Method and Electronic Device for Eliminating Electromagnetic Interference Noise in Detection Images

Abstract

The present application discloses a method and an electronic device for eliminating electromagnetic interference noise in a detection image. The method includes: acquiring a detection signal of a detector for an astronomical environment; extracting detection values of each pixel point in the overscan region from the detection signal; performing modeling analysis on the detection sequence according to the distribution attribute of the detection sequence in the time domain; performing mathematical modeling on the electromagnetic interference noise to construct an electromagnetic interference model of the electromagnetic interference noise in the time domain; determining values of relevant parameters in the sine function and the Gaussian function in the electromagnetic interference model according to the detection values of each pixel point in the overscan region; and performing denoising processing on the detection values of each pixel point in the photosensitive region based on the electromagnetic interference model to generate a detection image of the astronomical environment. By using the embodiments of the present application, the noise filtering effect can be improved, and the imaging quality of the detection image can be enhanced.

Description

Technical Field

[0001] This application relates to the field of space exploration technologies, and particularly to a method and an electronic device for eliminating electromagnetic interference noise in detection images. Background Art

[0002] When using a detector to detect the surrounding environment, most of the signals returned by the detector are coupled with electromagnetic interference introduced by the detector itself or surrounding devices. Specifically, on the image, it is roughly stripe-shaped noise, forming interference stripes. Affected by these interference stripes, the pixel readings of the detector will change, and the magnitude and period of the influence are determined by the nature of the interference source.

[0003] To eliminate such electromagnetic interference, the main technical means that can be adopted are as follows: using electromagnetic shielding technology to reduce electromagnetic interference, using grounding technology to eliminate electromagnetic interference, using wiring technology to improve electromagnetic interference, using filtering technology to reduce electromagnetic interference, etc. Among them, the common processing method is to perform electromagnetic shielding or circuit grounding on the detector in hardware, which can improve the problem of electromagnetic interference to a certain extent.

[0004] However, in some special cases, the above operations are no longer applicable. The main reasons are as follows:

[0005] First, in practice, it is very difficult to achieve complete electromagnetic shielding in hardware. Especially when the detector needs to operate simultaneously with complex circuits or high-power motor devices, the electromagnetic shielding of the detector becomes poor. This is particularly obvious in astronomical observations. When the detector (such as a CCD detector or a CMOS detector) is working, the motor used to drive the telescope is always in a working state, and the fan used to dissipate heat from the detector is always in a working state, which can all cause the electromagnetic shielding of the detector to become poor;

[0006] Second, in special environments, to achieve effective electromagnetic shielding or grounding operations, the cost and maintenance investment may be very high. For example, when using a detector for astronomical observations in harsh environments such as the North and South Poles, or when using a space imaging satellite equipped with a detector for space exploration, the difficulty of electromagnetic shielding of the detector in hardware is high. Moreover, during long-term operation, the electromagnetic shielding is prone to failure. If it fails, it will have a considerable impact on the imaging process of astronomical observations or space exploration.

[0007] In addition, different from the above hardware-dependent means, there is currently a method for improving the image quality of a detector that can be implemented through software. The general principle is as follows: The detector takes multiple pictures of the target to obtain multiple images (including interference stripes), performs "median stacking" processing on the multiple images, and finally an image (without interference stripes) can be obtained, which can achieve the purpose of removing the noise in the detection image.

[0008] However, the method of median stacking based on multiple images has the following disadvantages:

[0009] First of all, this method requires multiple shots of the same target. Obviously, the method cannot be implemented with only one shot. If the number of shots is too small and the number of images is too small, high-precision processing cannot be achieved, and residual effects will be formed. In the process of astronomical exploration, the shooting time of the detector is long, and multiple shots will also result in a waste of noise time cost;

[0010] Secondly, the method of median stacking essentially requires that the same pixel is not covered by interference signals for most of the time. This requires strict control of the pattern of interference signal appearance to finally obtain an image without interference fringes. In one case, if the positions and intensities of the interference fringes on each of the multiple captured images are fixed, the median stacking method will fail.

[0011] Due to the above defects of the median stacking method, when using this method for environmental detection, it has high requirements for the stability control of the detector and the computing power of the processor, and is prone to residual effects, with low reliability of the detection results and poor practicability. Summary of the Invention

[0012] In view of this, the embodiments of the present application provide a method and an electronic device for eliminating electromagnetic interference noise in a detection image, which can improve the noise filtering effect and enhance the imaging quality of the detection image.

[0013] The embodiments of the present application provide a method for eliminating electromagnetic interference noise in a detection image, including: obtaining a detection signal of a detector for an astronomical environment, where the detection signal includes detection values of each pixel point in the overscan region and detection values of each pixel point in the photosensitive region; extracting the detection values of each pixel point in the overscan region from the detection signal, and generating a detection sequence of electromagnetic interference noise according to the time-domain output order of the detection values; performing modeling analysis on the detection sequence according to the distribution attributes of the detection sequence in the time domain to determine that the electromagnetic interference noise in the detection environment includes two parts: a sine distribution and a Gaussian distribution in the time domain; performing a mathematical modeling on the electromagnetic interference noise to construct an electromagnetic interference model of the electromagnetic interference noise in the time domain, where the electromagnetic interference model includes a sine function and a Gaussian function; determining the values of relevant parameters in the sine function and the Gaussian function in the electromagnetic interference model according to the detection values of each pixel point in the overscan region; and performing denoising processing on the detection values of each pixel point in the photosensitive region based on the electromagnetic interference model to generate a detection image of the astronomical environment.

