Infrared Image Acquisition Control Method, Device, System, and Storage Medium

Abstract

The present application provides an infrared image acquisition control method, device, equipment, system and storage medium, the method comprising: obtaining sensor data representing the current weather conditions collected by a set sensor, and determining a first weather type in the current environment of a target field of view based on the sensor data; obtaining an original infrared image collected by an infrared module in real time for the target field of view; performing image quality analysis on the original infrared image based on a detail layer of the original infrared image; and / or determining a second weather type in the current environment of the target field of view based on the image quality analysis result; performing image recognition on the original infrared image through an image weather recognition model to identify a third weather type in the current environment of the target field of view; determining the current weather type based on the first weather type, as well as the second weather type and / or the third weather type, and controlling the infrared module to start an image enhancement processing mode when the current weather type is severe weather.

Description

Technical Field

[0001] The present application relates to the field of image processing, and in particular to an infrared image acquisition control method, device, system and storage medium. Background Art

[0002] With advances in infrared technology, infrared devices are becoming increasingly common in various fields. In severe weather conditions such as heavy rain, snow, and dust storms, the limitations of visible light are particularly pronounced, potentially affecting the user's field of vision and leading to unexpected situations. For example, drivers' vision is impaired by rain and snow, leading to a sharp increase in the probability of traffic accidents. The advent of infrared modules can compensate for these limitations in visible light, providing users with a clearer field of vision and preventing accidents.

[0003] However, infrared image quality varies in different weather conditions, leading to varying degrees of visual clarity. For example, in inclement weather, infrared image quality degrades, severely impacting the user's field of view. In normal weather, infrared image quality is superior, providing a clear field of view. Therefore, ensuring that infrared modules produce high-quality infrared images in varying weather conditions has become a pressing issue. Summary of the Invention

[0004] In view of this, the present application provides an infrared image acquisition control method, device, equipment, infrared image acquisition system and computer-readable storage medium, which can enable the infrared module to obtain infrared images with good imaging quality under adverse weather conditions.

[0005] To achieve the above objectives, the technical solution of the embodiment of the present application is implemented as follows:

[0006] In a first aspect, an embodiment of the present application provides an infrared image acquisition control method, comprising:

[0007] Obtaining sensor data representing a current weather condition collected by a predetermined sensor, and determining a first weather type in a current environment of a target field of view based on the sensor data;

[0008] Obtain the original infrared image collected by the infrared module in real time for the target field of view;

[0009] performing an image quality analysis on the original infrared image based on an image detail layer of the original infrared image, and determining a second weather type under the current environment of the target field of view according to the image quality analysis result; and / or performing image recognition on the original infrared image using an image weather recognition model to determine a third weather type under the current environment of the target field of view;

[0010] The current weather type is determined based on the first weather type, the second weather type and / or the third weather type. When the current weather type is severe weather, the infrared module is controlled to start an image enhancement processing mode so that the infrared module performs image enhancement processing on the original infrared images subsequently collected in real time.

[0011] In a second aspect, an embodiment of the present application provides an infrared image acquisition and control device, comprising a processor and a memory, wherein the memory stores a computer program that can be executed by the processor, and when the computer program is executed by the processor, the infrared image acquisition and control method as described in any embodiment of the present application is implemented.

[0012] In a third aspect, an embodiment of the present application provides an infrared image acquisition system, characterized in that it includes an infrared module and the infrared image acquisition control device described in any embodiment of the present application, wherein the infrared module is used to acquire and output an infrared image of the target field of view.

[0013] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a controller, the infrared image acquisition control method described in any embodiment of the present application is implemented.

