Figure Description

[0044] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments of this application will be briefly introduced below.

[0045] Figure 1 This is a schematic diagram of the system architecture of an image correction method provided in an embodiment of this application;

[0046] Figure 2 This is one of the flowcharts illustrating an image correction method provided in an embodiment of this application;

[0047] Figure 3 This is one of the schematic diagrams of the light response curve of an image correction method provided in an embodiment of this application;

[0048] Figure 4 A second schematic diagram of the light response curve of an image correction method provided in this application embodiment;

[0049] Figure 5 A third schematic diagram of the light response curve of an image correction method provided in this application embodiment;

[0050] Figure 6 This is a second schematic flowchart illustrating an image correction method provided in an embodiment of this application.

[0051] Figure 7 This is a schematic diagram illustrating an application scenario of an image correction method provided in an embodiment of this application;

[0052] Figure 8 This is a schematic diagram of the structure of an image correction device provided in an embodiment of this application;

[0053] Figure 9 This is a schematic diagram of the structure of an electronic device for image correction provided in an embodiment of this application. Detailed Implementation

[0054] The embodiments of this application are described below with reference to the accompanying drawings. It should be understood that the embodiments described below with reference to the accompanying drawings are exemplary descriptions for explaining the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions of the embodiments of this application.

[0055] Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the terms “comprising” and “including” as used in embodiments of this application mean that the corresponding feature can be implemented as the presented feature, information, data, step, operation, element, and / or component, but do not exclude implementation as other features, information, data, step, operation, element, component, and / or combinations thereof supported by the art. It should be understood that when we say that an element is “connected” or “coupled” to another element, the one element can be directly connected or coupled to the other element, or it can mean that the one element and the other element establish a connection relationship through an intermediate element. Furthermore, “connected” or “coupled” as used herein can include wireless connection or wireless coupling. The term “and / or” as used herein indicates at least one of the items defined by the term; for example, “A and / or B” can be implemented as “A,” or as “B,” or as “A and B.”

[0056] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0057] To further illustrate the technical solutions provided in the embodiments of this application, a detailed description is provided below in conjunction with the accompanying drawings and specific implementation methods. Although the embodiments of this application provide method operation steps as shown in the following embodiments or drawings, the method may include more or fewer operation steps based on conventional or non-inventive methods. In steps where there is no logically necessary causal relationship, the execution order of these steps is not limited to the execution order provided in the embodiments of this application.

[0058] First, combine Figure 1 This is a system architecture diagram of the image correction method provided in the embodiments of this application. The system may include a server 101 and a terminal cluster, wherein the server 101 can be considered as a backend server for image correction processing.

[0059] The terminal cluster may include: terminal 102, terminal 103, terminal 104, ..., wherein each terminal may have a client installed that supports image correction processing. Communication connections may exist between the terminals; for example, there may be a communication connection between terminal 102 and terminal 103, and a communication connection between terminal 103 and terminal 104.

[0060] Meanwhile, server 101 can provide services to the terminal cluster through communication connection function. Any terminal in the terminal cluster can have a communication connection with server 101. For example, terminal 102 has a communication connection with server 101, and terminal 103 has a communication connection with server 101. The above-mentioned communication connection is not limited to the connection method. It can be directly or indirectly connected through wired communication, or directly or indirectly connected through wireless communication, or through other methods.

[0061] The network for the aforementioned communication connection can be a wide area network (WAN), a local area network (LAN), or a combination of both. This application does not impose any restrictions on this.

[0062] In this embodiment, a preset image correction coefficient of the X-ray detector is obtained; based on the image correction coefficient, the image to be corrected is corrected to obtain the corrected target image. The image correction coefficient is determined based on a first image and a second image captured by the X-ray detector at a first X-ray intensity and a second X-ray intensity. This method of determining the image correction coefficient using the first and second images captured at the first and second X-ray intensities, i.e., using two bright-state image templates to correct the image to be corrected, reduces the error caused by scintillator defects when using two bright-state image templates, thus improving the accuracy of the image correction coefficient and consequently enhancing the accuracy of the corrected image.

[0063] The methods provided in this application can be executed by computer devices, including but not limited to terminals (including the aforementioned user terminals) or servers (including the aforementioned server 101). The server can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The terminal can be a smartphone, tablet computer, laptop computer, desktop computer, smart speaker, smartwatch, etc., but is not limited to these. The terminal and server can be directly or indirectly connected via wired or wireless communication, which is not limited herein.