[0014] Optionally, according to the method of the embodiments of the present application, the detector includes at least one of the following: a detector installed in an astronomical telescope, a detector carried on a space imaging satellite, a detector used in a harsh environment, a CCD detector, and a CMOS detector.

[0015] Optionally, according to the method of the embodiments of the present application, before mathematically modeling the electromagnetic interference noise, the method further includes: decomposing the detection sequence to obtain one or more pulse signal chains, where different pulse signal chains have different frequencies and amplitudes.

[0016] Optionally, according to the method of the embodiments of the present application, the method further includes: obtaining interference characteristic information corresponding to one or more hardware devices in the detection environment where the detector is located; matching the one or more pulse signal chains obtained by the decomposition process with the interference characteristic information corresponding to the one or more hardware devices, and determining the hardware device with a successful match as the interference source of the detector.

[0017] Optionally, according to the method of the embodiments of the present application, the electromagnetic interference model of the electromagnetic interference noise in the time domain adopts the following form:

[0018]

[0019] where t is the output order of the detection value, I(t) is the noise interference value corresponding to the t-th detection value, I0 is the interference value of the background noise in the detection environment, the subscript i represents the i-th pulse signal chain, N is a positive integer, A i is the amplitude of the i-th pulse signal chain, ω i and α i are respectively the frequency and phase of the sine part in the i-th pulse signal chain, σ i and β i are respectively the width and displacement of the Gaussian part in the i-th pulse signal chain.

[0020] Optionally, according to the method of the embodiments of the present application, modeling and analyzing the detection sequence according to the distribution attributes of the detection sequence in the time domain includes: decomposing the detection sequence to obtain one or more pulse signal chains, where different pulse signal chains have different frequencies and amplitudes; performing modeling and analysis on each decomposed pulse signal chain, where part or all of the pulse signals are respectively made to include a sine part and a Gaussian part to construct a fitting function for each pulse signal chain; constructing a mathematical model of the detection sequence based on the fitting functions of each pulse signal chain; and determining that the mathematical model of the detection sequence matches the distribution attributes of the detection sequence.

[0021] Optionally, according to the method of the embodiments of the present application, the fitting function of a single pulse signal chain adopts the following form:

[0022]

[0023] Among them, the subscript i represents the i-th pulse signal chain, t is the output order of the detection value, Ii(t) is the interference value of the i-th electromagnetic interference on the t-th output, A i is the amplitude of the i-th pulse signal chain, ω i and α i are respectively the frequency and phase of the sine part in the i-th pulse signal chain, σ i and β i are respectively the width and displacement of the Gaussian part in the i-th pulse signal chain.

[0024] An embodiment of the present application provides an electronic device, which includes a processor and a memory storing computer program instructions; when the processor executes the computer program instructions, the steps of the above method are implemented.

[0025] An embodiment of the present application provides a computer-readable storage medium, on which computer program instructions are stored. When the computer program instructions are executed by a processor, the steps of the above-mentioned method are implemented.

[0026] An embodiment of the present application provides a computer program product, which includes computer program instructions. When the computer program instructions are executed by a processor, the steps of the above-mentioned method are implemented.

[0027] By adopting the embodiment of the present application, by obtaining the detection values of each pixel point in the overscan area of the detector, and then generating a detection sequence of electromagnetic interference noise according to the time-domain output order of the detection values. After that, the detection sequence is modeled and analyzed according to the distribution attributes of the detection sequence in the time domain. After determining that the electromagnetic interference noise in the detection environment includes two parts, namely, a sine distribution and a Gaussian distribution in the time domain, by constructing an electromagnetic interference model including a sine function and a Gaussian function, and combining the detection values of each pixel point in the overscan area, the values of the relevant parameters in the sine function and the Gaussian function in the electromagnetic interference model are determined, and an electromagnetic interference model including specific parameters is obtained. Based on this electromagnetic interference model, the actual fluctuation of the electromagnetic interference noise can be accurately represented, so as to accurately determine the interference value of the electromagnetic interference corresponding to each pixel point in the photosensitive area during the denoising process. After denoising, a clear detection image of the astronomical environment can be generated. In the embodiment of the present application, for the denoising task of the detection image, it is not necessary for the detector to take multiple shots, nor is it necessary to add additional hardware shielding devices, which effectively reduces the denoising cost. Moreover, since the detection values in the overscan area are sufficient in quantity, even for a single-shot task, the electromagnetic interference model has sufficient accuracy to ensure the filtering effect of the electromagnetic interference noise and improve the imaging quality of the detection image, providing a clearer and more accurate image basis for subsequent analysis of astronomical data. Brief Description of the Drawings

[0028] To more clearly illustrate the technical solutions of the embodiments of the present application, the following briefly introduces the drawings in the embodiments of the present application.

[0029] Figure 1 It is a flowchart of the method for eliminating electromagnetic interference noise in a detection image according to an embodiment of the present application.

[0030] Figure 2 A schematic diagram of interference noise provided by an embodiment of the present application.

[0031] Figure 3 It is a schematic diagram of the denoising effect of a detection image provided by an embodiment of the present application.

[0032] Figure 4 It is a schematic diagram of a pulse signal chain provided by an embodiment of the present application.