[0014] The infrared image acquisition control method, device, infrared image acquisition system, and computer storage medium provided in the above-mentioned embodiments of the present application can obtain sensor data representing the current weather conditions collected by a set sensor, and determine the first weather type of the target field of view's current environment based on the sensor data. In this way, the weather type of the current environment can be determined from the hardware level. The original infrared image captured in real time by the infrared module for the target field of view is obtained, and the original infrared image is subjected to image quality analysis based on the detail layer of the original infrared image. The second weather type of the target field of view's current environment is determined based on the image quality analysis results, and / or the original infrared image is subjected to image recognition using an image weather recognition model to identify the third weather type of the target field of view's current environment. In this way, the weather type of the current environment can be determined from the software level. Furthermore, the current weather type is determined based on the first weather type, the second weather type, and / or the third weather type. In this way, the current weather type can be accurately determined from both the hardware and software levels. Moreover, when the current weather type is severe weather, the infrared module is controlled to start the image enhancement processing mode, so that the infrared module performs image enhancement processing on the original infrared image subsequently collected in real time. In this way, the infrared module can collect infrared images according to the image enhancement processing mode under severe weather conditions, thereby enabling the infrared module to obtain infrared images with better imaging quality under severe weather conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A schematic diagram illustrating the architecture of an infrared image acquisition system provided in an embodiment of the present application is shown;

[0016] Figure 2 A schematic structural diagram of an infrared module provided in an embodiment of the present application is shown;

[0017] Figure 3 A schematic structural diagram of an integrated infrared module provided in an embodiment of the present application is shown;

[0018] Figure 4 A schematic diagram showing a flow chart of an infrared image acquisition control method provided in an embodiment of the present application;

[0019] Figure 5 A schematic diagram showing an infrared image provided by an embodiment of the present application;

[0020] Figure 6 A schematic diagram showing an enhanced infrared image provided by an embodiment of the present application;

[0021] Figure 7 A schematic diagram showing a flow chart of another infrared image acquisition control method provided in an embodiment of the present application;

[0022] Figure 8 A schematic structural diagram of an infrared image acquisition and control device provided in an embodiment of the present application is shown;

[0023] Figure 9 The figure shows a structural diagram of an infrared image acquisition and control device provided by the present application. DETAILED DESCRIPTION

[0024] The technical solution of this application is further elaborated in detail below with reference to the accompanying drawings and specific embodiments.

[0025] In order to make the purpose, technical solutions and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. The described embodiments should not be regarded as limiting this application. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0026] In the following description, the expression "some embodiments" is involved, which describes a subset of all possible embodiments. It should be noted that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict.

[0027] In the following description, the terms "first, second, and third" are merely used to distinguish similar objects and do not represent a specific ordering of the objects. It is understandable that "first, second, and third" can be interchanged with a specific order or sequence where permitted, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein.

[0028] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application pertains. The terms used herein are for the purpose of describing the embodiments of this application only and are not intended to limit this application.

[0029] Figure 1 A schematic diagram of the architecture of an infrared image acquisition system provided by an embodiment of the present application is shown in FIG. Figure 1 As shown, the infrared image acquisition system 10 may include an infrared module 11 and an infrared image acquisition control device 12. The infrared image acquisition control device 12 may execute the infrared image acquisition control method provided by any embodiment of the present application with respect to the target field of view measured by the infrared module 11, thereby enabling the infrared module 11 to obtain infrared images with good imaging quality under adverse weather conditions.

[0030] Figure 2 A schematic diagram of the structure of an infrared module provided in an embodiment of the present application is shown in FIG. Figure 2 As shown, the infrared module 11 may include a setting sensor 21 , a lens module 22 , a detector module 23 , an image processing module 24 and a signal output module 25 .

[0031] The sensor 21 may be configured to collect sensor data representing the current weather conditions. Alternatively, the sensor 21 may be configured to be a rain or snow sensor. Furthermore, the sensor may be configured to be a pressure sensor.

[0032] The lens module 22 may be any type of lens, including but not limited to fixed-focus lenses of various focal lengths or continuous zoom lenses. The lens module 22 may be used to acquire infrared radiation emitted by a target field of view.

[0033] The detector module 23 may be various types of detectors, including but not limited to light detectors and heat detectors. The detector module 23 may be used to collect infrared radiation emitted by the target field of view into an original infrared image.

[0034] The image processing module 24 can be used to perform image processing on the original infrared image according to the image acquisition mode to obtain a processed infrared image. In addition, in order to reduce the noise of the infrared image, the image processing module 24 can also be used to reduce the noise of the original infrared image.

[0035] The signal output module 25 can be used to output the infrared image after the image processing. Specifically, the signal output module can convert the enhanced infrared image or the original infrared image into a digital video signal or a model video output.