[0064] The embodiments described in this application are not intended to be limiting. Figure 1 The functions that each device in the application scenario shown can achieve will be described in subsequent method embodiments, and will not be elaborated on here.

[0065] This application provides a possible implementation, which can be executed by any electronic device. Optionally, any electronic device can be a server device with image correction capabilities, or a device or chip integrated into these devices. Figure 2 As shown, this is one of the flowcharts of an image correction method provided in an embodiment of this application. The method includes the following steps:

[0066] Step S201: Obtain the image to be corrected. The image to be corrected includes an image captured by a radiation detector.

[0067] Optionally, the image correction method of this application embodiment can be applied to application scenarios that correct images captured by a ray detector.

[0068] The aforementioned radiation detector is a device that converts radiation energy into a digital image that can be recorded. Radiation detectors offer advantages such as fast imaging speed, ease of operation, and high image quality. In practical applications, radiation detectors can be used in medical diagnosis, industrial inspection, security checks, and other scenarios. The radiation detector may include X-ray detectors, alpha-ray detectors, and so on.

[0069] Optionally, this application may use an X-ray detector as an example for illustration. An X-ray detector is a device that converts X-ray energy into a digital image that can be recorded. An X-ray detector mainly consists of two system components: a detector panel and a scintillator. X-rays irradiate the scintillator and are converted into visible light, which is then absorbed by the silicon material below, ultimately outputting images with different grayscale values. Within a certain dose range, the intensity of the X-rays received by the detector is directly proportional to the grayscale value of the final output image; that is, the greater the intensity of the received X-rays, the greater the grayscale value of the image, and vice versa.

[0070] In medical diagnostic scenarios, for example, the intensity of the X-ray signal received by the detector typically depends on the density of the tissue within the cross-section of the human body at the irradiated site. High-density tissues (such as bone) absorb more X-rays, resulting in a weaker intensity of radiation received by the detector; conversely, low-density tissues (such as fat) absorb less X-rays, leading to a stronger intensity of radiation received by the detector. Based on the intensity of the radiation received by the detector, the resulting image can be determined.

[0071] The image to be corrected includes images captured by a X-ray detector. In practical scenarios, the image to be corrected may include images obtained by capturing images of the target object using the X-ray detector. As an example, in a medical diagnostic scenario, the target object can be a part of a patient's body, such as the patient's legs, feet, waist, head, etc.; images of these parts can be obtained by capturing images with the X-ray detector. As yet another example, in an industrial inspection scenario, the target object can be a product, device, part, etc., such as a ceramic product, a device in a car, or a screw.

[0072] Because the manufacturing process of X-ray detectors is complex and requires high precision in terms of process flow, even minor fluctuations during production can affect the output image. In practical applications, process fluctuations are unavoidable in the manufacturing process of X-ray detectors, leading to unevenness or contamination in components such as scintillators, and differences between IC channels. These issues can all cause deviations in the pixel parameters (e.g., grayscale values) of the images captured by the X-ray detector. Therefore, the embodiments of this application can correct the images captured by the X-ray detector (i.e., the images to be corrected).

[0073] In some alternative implementations, the image to be corrected can be obtained by receiving an image uploaded by a radiation detector, or by obtaining it from a database storing images to be corrected, etc. The above acquisition methods are merely examples and are not limited in this application.

[0074] Step S202: Obtain the preset image correction coefficients of the X-ray detector.

[0075] The image correction coefficient is determined based on a first image and a second image pre-captured by the ray detector; the first image and the second image are captured by the ray detector through a first ray intensity and a second ray intensity, respectively; and both the first ray intensity and the second ray intensity are not zero.

[0076] The image correction coefficient includes correction parameters for correcting the image to be corrected. The image correction coefficient is related to the instrument performance of the X-ray detector itself. By determining this image correction coefficient, deviations in the pixel parameters of the image captured by the X-ray detector can be corrected.

[0077] In this embodiment, the image correction coefficient can be determined based on a first image and a second image pre-captured by the ray detector. The first image is an image captured by the ray detector at a first ray intensity; the second image is an image captured by the ray detector at a second ray intensity; wherein the first ray intensity and the second ray intensity are different, optionally, in this embodiment, the first ray intensity is less than the second ray intensity.

[0078] In some alternative implementations, the first image and the second image are images taken by the ray detector under no-load conditions, which include situations where there is no target object to be photographed.