[0033] Figure 5 It is a schematic diagram of an electronic device for implementing the method for eliminating electromagnetic interference noise in a detection image according to an embodiment of the present application. Detailed Embodiments

[0034] The following will describe the principles and spirit of the present application with reference to several exemplary embodiments. It should be understood that the purpose of providing these embodiments is to make the principles and spirit of the present application clearer and more thorough, so that those skilled in the art can better understand and then implement the principles and spirit of the present application. The exemplary embodiments provided herein are only a part of the embodiments of the present application, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments herein without creative efforts fall within the scope of protection of the present application.

[0035] It should be noted that the acquisition, storage, use, processing, etc. of data in the embodiments of the present application all comply with the relevant regulations of national laws and regulations.

[0036] In this document, terms such as first, second, third, etc. are only used to distinguish one entity (or operation) from another entity (or operation), rather than requiring or implying any order or association between these entities (or operations).

[0037] The embodiments of the present application relate to terminal devices and / or servers. Those skilled in the art know that the embodiments of the present application can be implemented as a system, device, equipment, method, computer-readable storage medium, or computer program product. Therefore, the present disclosure can be specifically implemented in at least one of the following forms: complete hardware, complete software, or a combination of hardware and software.

[0038] As the exploration space of people becomes wider and wider, the application environments for collecting image data through detectors are also increasing. A detector can capture light in the environment and convert the light in the environment into an electrical signal. Then, a detection image can be generated in combination with the electrical signal. Commonly used detectors include, for example, Charge-Coupled Device (CCD) detectors, Complementary Metal-Oxide-Semiconductor (CMOS) detectors, etc., which will not be listed one by one here.

[0039] In the related art, the working environment of the detector is vulnerable to electromagnetic interference from the surrounding circuits, resulting in striped noise in the detection image generated based on the electrical signal output by the detector. Since these surrounding circuits include circuits shared with the detector or circuits of other necessary electronic devices, it is difficult to completely cut off the interference source to avoid generating noise. Although in the related art, improvement methods have been proposed respectively from the aspects of hardware or software to reduce the striped noise in the detection image, the current improvement methods all have the problems of high denoising cost and poor denoising effect.

[0040] Based on this, the embodiments of the present application provide a method, device and electronic device for eliminating electromagnetic interference noise in a detection image. By obtaining the detection values of each pixel point in the overscan region of the detector and the time-domain output order of the detection values, a suitable electromagnetic interference model is constructed, and accurate model parameters are determined, so as to accurately represent the actual fluctuation of the electromagnetic interference noise through the electromagnetic interference model. Furthermore, in the process of denoising, the interference value of the electromagnetic interference corresponding to each pixel point in the photosensitive region can be accurately determined. After denoising, a clear detection image of the astronomical environment can be generated, providing clearer and more accurate image data for subsequent analysis of astronomical data.

[0041] The following introduces the method for eliminating electromagnetic interference noise in a detection image provided by the embodiments of the present application with reference to the accompanying drawings. Figure 1 It is a flowchart of a method for eliminating electromagnetic interference noise in a detection image provided by some embodiments of the present application. Combining Figure 1 As shown, the method includes the following steps 101 to 106.

[0042] Step 101, obtain the detection signal of the detector for the astronomical environment, where the detection signal includes the detection values of each pixel point in the overscan region and the detection values of each pixel point in the photosensitive region.

[0043] Step 102, extract the detection values of each pixel point in the overscan region from the detection signal, and generate a detection sequence of electromagnetic interference noise according to the time-domain output order of the detection values.

[0044] Step 103: Model and analyze the detection sequence based on its distribution attributes in the time domain to determine that the electromagnetic interference noise in the detection environment includes two parts in the time domain: a sine distribution and a Gaussian distribution.

[0045] Step 104: Mathematically model the electromagnetic interference noise to construct an electromagnetic interference model in the time domain for the electromagnetic interference noise. The electromagnetic interference model includes a sine function and a Gaussian function.

[0046] Step 105: Determine the values of the relevant parameters in the sine function and the Gaussian function in the electromagnetic interference model based on the detection values of each pixel point in the overscan region.

[0047] Step 106: Based on the electromagnetic interference model, perform denoising processing on the detection values of each pixel point in the photosensitive region to generate a detection image of the astronomical environment.

[0048] The above steps will be described in detail below in conjunction with specific embodiments.

[0049] Specifically, regarding Step 101, the detection signals of the astronomical environment include the detection values of each pixel point in the overscan region and the detection values of each pixel point in the photosensitive region.

[0050] Exemplarily, the detector includes at least one of the following: a detector installed in an astronomical telescope, a detector carried on a space imaging satellite, a detector used in a harsh environment, a CCD detector, and a CMOS detector. Among them, in a harsh environment such as the surface environment of ice at high cold and high altitude, specifically, for example, a telescope array established at the Antarctic astronomical observatory.

[0051] The detector includes an overscan region and a photosensitive region. Optionally, in the detector, the overscan region can be located around the photosensitive region. For example, at the start or end of each row of pixel points, the overscan region can also be located at other photosensitive positions, and no specific limitation is made here.