[0036] In some embodiments, as Figure 2 As shown, the infrared module 11 may further include a heating, dehumidification, and dust removal module 26. The heating, dehumidification, and dust removal module 26 may be used to perform heating, dehumidification, or dust removal on the lens module 22 according to the image acquisition mode, thereby keeping the lens module 22 clean in any weather conditions.

[0037] It should be noted that the infrared image acquisition and control device 12 can be provided separately from the infrared module.

[0038] Figure 3 FIG. 1 shows a schematic structural diagram of an integrated infrared module provided in an embodiment of the present application. Figure 3 As shown, the infrared image acquisition control device 12 can also be integrated with the infrared module 11.

[0039] After infrared radiation passes through lens module 22 and is received by detector module 23, it is enhanced by image processing module 24. The enhanced image is then output via signal output module 25. The infrared image acquisition and control device 12 is responsible for interacting with each module and executing various control actions.

[0040] Specifically, if the sensor 21 detects rain or snow, and the infrared image acquisition and control device 12 determines that the current weather is rainy or snowy based on other factors, it controls the heating, dehumidification, and dust removal module 26 to heat and dehumidify the lens module 22, and the image processing module 24 performs adaptive image enhancement processing to improve image quality. If the sensor 21 does not detect rain or snow, but the infrared image acquisition and control device 12 determines that the current weather is severe, such as sandstorms, it controls the heating, dehumidification, and dust removal module 26 to remove dust from the lens module 22, and the image processing module 24 performs adaptive image enhancement processing to improve image quality.

[0041] In the above embodiment, the infrared image acquisition and control device may be a device with computing and storage functions, such as a vehicle-mounted device or a chip integrated in an infrared module.

[0042] In one aspect of the present application, an infrared image acquisition control method is provided, which can be applied to Figure 1 The infrared image acquisition control device 12 is shown. Figure 4 A flow chart of an infrared image acquisition control method provided by an embodiment of the present application is shown as follows: Figure 4As shown, the infrared image acquisition control method may include but is not limited to S41, S42, S43, S44 and S45.

[0043] S41, obtaining sensor data representing the current weather conditions collected by a set sensor, and determining a first weather type in the current environment of the target field of view according to the sensor data.

[0044] Here, the target field of view may be the range of the environment observable by the infrared module. The sensor data may represent the current weather conditions. The sensor data may be data collected from the environment in which the target field of view is located under the current weather conditions set by the sensor. The first weather type may include, but is not limited to, severe weather or normal weather.

[0045] In the embodiment of the present application, the sensor data collected by the sensor is set to be different under different weather conditions. The correspondence between different numerical ranges of the sensor data and different weather types can be determined by using a large amount of experimental weather data. The correspondence between the sensor data and the weather types is pre-stored in the infrared image acquisition and control device. The weather type of the current environment in the target field of view is determined based on the numerical range of the sensor data, thereby obtaining a first weather type.

[0046] In the embodiments of the present application, the set sensors may include, but are not limited to, one or more of a temperature sensor, a humidity sensor, a rain and snow sensor, and a pressure sensor. Correspondingly, the sensor data may include, but are not limited to, one or more of current data, voltage data, temperature data, humidity data, and pressure data.

[0047] S42, obtaining the original infrared image collected by the infrared module in real time for the target field of view.

[0048] Here, the original infrared image can be an image formed based on the intensity of infrared radiation from the surface of an object within the target field of view. In other words, it is an image directly formed by the detector. The original infrared image is a single-channel image.

[0049] S43, performing image quality analysis on the original infrared image based on the detail layer of the original infrared image, and determining the second weather type in the current environment of the target field of view according to the image quality analysis result; and / or, performing image recognition on the original infrared image through an image weather recognition model to identify the third weather type in the current environment of the target field of view.

[0050] Here, the detail layer of the original infrared image may contain high-frequency information of the original infrared image and may reflect small-scale details of the original infrared image. Image quality analysis results may include, but are not limited to, image clarity and image blur. The second weather type may be the weather type of the current environment in the target field of view. The second weather may include, but is not limited to, severe weather or normal weather. Severe weather may include, but is not limited to, dusty weather and rainy and snowy weather. Normal weather may include, but is not limited to, clear weather and cloudy weather.