[0079] In other words, the first and second images are images taken by the X-ray detector without any object being photographed. The first and second images can be understood as being used to determine image correction coefficients.

[0080] In some optional implementations, the image correction coefficient can be determined based on the pixel parameters of the pixels in the first image (which can be referred to as the first pixel parameter for easy distinction) and the pixel parameters of the pixels in the second image (which can be referred to as the second pixel parameter for easy distinction). Optionally, the pixel parameters can be the grayscale value of the pixel, etc.

[0081] Step S203: According to the image correction coefficient, perform correction processing on the image to be corrected to obtain the corrected target image.

[0082] In some optional implementations, when performing correction processing on the image to be corrected, the pixel parameters of each pixel in the image to be corrected can be corrected separately. For example, in practical implementation scenarios, calculations can be performed based on the image correction parameters and the pixel parameters of the pixels in the image to be corrected to obtain the corrected pixel parameters. In this way, the target image can be obtained based on the corrected pixel parameters of the pixels.

[0083] In this embodiment, a preset image correction coefficient of the X-ray detector is obtained; based on the image correction coefficient, the image to be corrected is corrected to obtain the corrected target image. The image correction coefficient is determined based on a first image and a second image captured by the X-ray detector at a first X-ray intensity and a second X-ray intensity. This method of determining the image correction coefficient using the first and second images captured at the first and second X-ray intensities, i.e., using two bright-state image templates to correct the image to be corrected, reduces the error caused by scintillator defects when using two bright-state image templates, thus improving the accuracy of the image correction coefficient and consequently enhancing the accuracy of the corrected image.

[0084] In one embodiment of this application, the method further includes:

[0085] Obtain the first pixel parameters of the pixels in the first image and the second pixel parameters of the pixels in the second image;

[0086] The image correction coefficient is determined based on the first pixel parameter and the second pixel parameter.

[0087] In one embodiment of this application, determining the image correction coefficient based on the first pixel parameter and the second pixel parameter includes:

[0088] Determine a first average parameter of the first pixel parameter, and determine a second average parameter of the second pixel parameter;

[0089] The image correction coefficient is determined based on the proportional relationship between the first difference and the second difference; wherein the first difference includes the difference between the first pixel parameter and the second pixel parameter; and the second difference includes the difference between the first average parameter and the second average parameter.

[0090] Specifically, embodiments of this application may further include a processing step of pre-determining the image correction coefficients.

[0091] In some alternative implementations, the image correction coefficients can be determined by the slope of the average light response curve of the ray detector. Combined with Figure 3As shown, the average light response curve characterizes the relationship between the average gray value of pixels in an image captured under different ray intensities and the ray intensity. When determining the average light response curve, it can be determined based on the first average parameter of the first pixel parameter under the first ray intensity and the second average parameter of the second pixel parameter under the second ray intensity.

[0092] Therefore, the first average parameter of the first pixel parameter (i.e., the average value of the first pixel parameter) can be determined first, and the second average parameter of the second pixel parameter (i.e., the average value of the second pixel parameter) can be determined. Then, the average light response curve is determined based on the first ray intensity, the first average parameter, the second ray intensity, and the second average parameter (i.e., the average light response curve is determined by points a and b).

[0093] After determining the average light response curve, the image correction coefficient can be determined based on the proportional relationship between the first difference and the second difference; wherein, the first difference includes the difference between the first pixel parameter and the second pixel parameter; and the second difference includes the difference between the first average parameter and the second average parameter.

[0094] The image correction coefficient Gain(x,y) can be expressed as:

[0095] Among them, I light_2_avg Indicates the second average parameter; I light_1_avg I represents the first average parameter; light_2 (x,y) represents the second pixel parameter; I light_1 (x,y) represents the first pixel parameter; (x,y) represents the pixel coordinate position.

[0096] In one embodiment of this application, the step of performing correction processing on the image to be corrected according to the image correction coefficients to obtain the corrected target image includes:

[0097] Based on the image correction coefficient, the third pixel parameter of the pixel in the image to be corrected is corrected to obtain the corrected pixel parameter.

[0098] The target image is obtained based on the corrected pixel parameters.

[0099] Specifically, the third pixel parameter can be the grayscale value of a pixel in the image to be corrected.