[0052] When the detector is performing a detection task, the pixel points in the photosensitive region can receive environmental light. The light collected by each pixel point is converted into an electrical signal. After the corresponding output value of the electrical signal is output, the detection value of the pixel point in the photosensitive region is obtained. Based on this detection value, a detection image can be generated. Among them, the detection image can include the imaging of astronomical data, and the astronomical data includes but is not limited to celestial bodies such as stars and galaxies or other objects that can be photographed by the detector.

[0053] The overscan region in the detector is the area not exposed to light. The detection values of each pixel in the overscan region are affected by the noise in the environment where the detector is located. In other words, the detection values of each pixel in the overscan region are generated based on the noise in the environment where the detector is located, such as the background noise and the electromagnetic interference noise received by the readout channel during output.

[0054] It can be understood that the detection values of each pixel in the photosensitive region are also affected by the noise in the environment where the detector is located. Therefore, there will be noise in the detection image directly generated based on the detection values of each pixel in the photosensitive region. Exemplarily, electromagnetic interference sources in the detection environment, such as periodic working electronic devices like motors or AC circuits, are prone to electromagnetic leakage. Therefore, when the detector outputs signals through the readout channel, the output signals corresponding to each pixel in the photosensitive region and the overscan region will be affected.

[0055] As a specific example, when a CCD detector used in a telescope takes images, in the readout channel of the CCD detector, an interference pattern of straight stripes and inclined stripes can be clearly observed. Among them, stripe noise as shown in Figure 2 is formed on the local image. The pixel brightness affected by the interference stripes will increase or decrease by about 20 - 50 ADU.

[0056] In some embodiments, the readout period of the detector's readout channel and the interference period of the electromagnetic interference source will affect the display position of the interference noise on the image. Therefore, the stripe - shaped noise formed on the detection image may be inclined stripe - shaped noise, vertical stripe - shaped noise, or discontinuous stripe noise. The display forms of the noise are not listed one by one here.

[0057] Next, it involves step 102. For extracting the detection values of each pixel in the overscan region from the detection signal, an electromagnetic interference noise detection sequence is generated according to the time - domain output order of the detection values.

[0058] Specifically, each detector may correspond to one or more readout channels, and each readout channel sequentially outputs the corresponding electrical signals of each pixel based on the arrangement order of the pixels. For example, the readout channel of the detector sequentially outputs along the row direction of the pixels, or the signal readout channel sequentially outputs along the column direction of the pixels.

[0059] In some alternative embodiments, the output manner of sequentially outputting along the row direction of pixels is consistent with the horizontal scan of pixel arrangement, which can improve the readout efficiency and facilitate improving the speed of image processing as a whole. The output manner of sequentially outputting along the column direction of pixels can be applicable to data acquisition scenarios with vertical priority. For example, some detectors can be astronomical spectrometers or remote sensing devices in specific modes. In the embodiments of the present application, the required output manner can be selected according to the actual application scenario.

[0060] In some embodiments, the detector can output the detection values of each pixel point in the overscan area and the detection values of each pixel point in the photosensitive area through one readout channel. Thus, each detection value corresponds to a time-domain output order, and the detection values of different pixel points correspond to different time-domain output orders. Thereby, a two-dimensional array is converted into a one-dimensional array.

[0061] Optionally, if the detection signals output the detection values through multiple readout channels, for each readout channel, a one-dimensional array is generated; thus, one-dimensional arrays corresponding to the multiple readout channels are obtained. Subsequently, any one of the one-dimensional arrays can be selected for analysis, an electromagnetic interference model is constructed, and the relevant parameters of the model are determined.

[0062] In some embodiments, a one-dimensional array can include the detection values of each pixel point in the overscan area and the detection values of each pixel point in the photosensitive area. By combining the positions of each pixel point in the overscan area and the positions of each pixel point in the photosensitive area, the detection values corresponding to each pixel point in the overscan area are extracted from the array, so as to obtain the detection sequence of electromagnetic interference noise.

[0063] In the detection sequence of electromagnetic interference noise arranged based on the time-domain output order, the interference information in the environment where the detector is located is included. Therefore, by analyzing the detection sequence of electromagnetic interference noise, an electromagnetic interference model can be accurately constructed. Among them, the distribution attributes of the detection sequence in the time domain, such as the periodic distribution of the frequency of pulse occurrence, etc., and the attenuation of the pulse amplitude, etc.

[0064] Specifically, it relates to step 103 and step 104. The detection sequence is modeled and analyzed according to the distribution attributes of the detection sequence in the time domain to determine that the electromagnetic interference noise in the detection environment includes two parts: a sine distribution and a Gaussian distribution in the time domain. Furthermore, a mathematical model of the electromagnetic interference noise is established to construct an electromagnetic interference model including a sine function and a Gaussian function, that is, the electromagnetic interference model of the electromagnetic interference noise in the time domain. In the electromagnetic interference model, the operation relationship between the sine part and the Gaussian part is a multiplication relationship.

[0065] As a specific example, the operation relationship between the sine part and the Gaussian part in the electromagnetic interference model can be expressed as: , the sine function part is: ; the Gaussian function part is: .

[0066] Based on the electromagnetic interference model constructed according to the embodiments of the present application, the sine function in the electromagnetic interference model can be used to characterize some periodic features in the interference information. For example, it can be used to represent the periodic interference noise caused by the electronic devices working in the detection environment. The Gaussian function in the electromagnetic interference model can control the sine wave corresponding to the sine function to fluctuate within the envelope range corresponding to the Gaussian function term. In this way, the amplitude change range of the sine wave can be controlled within the envelope corresponding to the Gaussian function term. After determining the specific parameters, the fluctuation of the electromagnetic interference noise can be accurately represented.