[0051] In the embodiments of the present application, the quality of the original infrared images captured by the infrared module varies under different weather conditions. For example, under normal weather conditions, infrared images are clear and sharp, with a wide dynamic range and strong contrast, while under severe weather conditions, the infrared images become relatively blurry and lose image detail. Therefore, the image quality of the original infrared image can be analyzed based on its detail layer. Based on the mapping relationship between image quality and weather type, the weather type that matches the image quality analysis result of the original infrared image can be determined, thereby obtaining a second weather type.

[0052] Here, the image weather recognition model can be a pre-trained classification neural network model. The image weather recognition model can be used to recognize scenes under various weather conditions.

[0053] In specific implementation, infrared images under various weather conditions can be used as training samples, and the training samples can be labeled with weather categories. The image weather recognition model can be trained using the training samples labeled with the target category, that is, the image weather recognition model can predict the category of the training samples, and compare the predicted category with the labeled category to determine the value of the loss function of the image weather recognition model based on the difference between the predicted category and the labeled category. The value of the loss function is then transmitted back to each layer of the image weather recognition model, and the model parameters of each layer are updated by the stochastic gradient descent method to realize model training.

[0054] In other words, raw infrared images of various weather conditions are collected in advance as training samples. Deep learning is then used to train these training samples and develop an image weather recognition model that can identify various weather types. The real-time raw infrared images are then fed into the image weather recognition model to identify the weather conditions in the target field of view and determine the weather conditions.

[0055] S44, based on the first weather type, and the second weather type and / or the third weather type, determine the current weather type. When the current weather type is severe weather, control the infrared module to start the image enhancement processing mode so that the infrared module performs image enhancement processing on the original infrared image subsequently collected in real time.

[0056] Here, the current weather type may be the weather type of the target field of view's current environment. The current weather type may include, but is not limited to, severe weather and normal weather. Severe weather may include, but is not limited to, sandstorms and rainy and snowy weather. Normal weather may include, but is not limited to, clear weather and cloudy weather.

[0057] In an embodiment of the present application, the infrared image acquisition and control device can determine the current weather type based on the first weather type and the second weather type. Alternatively, the current weather type can be determined based on the first weather type and the third weather type. Alternatively, the current weather type can be determined based on the first weather type, the second weather type, and the third weather type. In this way, the current weather type can be comprehensively determined at both the hardware and software levels.

[0058] For example, if the sensor is set as a rain and snow sensor and the rain and snow sensor does not detect the presence of rain or snow, it can be determined that the first weather type is not rain or snow weather, and whether the current weather type is normal weather can be determined based on the second weather type and / or the third weather type.

[0059] It should be noted that when the first weather type is a certain type of severe weather, the second weather type and / or the third weather type can be used to assist in determining whether the current weather type is severe weather. When the first weather type is not a certain type of severe weather, the second weather type and / or the third weather type can be used to determine whether the current weather type is severe weather.

[0060] It should be noted that, when the infrared image acquisition control device determines the first weather type and the second weather type, it can determine the current weather type according to the first weather type and the second weather type.

[0061] When the infrared image acquisition control device determines the first weather type and the third weather type, it can determine the current weather type according to the first weather type and the third weather type.

[0062] When the infrared image acquisition control device determines the first weather type, the second weather type, and the third weather type, it can determine the current weather type based on the first weather type, the second weather type, and the third weather type.

[0063] In an embodiment of the present application, the infrared image acquisition and control device can control the device's infrared module to activate different image processing modes for different weather types. That is, each image processing mode corresponds to each weather type. The image processing modes may include, but are not limited to, image enhancement processing mode and conventional image processing mode. For example, severe weather corresponds to image enhancement processing mode, while normal weather corresponds to conventional image processing mode.

[0064] In an embodiment of the present application, the infrared image acquisition control device can determine the image processing mode that matches the current weather type based on the mapping relationship between weather type and image processing mode, thereby controlling the infrared module to activate the matching image processing mode, so that the infrared module performs corresponding processing on the raw infrared images subsequently acquired in real time. In this way, the infrared module can process the raw infrared images acquired in real time in different ways according to different image processing modes under different weather conditions, allowing the infrared module to obtain infrared images with good imaging quality under all weather conditions.