[0100] The correction process for the third pixel parameter can include various processing methods:

[0101] As an optional implementation, the step of correcting the third pixel parameter according to the image correction coefficient to obtain the corrected pixel parameter includes:

[0102] Determine the third difference between the third pixel parameter and the first pixel parameter;

[0103] The corrected pixel parameters are determined based on the product of the image correction coefficient and the third difference.

[0104] Optionally, in this processing method, the corrected pixel parameter I output (x,y) can be represented as:

[0105] Among them, I light_2_avg Indicates the second average parameter; I light_1_avg I represents the first average parameter; light_2 (x, y) represents the second pixel parameter; I light_1 (x, y) represents the first pixel parameter; (x, y) represents the pixel coordinate position; I input (x, y) represents the third pixel parameter.

[0106] As another optional implementation, the step of correcting the third pixel parameter according to the image correction coefficient to obtain the corrected pixel parameter includes:

[0107] Determine the third difference between the third pixel parameter and the first pixel parameter;

[0108] Determine the product of the image correction coefficient and the third difference.

[0109] The corrected pixel parameters are determined based on the sum of the product value and the first average parameter.

[0110] Optionally, in this processing method, the corrected pixel parameter Io utput (x, y) can be represented as:

[0111] Among them, I light_2_avg Indicates the second average parameter; I light_1_avg I represents the first average parameter; light_2 (x, y) represents the second pixel parameter; I light_1 (x, y) represents the first pixel parameter; (x, y) represents the pixel coordinate position; I input (x, y) represents the third pixel parameter.

[0112] It is understandable that, in the above processing method, a constant I is added to the corrected pixel parameters. light_1_avg This process is to avoid the occurrence of I input (x, y) - I light_1 When (x, y) is less than 0, the corrected pixel parameter is negative.

[0113] As another optional implementation, the step of correcting the third pixel parameter according to the image correction coefficient to obtain the corrected pixel parameter includes:

[0114] Obtain the fourth pixel parameter, wherein the fourth pixel parameter is determined based on the pixel parameters of the image captured by the ray detector at the third ray intensity;

[0115] Determine the fourth difference between the third pixel parameter and the fourth pixel parameter;

[0116] The corrected pixel parameters are determined based on the product of the image correction coefficient and the fourth difference.

[0117] Optionally, in this processing method, the corrected pixel parameter Io utput (x, y) can be represented as:

[0118] Among them, I light_2_avg Indicates the second average parameter; I light_1_avg I represents the first average parameter; light_2 (x, y) represents the second pixel parameter; I light_1 (x, y) represents the first pixel parameter; (x, y) represents the pixel coordinate position; I input (x, y) represents the third pixel parameter; I dark_fitted (x, y) represents the fourth pixel parameter; the fourth pixel parameter is the pixel parameter fitted based on the image taken without applied ray intensity, that is, the fourth pixel parameter is... Figure 4 The gray value of the intersection point (m point) of the mid-light response curve and the vertical axis.

[0119] In this embodiment, a preset image correction coefficient of the X-ray detector is obtained; based on the image correction coefficient, the image to be corrected is corrected to obtain the corrected target image. The image correction coefficient is determined based on a first image and a second image captured by the X-ray detector at a first X-ray intensity and a second X-ray intensity. This method of determining the image correction coefficient using the first and second images captured at the first and second X-ray intensities, i.e., using two bright-state image templates to correct the image to be corrected, reduces the error caused by scintillator defects when using two bright-state image templates, thus improving the accuracy of the image correction coefficient and consequently enhancing the accuracy of the corrected image.

[0120] The following is combined with Figures 6 to 7 The overall implementation process and scenarios of the embodiments of this application are described below:

[0121] Combination Figure 6 First, multiple frames of bright-state images under the first ray intensity (i.e., the first image in this embodiment) are acquired, a first correction template is generated, and the first pixel parameter Ilight_1(x,y) is determined. Then, multiple frames of bright-state images under the second ray intensity (i.e., the second image in this embodiment) are acquired, a second correction template is generated, and the second pixel parameter Ilight_2(x,y) is determined. Further, the average light response curve is determined using the two bright-state templates to obtain the image correction coefficients. Further, the image to be corrected on the detector is corrected to obtain the corrected image, which is then output. In some implementation scenarios, the average grayscale value of bright-state template 1 is typically selected from 5000 to 15000 LSB, and the average grayscale value of bright-state template 2 is typically selected from the range of 20000 to 35000.