[0067] After determining the electromagnetic interference model, the following step 105 is involved, that is, according to the detection values of each pixel point in the overscan region, determine the values of the relevant parameters in the sine function and the Gaussian function in the electromagnetic interference model.

[0068] Exemplarily, the parameters related to the sine function, such as pulse amplitude, frequency, phase, etc. Among them, the amplitude can represent the interference intensity of the interference source, and the frequency can represent the interference interval. The parameters related to the Gaussian function, such as the width and displacement of the Gaussian part. Among them, the width of the Gaussian part can also be called the pulse expansion degree.

[0069] When calculating the parameter values, fitting can be performed according to the time-domain output order of the detection values in the detection sequence of the electromagnetic interference noise and the magnitudes of the detection values, so as to determine the values of the relevant parameters in the sine function and the Gaussian function. Among them, the fitting processing methods include, but are not limited to, optimization algorithms such as the least squares method. Through the fitting processing, the values of the relevant parameters can be adjusted to the optimal values, so that they can accurately represent the one-dimensional corresponding fluctuation of the electromagnetic interference noise, which is beneficial to accurately removing the noise in the image subsequently.

[0070] In some embodiments, the detection values of each pixel point in the overscan region are values generated based on the noise in the environment where the detector is located. The noise in the environment where the detector is located also includes the background noise. Since the background noise is relatively stable and smooth, the detection value corresponding to the background noise is usually a constant I0. Optionally, the determination method of the background noise, for example, select the detection values with a relatively stable fluctuation range, and determine the interference value of the background noise by calculating the mean value or the standard deviation. In the embodiments of the present application, the acquisition method of the interference value of the background noise is not specifically limited.

[0071] Optionally, before determining the values of the relevant parameters in the sine function and the Gaussian function, the detected values corresponding to the background noise in the detection sequence of the electromagnetic interference noise can be removed first, and then, based on the detection sequence after removing the background noise, the parameter values of the relevant parameters in the sine function and the Gaussian function can be determined.

[0072] Exemplarily, the detection sequence of the electromagnetic interference noise without removing the background noise is, for example, {I0, I0, X1, X2, X3, I0, X4, X5, I0, I0, I0}, and the detection sequence after removing the background noise is, for example, {0, 0, X1 - I0, X2 - I0, X3 - I0, 0, X4 - I0, X5 - I0, 0, 0, 0}.

[0073] The electromagnetic interference model includes at least a sine function part and a Gaussian function part. After determining the values of the relevant parameters in the sine function and the Gaussian function in the electromagnetic interference model, next, referring to step 106, the detected values of each pixel point in the photosensitive area can be denoised to remove the interference stripes in the image, and the detected values after the denoising process can be used to generate a clear detection image.

[0074] Specifically, by inputting the time-domain output order corresponding to each pixel point in the photosensitive area into the electromagnetic interference model, the electromagnetic interference value corresponding to each pixel point in each photosensitive area can be determined through the electromagnetic interference model. Based on the electromagnetic interference value corresponding to each pixel point in the photosensitive area, the detected values corresponding to each pixel point in the photosensitive area can be denoised to remove the interference stripes in the detection image. For example, Figure 3 is a schematic diagram of the denoising effect of a group of detection images provided by an embodiment of the present application, the photosensitive area image Figure 3 (a), after the denoising process, the detection image obtained is as Figure 3 (b) shown.

[0075] According to the embodiment of the present application, for the denoising task of the detection image, it is not necessary for the detector to take multiple shots, nor is it necessary to add additional hardware shielding devices, effectively reducing the denoising cost. Moreover, since the detected values in the overscan area are sufficient in number, even for a single-shot task, the electromagnetic interference model has sufficient accuracy to ensure the filtering effect of the electromagnetic interference noise, which is beneficial to improving the imaging quality of the detection image and providing a clearer and more accurate image basis for subsequent analysis of astronomical data.

[0076] Compared with traditional denoising methods that require taking multiple images and then using median stacking to remove interference fringes, and which also require the positions and intensities of the interference fringes in each image to be fixed, once the interference sources in the detection environment change, such as the interference frequency changes, the positions of the same interference signal in each image will also change, resulting in poor denoising effects when using median stacking to remove interference fringes. However, the denoising method provided based on the embodiments of the present application can not only be applied separately to each detection image, but also accurately locate the interference value corresponding to each pixel even when the position of the same interference signal in the image changes, achieving precise denoising of the original detection image.

[0077] In some alternative embodiments, the electromagnetic interference model may also include a constant part for representing the corresponding detection value of the background noise in the detection environment.

[0078] As a specific example, the electromagnetic interference model of electromagnetic interference noise in the time domain can adopt the following form:

[0079] (1)

[0080] where t is the output order of the detection value, I(t) is the noise interference value corresponding to the t-th detection value, I0 is the interference value of the background noise in the detection environment, the subscript i represents the i-th pulse signal chain, N is a positive integer, A i is the amplitude of the i-th pulse signal chain, ω i and α i are respectively the frequency and phase of the sine part in the i-th pulse signal chain, σ i and β i are respectively the width and displacement of the Gaussian part in the i-th pulse signal chain.