[0065] Specifically, when the current weather type is severe weather, the infrared image acquisition control device can determine the image enhancement processing mode that matches the severe weather based on the mapping relationship between the weather type and the image processing mode, thereby controlling the infrared module to turn on the image enhancement processing mode, so that the infrared module can perform image enhancement processing on the original infrared images subsequently acquired in real time.

[0066] When the current weather type is normal weather, the infrared image acquisition control device can determine the normal image processing mode that matches the normal weather based on the mapping relationship between the weather type and the image processing mode, thereby controlling the infrared module to start the normal image processing mode, so that the infrared module can perform normal image processing on the original infrared images subsequently acquired in real time.

[0067] It should be noted that the image processing parameters used to process the original infrared image in the image enhancement mode are greater than those used in the conventional image processing mode. In other words, the image quality of the infrared image after conventional image processing and the infrared image after image enhancement are both higher than the image quality of the original infrared image. However, the degree of change in the infrared image after conventional image processing relative to the original infrared image is less than that after image enhancement processing.

[0068] Here, the image processing parameters may include but are not limited to image detail processing parameters, image sharpness processing parameters, and image contrast parameters.

[0069] In the embodiments of the present application, the raw infrared image subsequently acquired in real time can be understood as the raw infrared image acquired in real time after the current weather type is determined. Here, after the infrared module activates the image processing mode corresponding to the current weather type, it configures the corresponding image processing parameters to process the raw infrared image acquired in real time until the re-determined current weather type changes. In addition, the infrared module can also activate specific functions (such as heating and dehumidification or dust removal) to improve lens clarity.

[0070] In the above embodiment, sensor data representing the current weather conditions collected by a set sensor can be obtained, and the first weather type in the current environment of the target field of view can be determined based on the sensor data. In this way, the weather type of the current environment can be determined from the hardware level. The original infrared image collected in real time by the infrared module for the target field of view is obtained, and the image quality analysis of the original infrared image is performed on the original infrared image based on the detail layer of the original infrared image. The second weather type in the current environment of the target field of view is determined based on the image quality analysis result, and / or the original infrared image is subjected to image recognition by an image weather recognition model to identify the third weather type in the current environment of the target field of view. In this way, the weather type of the current environment can be determined from the software level. And, based on the first weather type, as well as the second weather type and / or the third weather type, the current weather type is determined. In this way, the current weather type can be accurately determined from two different levels, hardware and software. Moreover, when the current weather type is severe weather, the infrared module is controlled to start the image enhancement processing mode, so that the infrared module performs image enhancement processing on the original infrared image subsequently collected in real time. In this way, the infrared module can collect infrared images according to the image enhancement processing mode under severe weather conditions, thereby enabling the infrared module to obtain infrared images with better imaging quality under severe weather conditions.

[0071] In some embodiments, S41, obtaining sensor data representing the current weather conditions collected by a predetermined sensor, and determining a first weather type in the current environment of the target field of view based on the sensor data, includes:

[0072] Sensor data collected by a rain and snow sensor is acquired, and whether the first weather type is rain and snow weather is determined according to the sensor data.

[0073] Here, the sensor can be a rain or snow sensor. The rain or snow sensor can be mounted on the surface of the infrared module and can detect whether rain or snow has fallen on the infrared module. The sensor data from the rain or snow sensor can be analog (such as current or voltage) or digital (such as a high-level signal or a low-level signal). The rain or snow sensor can output different sensor data depending on whether it is raining or snowing, or not.

[0074] In an embodiment of the present application, the infrared image acquisition control device can obtain the sensor data currently collected by the rain and snow sensor, and determine whether the first weather type in the current environment of the target field of view is rain and snow weather based on the mapping relationship between the sensor data and the weather type.

[0075] In the above embodiment, the rain and snow sensor is used as the setting sensor, so that whether the first weather type is rain and snow weather can be accurately determined through sensor data, thereby improving the determination accuracy of the first weather type.