[0122] Combination Figure 7 , Figure 7 To compare the images corrected using the traditional method and the method proposed in this application, and to make the comparison more obvious, a detector image prepared using a mask stitching process is used here. In the mask stitching area, due to abrupt changes in pixel sensitivity, dark-state grayscale values, etc., anomalies are usually present in the corrected image. It can be seen that the traditional correction method leaves obvious stitching marks at the mask stitching location, while the stitching marks in the image corrected using the method proposed in this application are slight and difficult to detect.

[0123] Compared to the prior art method of determining image correction coefficients using an image taken without applied ray intensity (dark state template) and an image taken with applied ray intensity (bright state template), the image correction coefficients determined in this embodiment are more accurate. The reasons are as follows:

[0124] Combination Figure 4 and Figure 5 In existing technologies, the grayscale value of point m on the light response curve determined by the dark and bright state templates is the fitted dark state grayscale value determined by the curve. However, the measured dark state grayscale value is different from the fitted dark state grayscale value, which leads to the inaccuracy of the average light response curve determined by the dark and bright state templates. Consequently, the determined correction pixel parameters are also inaccurate (as shown in the figure, there is a certain deviation between the expected correction value and the actual correction value). This application overcomes the related defects in existing technologies by determining the average light response curve and image correction coefficients through two bright state templates.

[0125] In summary, by obtaining the preset image correction coefficients of the X-ray detector, and then correcting the image to be corrected based on these coefficients, a corrected target image is obtained. The image correction coefficients are determined based on the first and second images captured by the X-ray detector at first and second X-ray intensities, respectively. This application determines the image correction coefficients using the first and second images captured at the first and second X-ray intensities, i.e., by using two bright-state image templates to correct the image to be corrected. Since the error caused by scintillator defects is smaller when using two bright-state image templates, the accuracy of the image correction coefficients can be improved, thereby enhancing the accuracy of the corrected image.

[0126] This application provides an image correction device, such as... Figure 8 As shown, the image correction device 80 may include: a first acquisition module 801, a second acquisition module 802, and a correction module 803, wherein,

[0127] The first acquisition module 801 is used to acquire an image to be corrected; wherein, the image to be corrected includes an image captured by a radiation detector;

[0128] The second acquisition module 802 is used to acquire the preset image correction coefficients of the ray detector;

[0129] The image correction coefficient is determined based on a first image and a second image pre-captured by the ray detector; the first image and the second image are captured by the ray detector through a first ray intensity and a second ray intensity, respectively; and both the first ray intensity and the second ray intensity are not zero.

[0130] The correction module 803 is used to perform correction processing on the image to be corrected according to the image correction coefficients to obtain the corrected target image.

[0131] In one embodiment of this application, the device further includes a coefficient determination module, used to obtain the first pixel parameters of the pixels in the first image and the second pixel parameters of the pixels in the second image;

[0132] The image correction coefficient is determined based on the first pixel parameter and the second pixel parameter.

[0133] In one embodiment of this application, the coefficient determination module is specifically used to determine a first average parameter of the first pixel parameter and a second average parameter of the second pixel parameter;

[0134] The image correction coefficient is determined based on the proportional relationship between the first difference and the second difference; wherein the first difference includes the difference between the first pixel parameter and the second pixel parameter; and the second difference includes the difference between the first average parameter and the second average parameter.

[0135] In one embodiment of this application, the correction module is specifically used to correct the third pixel parameter of the pixel in the image to be corrected according to the image correction coefficient, so as to obtain the corrected pixel parameter;

[0136] The target image is obtained based on the corrected pixel parameters.

[0137] In one embodiment of this application, the correction module is specifically used to determine a third difference between the third pixel parameter and the first pixel parameter;

[0138] The corrected pixel parameters are determined based on the product of the image correction coefficient and the third difference.

[0139] In one embodiment of this application, the correction module is specifically used to determine a third difference between the third pixel parameter and the first pixel parameter;

[0140] Determine the product of the image correction coefficient and the third difference.

[0141] The corrected pixel parameters are determined based on the sum of the product value and the first average parameter.

[0142] In one embodiment of this application, the correction module is specifically used to obtain a fourth pixel parameter, wherein the fourth pixel parameter is determined based on the pixel parameters of the image captured by the ray detector at the third ray intensity;

[0143] Determine the fourth difference between the third pixel parameter and the fourth pixel parameter;

[0144] The corrected pixel parameters are determined based on the product of the image correction coefficient and the fourth difference.