[0081] Based on the three parts of the constant, sine distribution, and Gaussian distribution, not only can the interference noise caused by electromagnetic interference sources and other devices be removed, but also the background noise can be removed, further eliminating the random noise and system bias inside, achieving a more comprehensive removal of the noise in the detection image and improving the imaging quality of the detection image.

[0082] In some embodiments, the sources of electromagnetic interference in the detection environment are periodic working electronic devices such as motors or AC circuits. Therefore, there may be multiple electronic devices in the detection environment interfering with the detector noise. Before mathematically modeling the electromagnetic interference noise, the detection sequence can be decomposed to obtain one or more pulse signal chains with different frequencies and amplitudes. A fitting function can be established separately for each pulse signal chain, and then based on the fitting functions of each pulse signal chain, a mathematical model of the detection sequence can be constructed.

[0083] Exemplarily, taking the case where there are two interference sources in the detection environment as an example, the detection sequence is {I0, X, I0, Y, I0, X, I0, Y, I0}, where X corresponds to one interference source and includes multiple detection values, Y corresponds to the other interference source and includes multiple detection values, and I0 is the noise value corresponding to the background noise. By decomposing and processing the detection sequence, two pulse signal chains can be obtained, which are {I0, X, I0, I0, I0, X, I0, I0, I0} and {I0, I0, I0, Y, I0, I0, I0, Y, I0} respectively. The two pulse signal chains respectively correspond to a frequency and an amplitude.

[0084] In some embodiments, since there are a large number of electronic devices in the detection environment, it is not convenient to locate which specific device causes interference. Optionally, interference characteristic information corresponding to one or more hardware devices in the detection environment where the detector is located can be obtained; one or more pulse signal chains obtained by decomposition processing are matched with the interference characteristic information corresponding to one or more hardware devices, and the hardware device with successful matching is determined as the interference source of the detector.

[0085] Specifically, the hardware device is an electronic device that operates periodically, such as a motor or an AC circuit. The interference characteristic information of the hardware device, for example, the power supply frequency of an AC motor, etc. For each pulse signal chain obtained by decomposition processing, the periodic information corresponding to the pulse signal chain is extracted, such as pulse amplitude, frequency, phase, etc. Based on the matching of the periodic information corresponding to the pulse signal chain with the interference characteristic information of the hardware device, it is possible to identify which specific devices cause interference to the readout channel of the detector. For example, if the power supply frequency of the AC motor is consistent with the pulse signal chain and the AC motor, it can be considered that the AC motor matches the pulse signal chain and the AC motor causes interference to the readout channel of the detector.

[0086] In one example, the matching result can also help to troubleshoot potential hardware failures. For example, each pulse signal chain matches a hardware device in the detection environment, but there are still hardware devices in the detection environment that do not match successfully. Based on this, it can be checked whether the hardware device that does not match successfully fails to ensure the smooth progress of the entire detection task.

[0087] As a specific example, after fitting the detection sequence, it is determined that the main frequency of the electromagnetic interference is 15.89 kHz. Based on the method provided in the embodiments of the present application, the frequencies of each interference source can be accurately found. Through further analysis, it is determined that the electromagnetic interference noise is actually caused by the superposition effect of four interference sources. These interference sources not only have different amplitudes, but the frequency difference between different interference sources is even only 0.1 Hz. Since the ceramic resonator is at this level, while the crystal oscillator has higher precision and the RC oscillator is far inferior, this tiny frequency difference indicates that the interference source may use a ceramic resonator. Further, interference localization can be performed based on the ceramic resonator. For example, the device associated with the ceramic resonator can be found. In this example, it is speculated that the interference source comes from the four power supply systems of the equatorial mounting drive motor. After the engineer further checks the power supply system, it is determined that there is a fault in the grounding wire break of the motor drive system. Thus, the fault can be repaired in time to ensure the smooth progress of the detection.

[0088] In some embodiments of the present application, in order to further improve the accuracy of the values of the relevant parameters in the sine function and the Gaussian function in the electromagnetic interference model, in the step of constructing the electromagnetic interference model, the mathematical model corresponding to each pulse signal chain can be established first, that is, the fitting function of the pulse signal chain. Specifically, the detection sequence is modeled and analyzed according to the distribution attributes of the detection sequence in the time domain, including: decomposing the detection sequence to obtain one or more pulse signal chains, where different pulse signal chains have different frequencies and amplitudes; performing modeling and analysis on each decomposed pulse signal chain, where some or all of the pulse signals are respectively made to include a sine part and a Gaussian part to construct the fitting function of each pulse signal chain; constructing the mathematical model of the detection sequence based on the fitting functions of each pulse signal chain; and determining that the mathematical model of the detection sequence matches the distribution attributes of the detection sequence.

[0089] Exemplarily, the fitting function of a single pulse signal chain adopts the following form:

[0090] (2)

[0091] where the subscript i represents the i-th pulse signal chain, t is the output order of the detection value, Ii(t) is the interference value of the i-th electromagnetic interference to the background noise in the t-th output, A i is the amplitude of the i-th pulse signal chain, ω i and α i are respectively the frequency and phase of the sine part in the i-th pulse signal chain, σ i and β i are respectively the width and displacement of the Gaussian part in the i-th pulse signal chain.