[0076] In some embodiments, S42, obtaining a raw infrared image captured in real time by the infrared module for the target field of view, includes:

[0077] When the current ambient temperature satisfies the image detection conditions, obtaining the original infrared image captured by the infrared module in real time for the target field of view; and / or,

[0078] Acquire the original infrared image collected by the infrared module in real time for the target field of view at a preset time interval; and / or,

[0079] When the first weather type meets the preset type, the original infrared image collected by the infrared module in real time for the target field of view is obtained.

[0080] Here, the image detection condition may be a condition for detecting the weather type based on the original infrared image. The image detection condition may be that the current ambient temperature is less than a preset temperature. The preset temperature may be an average temperature for normal weather. The preset type may be rainy or snowy weather or non-rainy or snowy weather.

[0081] Since the weather environment will not change significantly within a relatively small range, it is not necessary to determine the weather type in real time, and the weather type can be determined once every preset time period.

[0082] Since the ambient temperature varies in different weather conditions, a weather type judgment can be performed when the weather temperature reaches a preset condition.

[0083] In an embodiment of the present application, the infrared image acquisition control device can obtain the original infrared image captured in real time by the infrared module for the target field of view when the current ambient temperature meets the image detection conditions, every preset time period, and the first weather type meets one or more conditions of the preset types, and start the second weather type determination step and the third weather type determination step.

[0084] In the above embodiment, under specific conditions, the original infrared image collected by the infrared module in real time for the target field of view is obtained, thereby starting the second weather type and third weather type determination process, which can reduce the number of weather type judgments and reduce the probability of blind detection.

[0085] In some embodiments, after acquiring the original infrared image captured by the infrared module in real time for the target field of view in S42, the infrared image acquisition control method further includes: performing noise reduction processing on the original infrared image.

[0086] Here, the noise reduction process can be performed using an existing image noise reduction process method. In this way, the noise interference of the original infrared image can be removed through the noise reduction process, the image quality can be improved, and the image quality analysis result can be made more accurate.

[0087] In some embodiments, in S43, performing image quality analysis on the original infrared image based on the detail layer of the original infrared image may include:

[0088] Extracting a detail layer from the original infrared image, and determining the number of first pixels in the detail layer whose absolute values of pixel values are not greater than a preset detail threshold;

[0089] Calculating a pixel mean of the original infrared image, and determining the number of second pixels in the original infrared image whose pixel values are smaller than the pixel mean, and the number of third pixels whose pixel values are smaller than a preset pixel value;

[0090] An image quality analysis result of the original infrared image is obtained based on the difference between the number of the first pixels and the first preset threshold, and the difference between the number of the second pixels and the number of the third pixels.

[0091] Here, the detail layer of the original infrared image may be extracted by using existing image detail layer extraction methods, such as additive decomposition method and multiplicative decomposition method.

[0092] The absolute value of a pixel may be the absolute value of a pixel value of the pixel. The first pixel may be a pixel in the detail layer whose absolute value of the pixel value is not greater than a preset detail threshold. The preset detail threshold may be not greater than the average absolute value of the pixels in the detail layer of the original infrared image under normal weather conditions.

[0093] The pixel mean of the original infrared image may be the mean of the pixel values of the pixels in the original infrared image. Calculating the pixel mean of the original infrared image may be understood as summing the pixel values of all pixels in the original infrared image and then dividing the sum by the number of pixels in the original infrared image.

[0094] The second pixel may be a pixel in the original infrared image whose pixel value is less than the pixel mean. The third pixel may be a pixel whose pixel value is less than a preset pixel value. The preset pixel value may be within the pixel value range of a clear infrared image. The first preset threshold may be set based on experience. Optionally, the first preset threshold may be 90% of the total number of pixels in the detail layer.

[0095] The image quality analysis result can be used to indicate whether the quality of the original infrared image is blurry, and can include two analysis results: clear and blurry.

[0096] In the embodiment of the present application, an image quality analysis result of the raw infrared image is determined based on the difference between the number of first pixels and the first preset threshold, and the difference between the number of second pixels and the number of third pixels. Simultaneously, based on the mapping relationship between the image quality analysis result and the weather type, a second weather type in the current environment of the target field of view is determined based on the image quality analysis result of the raw infrared image acquired in real time.