[0145] In one embodiment of this application, the first image and the second image are images taken by the X-ray detector under no-load conditions, which includes situations where there is no target object to be photographed.

[0146] The apparatus in this application embodiment can execute the method provided in this application embodiment, and the implementation principle is similar. The actions performed by each module in the apparatus of each embodiment of this application correspond to the steps in the method of each embodiment of this application. For detailed functional descriptions of each module of the apparatus, please refer to the descriptions in the corresponding methods shown above, which will not be repeated here.

[0147] In this embodiment, a preset image correction coefficient of the X-ray detector is obtained; based on the image correction coefficient, the image to be corrected is corrected to obtain the corrected target image. The image correction coefficient is determined based on a first image and a second image captured by the X-ray detector at a first X-ray intensity and a second X-ray intensity. This method of determining the image correction coefficient using the first and second images captured at the first and second X-ray intensities, i.e., using two bright-state image templates to correct the image to be corrected, reduces the error caused by scintillator defects when using two bright-state image templates, thus improving the accuracy of the image correction coefficient and consequently enhancing the accuracy of the corrected image.

[0148] This application provides an electronic device comprising: a memory and a processor; at least one program stored in the memory, which, when executed by the processor, can achieve the following compared to existing technologies: In this application, a preset image correction coefficient of the X-ray detector is obtained; and the image to be corrected is corrected according to the image correction coefficient to obtain a corrected target image. The image correction coefficient is determined based on a first image and a second image captured by the X-ray detector at a first X-ray intensity and a second X-ray intensity. The method of determining the image correction coefficient using the first and second images captured at the first and second X-ray intensities, i.e., using two bright-state image templates to correct the image to be corrected, improves the accuracy of the image correction coefficient and thus enhances the accuracy of the corrected image because the error caused by scintillator defects is small when using two bright-state image templates.

[0149] In one alternative embodiment, an electronic device is provided, such as Figure 9 As shown, Figure 9The illustrated electronic device 4000 includes a processor 4001 and a memory 4003. The processor 4001 and the memory 4003 are connected, for example, via a bus 4002. Optionally, the electronic device 4000 may further include a transceiver 4004, which can be used for data interaction between the electronic device and other electronic devices, such as sending and / or receiving data. It should be noted that in practical applications, the transceiver 4004 is not limited to one type, and the structure of the electronic device 4000 does not constitute a limitation on the embodiments of this application.

[0150] Processor 4001 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 4001 may also be a combination that implements computational functions, such as including one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.

[0151] Bus 4002 may include a pathway for transmitting information between the aforementioned components. Bus 4002 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. Bus 4002 can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 9 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0152] The memory 4003 may be ROM (Read Only Memory) or other types of static storage devices capable of storing static information and instructions, RAM (Random Access Memory) or other types of dynamic storage devices capable of storing information and instructions, or EEPROM (Electrically Erasable Programmable Read Only Memory), CD-ROM (Compact Disc Read Only Memory) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto.

[0153] The memory 4003 stores application code (computer program) that executes the solution of this application, and its execution is controlled by the processor 4001. The processor 4001 executes the application code stored in the memory 4003 to implement the content shown in the foregoing method embodiments.

[0154] Electronic devices include, but are not limited to: mobile phones, laptops, multimedia players, desktop computers, etc.

[0155] This application provides a computer-readable storage medium storing a computer program that, when run on a computer, enables the computer to execute the corresponding content in the aforementioned method embodiments.

[0156] In this embodiment, a preset image correction coefficient of the X-ray detector is obtained; based on the image correction coefficient, the image to be corrected is corrected to obtain the corrected target image. The image correction coefficient is determined based on a first image and a second image captured by the X-ray detector at a first X-ray intensity and a second X-ray intensity. This method of determining the image correction coefficient using the first and second images captured at the first and second X-ray intensities, i.e., using two bright-state image templates to correct the image to be corrected, reduces the error caused by scintillator defects when using two bright-state image templates, thus improving the accuracy of the image correction coefficient and consequently enhancing the accuracy of the corrected image.

[0157] The terms "first," "second," "third," "fourth," "1," "2," etc. (if present) in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in a sequence other than that shown in the figures or text.