[0092] Exemplarily, Figure 4It is a schematic diagram of a pulse signal chain provided by an embodiment of the present application. Figure 4 Three different pulse signal chains are shown, where the three pulse signal chains have different amplitudes, intervals, and frequencies. For each pulse signal chain, by separately establishing a fitting function to represent its fluctuations, various different interference sources in the detection environment can be more flexibly dealt with. Then, a summation operation relationship is established between the fitting sub-functions to determine the electromagnetic interference model, so that the interference situation of the entire detection environment can be more accurately represented, which is beneficial to improving the accuracy of determining the interference value corresponding to each pixel point in the photosensitive area subsequently.

[0093] In some embodiments, in the step of denoising the detection values of each pixel point in the photosensitive area based on the electromagnetic interference model and generating a detection image of the astronomical environment, the interference value corresponding to each pixel point in the photosensitive area and the detection value of each pixel point in the photosensitive area can be first converted into pixel values, and then the pixel value corresponding to the detection value is subtracted from the pixel value corresponding to the interference value to obtain the target pixel value. The detection image composed of the target pixel values is the detection image after denoising processing.

[0094] Optionally, during the denoising process, the detection value of each pixel point can also be directly subtracted from the interference value corresponding to each pixel point to obtain the target detection value, and then the target detection value is converted into the target pixel value, and then the detection image composed of the target pixel values is the detection image after denoising processing.

[0095] The detection image processed according to the embodiment of the present application can accurately remove the interference noise in the photosensitive area image and also precisely retain the image information of the astronomical target.

[0096] Corresponding to the method embodiment of the present application, an embodiment of the present application also provides a device for eliminating electromagnetic interference noise in a detection image, including a data acquisition module and a data processing module. Among them, the data acquisition module is used to acquire the detection signal of the detector for the astronomical environment, and the data processing module is used to process the detection signal according to the method for eliminating electromagnetic interference noise in the detection image provided by the embodiment of the present application to generate a clear detection image.

[0097] It can be understood that the device for eliminating electromagnetic interference noise in the detection image according to the embodiment of the present application can correspond to the execution subject of the method for eliminating electromagnetic interference noise in the detection image provided by the embodiment of the present application. The specific details of the operations and / or functions of each module / unit of the device for eliminating electromagnetic interference noise in the detection image can refer to the corresponding parts of the method for eliminating electromagnetic interference noise in the detection image provided by the above embodiment of the present application. For the sake of brevity, it will not be elaborated here.

[0098] The electronic device in the embodiments of the present application can be a user terminal device, a server, or other computing devices, or a cloud server. Figure 5 The figure shows a schematic hardware structure of the electronic device according to the embodiments of the present application. The electronic device may include a processor 501 and a memory 502 storing computer program instructions. When the processor 501 executes the computer program instructions, the processes or functions of the methods in any of the above embodiments are implemented.

[0099] Specifically, the processor 501 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application. The memory 502 may include a mass storage for data or instructions. For example, the memory 502 may be at least one of the following: a hard disk drive (HDD), a read-only memory (ROM), a random access memory (RAM), a floppy disk drive, a flash memory, an optical disc, a magneto-optical disc, a magnetic tape, a universal serial bus (USB) drive, or other physical / tangible memory storage devices. Also, the memory 502 may include removable or non-removable (or fixed) media. Additionally, the memory 502 may be inside or outside the integrated gateway disaster recovery device. The memory 502 may be a non-volatile solid-state memory. In other words, generally, the memory 502 includes a tangible (non-transitory) computer-readable storage medium (such as a memory device) encoded with computer-executable instructions, and when the software is executed (such as by one or more processors), the operations described in the methods of the embodiments of the present application can be performed. The processor 501 realizes the processes or functions of any of the above methods by reading and executing the computer program instructions stored in the memory 502.

[0100] In one example, Figure 5The electronic device shown may further include a communication interface 503 and a bus 510. Among them, the processor 501, the memory 502, and the communication interface 503 are connected through the bus 510 to complete communication with each other. The communication interface 503 is mainly used to implement communication between various modules, devices, units, and / or devices in the embodiments of the present application. The bus 510 includes hardware, software, or both, and can couple the components of the online data flow charging device to each other. For example, the bus may include at least one of the following: Accelerated Graphics Port (AGP) or other graphics buses, Extended Industry Standard Architecture (EISA) bus, Front Side Bus (FSB), HyperTransport (HT) interconnect, Industry Standard Architecture (ISA) bus, InfiniBand interconnect, Low Pin Count (LPC) bus, Memory bus, MicroChannel Architecture (MCA) bus, Peripheral Component Interconnect (PCI) bus, PCI-Express (PCI-X) bus, Serial Advanced Technology Attachment (SATA) bus, Video Electronics Standards Association Local (VLB) bus, or other suitable buses. The bus 510 may include one or more buses. Although the embodiments of the present application describe or illustrate specific buses, the embodiments of the present application may consider any suitable bus or interconnect method.

[0101] Combined with the method in the above embodiments, the embodiments of the present application further provide a computer-readable storage medium, on which computer program instructions are stored. When the computer program instructions are executed by a processor, the processes or functions of any one of the methods in the above embodiments are implemented.

[0102] In addition, the embodiments of the present application further provide a computer program product, on which computer program instructions are stored. When the computer program instructions are executed by a processor, the processes or functions of any one of the methods in the above embodiments are implemented.