[0097] In the above embodiment, the image quality of the original infrared image can be accurately judged by the absolute value of the pixels in the detail layer and the original pixel value of the image.

[0098] In some embodiments, obtaining an image quality analysis result of the original infrared image based on a difference between the number of first pixels and a first preset threshold, and a difference between the number of second pixels and a third pixel, includes:

[0099] When the number of the first pixels is greater than the first preset threshold and the number of the second pixels is not greater than the number of the third pixels, the image quality analysis result of the original infrared image is blurred.

[0100] Here, when the number of first pixels is greater than the first preset threshold, it can be indicated that the details of the original image are relatively blurred, that is, the current scene in the original image is relatively blurred. When the number of second pixels is not greater than the number of third pixels, it can be indicated that most pixels in the original infrared image are in a blurred state. Therefore, based on these two conditions, it can be comprehensively determined that the original infrared image is relatively blurred, that is, the image quality analysis result of the original infrared image is blurred.

[0101] In some embodiments, obtaining an image quality analysis result of the original infrared image based on a difference between the number of first pixels and a first preset threshold, and a difference between the number of second pixels and a third pixel, includes:

[0102] When the number of the second pixels is greater than the number of the third pixels, the image quality analysis result of the original infrared image is clear.

[0103] Here, when the number of second pixels is greater than the number of third pixels, it can be said that most pixels of the original infrared image are in a clear state. Therefore, it can be determined that the original infrared image is relatively clear, that is, the image quality analysis result of the original infrared image is clear.

[0104] In some embodiments, in S43, performing image quality analysis on the original infrared image based on the detail layer of the original infrared image may include:

[0105] Extracting detail layers from a plurality of first original infrared images collected by the infrared module within a current time period to obtain a plurality of first detail layers;

[0106] Performing image absolute value conversion on each first detail layer to obtain a first absolute value image corresponding to each first detail layer;

[0107] Calculating the pixel mean of each first absolute value image to obtain a first pixel mean of each first absolute value image;

[0108] An image quality analysis result is determined based on the magnitude of each first pixel mean value and a preset total mean value.

[0109] Here, the current time period may start from the time when the weather type detection is determined based on the original infrared image and end at a preset time interval. The current time period may be longer than 1 minute. The multiple first original infrared images may be original infrared images collected over a continuous period of time.

[0110] In the embodiment of the present application, since the original infrared image captured in real time by the infrared module changes very little over a short period of time, the infrared image acquisition control device may acquire the first original infrared image captured in real time by the infrared module at a preset interval within the current time period. Optionally, the preset interval may be 1 second.

[0111] The first detail layer can be obtained by extracting details from the first original infrared image using an existing image detail extraction method. Each detail layer corresponds to a first original infrared image.

[0112] Image absolute value conversion can be understood as converting the pixel values of all pixels in an image into absolute values. For example, if pixel A has a value of -15, after image absolute value conversion, the pixel value of pixel A becomes 15. The first absolute valued image can be an image with no negative pixel values. Each first absolute valued image corresponds to each first detail layer image.

[0113] The pixel mean calculation may be performed by summing the pixel values of all pixels in the first absolute valued image and then dividing the sum by the number of pixels. In the embodiment of the present application, to avoid interference from low pixel values, when performing the pixel mean calculation on each first absolute valued image, pixels with pixel values less than 3 in each first absolute valued image may be deleted before performing the pixel mean calculation on the remaining pixels.

[0114] The preset total mean value may be the mean of a plurality of first pixel mean values within a historical time period. The historical time period may be a time period before severe weather, for example, a period before a rain or snow sensor detects rain or snow. Optionally, the historical time period may be more than 2 minutes.

[0115] It should be noted that the preset total mean value can be obtained by real-time calculation of the original infrared image collected in real time, or by calculation based on historical original infrared images. In the embodiment of the present application, there is no limitation on the method for obtaining the preset total mean value.

[0116] In this embodiment of the present application, an image quality analysis result for the current time period can be determined based on a comparison result of multiple first pixel means with a preset total mean. Simultaneously, a second weather type that matches the image quality analysis result for the current time period can be determined based on a mapping relationship between the image quality analysis result and the weather type.