[0158] It should be understood that although arrows indicate various operation steps in the flowcharts of this application's embodiments, the order in which these steps are implemented is not limited to the order indicated by the arrows. Unless explicitly stated herein, in some implementation scenarios of this application's embodiments, the implementation steps in each flowchart can be executed in other orders as required. Furthermore, some or all steps in each flowchart, based on the actual implementation scenario, may include multiple sub-steps or multiple stages. Some or all of these sub-steps or stages can be executed at the same time, and each sub-step or stage can also be executed at different times. In scenarios where execution times differ, the execution order of these sub-steps or stages can be flexibly configured according to requirements, and this application's embodiments do not limit this.

[0159] The above description is only an optional implementation method for some implementation scenarios of this application. It should be noted that for those skilled in the art, other similar implementation methods based on the technical concept of this application without departing from the technical concept of this application also fall within the protection scope of the embodiments of this application.

Claims

1. An image correction method, characterized in that, include: Acquire an image to be corrected; wherein the image to be corrected includes an image captured by a ray detector; Obtain the preset image correction coefficients of the ray detector; The image correction coefficient is determined based on a first image and a second image pre-captured by the ray detector; the first image and the second image are captured by the ray detector through a first ray intensity and a second ray intensity, respectively; both the first ray intensity and the second ray intensity are not zero; The image to be corrected is corrected according to the image correction coefficients to obtain the corrected target image; The method further includes: Obtain the first pixel parameters of the pixels in the first image and the second pixel parameters of the pixels in the second image; Determine a first average parameter of the first pixel parameter, and determine a second average parameter of the second pixel parameter; The image correction coefficient is determined based on the proportional relationship between the first difference and the second difference; wherein the first difference includes the difference between the first pixel parameter and the second pixel parameter; and the second difference includes the difference between the first average parameter and the second average parameter.

2. The image correction method according to claim 1, characterized in that, The step of performing correction processing on the image to be corrected according to the image correction coefficient to obtain the corrected target image includes: Based on the image correction coefficient, the third pixel parameter of the pixel in the image to be corrected is corrected to obtain the corrected pixel parameter. The target image is obtained based on the corrected pixel parameters.

3. The image correction method according to claim 2, characterized in that, The step of correcting the third pixel parameter according to the image correction coefficient to obtain the corrected pixel parameter includes: Determine the third difference between the third pixel parameter and the first pixel parameter; The corrected pixel parameters are determined based on the product of the image correction coefficient and the third difference.

4. The image correction method according to claim 2, characterized in that, The step of correcting the third pixel parameter according to the image correction coefficient to obtain the corrected pixel parameter includes: Determine the third difference between the third pixel parameter and the first pixel parameter; Determine the product of the image correction coefficient and the third difference. The corrected pixel parameters are determined based on the sum of the product value and the first average parameter.

5. The image correction method according to claim 2, characterized in that, The step of correcting the third pixel parameter according to the image correction coefficient to obtain the corrected pixel parameter includes: Obtain the fourth pixel parameter, wherein the fourth pixel parameter is determined based on the pixel parameters of the image captured by the ray detector at the third ray intensity; Determine the fourth difference between the third pixel parameter and the fourth pixel parameter; The corrected pixel parameters are determined based on the product of the image correction coefficient and the fourth difference.

6. The image correction method according to any one of claims 1-5, characterized in that, The first image and the second image are images taken by the X-ray detector under no-load conditions, which include situations where there is no target object to be photographed.

7. An image correction device, characterized in that, include: The first acquisition module is used to acquire the image to be corrected; wherein, the image to be corrected includes an image captured by a ray detector; The second acquisition module is used to acquire the preset image correction coefficients of the ray detector; The image correction coefficient is determined based on a first image and a second image pre-captured by the ray detector; the first image and the second image are captured by the ray detector through a first ray intensity and a second ray intensity, respectively; both the first ray intensity and the second ray intensity are not zero; The correction module is used to perform correction processing on the image to be corrected according to the image correction coefficients to obtain the corrected target image; The coefficient determination module is used to obtain the first pixel parameters of the pixels in the first image and the second pixel parameters of the pixels in the second image; Determine a first average parameter of the first pixel parameter, and determine a second average parameter of the second pixel parameter; The image correction coefficient is determined based on the proportional relationship between the first difference and the second difference; wherein the first difference includes the difference between the first pixel parameter and the second pixel parameter; and the second difference includes the difference between the first average parameter and the second average parameter.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps of the image correction method according to any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the image correction method according to any one of claims 1-6.

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