[0103] The flowcharts and / or block diagrams of the methods, devices, systems, and computer program products in the embodiments of the present application have been described above by way of example, and the relevant aspects have been described. It should be understood that each box or combination of boxes in the flowchart and / or block diagram can be implemented by computer program instructions, can also be implemented by dedicated hardware that performs a specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions. For example, these computer program instructions can be provided to the processor of a general-purpose computer, a dedicated computer, or other programmable data processing devices to form a machine, so that these instructions executed by such a processor enable the implementation of the specified functions / actions in each box or combination of boxes in the flowchart and / or block diagram. Such a processor can be a general-purpose processor, a dedicated processor, a special application processor, or a field programmable logic circuit.

[0104] The functional blocks shown in the structural block diagrams of the embodiments of the present application can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), appropriate firmware, a plug-in, a functional card, etc.; when implemented in software, it is a program or a code segment for performing the required tasks. The program or code segment can be stored in a memory or transmitted via a data signal carried in a carrier wave on a transmission medium or a communication link. The code segment can be downloaded via a computer network such as the Internet, an intranet, etc.

[0105] It should be noted that the present application is not limited to the specific configurations and processes described above or shown in the figures. The above are only specific embodiments of the present application. Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the described system, device, module, or unit can refer to the corresponding processes in the method embodiments and will not be repeated here. It should be understood that the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can think of various equivalent modifications or substitutions, and these modifications or substitutions should all be covered within the protection scope of the present application.

Claims

1. A method for eliminating electromagnetic interference noise in a detection image, characterized in that: include: Acquire a detection signal of the detector to the astronomical environment, wherein the detection signal includes a detection value of each pixel point in the overscan area and a detection value of each pixel point in the photosensitive area; Extracting the detection value of each pixel point in the overscan area from the detection signal, and generating a detection sequence of electromagnetic interference noise according to the time domain output order of the detection value; Modeling and analyzing the detection sequence according to the distribution properties of the detection sequence in the time domain to determine the two parts of the sine distribution and the Gaussian distribution contained in the electromagnetic interference noise in the detection environment in the time domain; Mathematically modeling the electromagnetic interference noise to construct an electromagnetic interference model of the electromagnetic interference noise in the time domain, wherein the electromagnetic interference model includes a sine function and a Gaussian function; Determining values ​​of relevant parameters in the sine function and the Gaussian function in the electromagnetic interference model according to the detection values ​​of each pixel point in the overscan area; Based on the electromagnetic interference model, the detection value of each pixel point in the photosensitive area is denoised to generate a detection image of the astronomical environment.

2. The method according to claim 1, characterized in that The detector includes at least one of the following: a detector installed in an astronomical telescope, a detector carried in a space imaging satellite, a detector used in a harsh environment, a CCD detector, and a CMOS detector.

3. The method according to claim 1, characterized in that Before mathematically modeling the electromagnetic interference noise, the method further includes: The detection sequence is decomposed to obtain one or more pulse signal chains, and different pulse signal chains have different frequencies and amplitudes.

4. The method according to claim 3, characterized in that The method further comprises: Obtain interference characteristic information corresponding to one or more hardware devices in the detection environment where the detector is located; The one or more pulse signal chains obtained by the decomposition process are matched with the interference characteristic information corresponding to the one or more hardware devices, and the hardware devices with successful matching are determined as interference sources of the detector.

5. The method according to claim 3, characterized in that: The electromagnetic interference model of the electromagnetic interference noise in the time domain is in the following form: Where t is the output order of the detection value, I(t) is the noise interference value corresponding to the t-th detection value, I0 is the interference value of the background noise in the detection environment, the subscript i represents the i-th pulse signal chain, N is a positive integer, and A i is the amplitude of the ith pulse signal chain, ω i and α i are the frequency and phase of the sinusoidal part in the i-th pulse signal chain, σ i and β i are the width and displacement of the Gaussian part in the i-th pulse signal chain, respectively.

6. The method according to claim 1, characterized in that The modeling and analyzing the detection sequence according to the distribution property of the detection sequence in the time domain includes: Decomposing the detection sequence to obtain one or more pulse signal chains, wherein different pulse signal chains have different frequencies and amplitudes; Modeling and analyzing each pulse signal chain obtained by decomposition, wherein part or all of the pulse signals are respectively made to include a sinusoidal part and a Gaussian part, so as to construct a fitting function of each pulse signal chain; Constructing a mathematical model of the detection sequence based on the fitting functions of each pulse signal chain; A mathematical model of the detection sequence is determined to match a distribution property of the detection sequence.

7. The method according to claim 6, characterized in that The fit function for a single pulse signal chain takes the following form: Where, the subscript i represents the i-th pulse signal chain, t is the output order of the detection value, Ii(t) is the interference value of the i-th electromagnetic interference on the t-th output, and A i is the amplitude of the ith pulse signal chain, ω i and α i are the frequency and phase of the sinusoidal part in the i-th pulse signal chain, σ i and β i are the width and displacement of the Gaussian part in the i-th pulse signal chain, respectively.

8. An electronic device, characterized in that: The electronic device comprises: a processor and a memory storing computer program instructions; when the electronic device executes the computer program instructions, the method according to any one of claims 1 to 7 is implemented.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer program instructions, and when the computer program instructions are executed by a processor, the method according to any one of claims 1 to 7 is implemented.

10. A computer program product, characterized in that, It comprises computer program instructions, which, when executed by a processor, implement the method according to any one of claims 1 to 7.

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