[0117] In the above embodiment, the image quality of the original infrared image in the current period can be accurately analyzed by comparing the average of the absolute values of the pixels of the detail layers of a plurality of consecutive original infrared images with the preset total average.

[0118] In some embodiments, determining an image quality analysis result based on the difference between each first pixel mean and a preset total mean includes:

[0119] When each first pixel mean is less than a preset total mean, the image quality analysis result is determined to be blurred.

[0120] Here, when each first pixel mean is less than the preset total mean, it can be determined that the image quality of the original infrared image in the current time period has deteriorated relative to the image quality of the original infrared image in the historical time period, that is, the image quality in the current time period has deteriorated relative to the image quality in the time period before the bad weather, and thus the image quality analysis result can be determined to be fuzzy.

[0121] In some embodiments, in S43, determining the second weather type of the target field of view's current environment based on the image quality analysis result includes:

[0122] When the image quality analysis result is blurred, determining that the second weather type of the current environment of the target field of view is severe weather;

[0123] When the image quality analysis result is clear, it is determined that the second weather type in the current environment of the target field of view is normal weather.

[0124] Here, under normal weather conditions, infrared images are clear and sharp, with a wide dynamic range and strong contrast, while in severe weather, infrared images become relatively blurry and lose image detail. Therefore, if the image quality analysis result is blurry, the second weather type can be determined to be severe weather, and if the image quality analysis result is normal, the second weather type can be determined to be normal weather.

[0125] In one example, after preliminary noise reduction is performed on the original infrared image, image details are extracted. A detail threshold T0 is given, and the absolute values of the image details are counted. If more than 90% of the values are less than T0, the current scene is judged to be blurry, possibly indicating inclement weather conditions. A pixel mean A0 is calculated for the original infrared image, and a normal pixel threshold B0 is given. The number Na of pixels in the original infrared image with values less than A0 and the number Nb of pixels with values less than B0 are counted. If Na is less than or equal to Nb, the majority of the image pixels are blurred, indicating that the original infrared image is blurred. If Na is greater than Nb, the infrared image is relatively clear. If the current scene in the original infrared image is blurry or the original infrared image is blurred, the second weather type can be determined to be inclement weather.

[0126] In one example, one frame is extracted per second from the raw infrared image captured in real time. After preliminary noise reduction is performed on the raw infrared image, image details are extracted and their absolute values are calculated. Points with absolute values less than or equal to 3 in the image details are excluded from the calculation. The mean (M1) of the absolute values of the remaining points is calculated. M2 is then calculated by averaging M1 for a period of time (more than 2 minutes) before the rain or snow sensor detects rain or snow. If the M1 values for multiple consecutive frames within the current time period decrease relative to the M2 values, the image quality analysis result is considered blurred, and the second weather type is determined to be inclement weather.

[0127] In some embodiments, in S44, when the current weather type is severe weather, controlling the infrared module to start an image enhancement processing mode so that the infrared module performs image enhancement processing on the subsequent raw infrared image collected in real time may include:

[0128] When the current weather type is severe weather, and the severe weather is rain or snow, the infrared module is controlled to start the heating and dehumidification function of the acquisition lens, and the first image enhancement processing parameters are configured so that the infrared module performs image enhancement processing on the subsequent real-time acquired original infrared image according to the first image enhancement processing parameters.

[0129] Here, the image enhancement processing mode may include processing the original infrared image with a first image enhancement parameter and enabling a heating and dehumidification function. The first image enhancement parameter may be determined based on a conventional image parameter and a first weight. The conventional image parameter may be an image processing parameter under normal weather conditions, i.e., an image processing parameter in the conventional image processing mode. The first weight may be determined based on a mean of absolute pixel values of a detail layer of the original infrared image under rainy or snowy weather conditions and a preset overall mean.

[0130] The preset total mean can be the total average of the mean of the absolute values of the pixels of the detail layers of multiple original infrared images under normal weather conditions within the historical time period, that is, the absolute value of the pixels of the detail layer of each original infrared image under normal weather conditions within the historical time period is first averaged to obtain the mean of multiple pixel absolute values, and then the mean of the multiple pixel absolute values is averaged to obtain multiple preset total means.

[0131] Optionally, the first image enhancement parameter may include a first detail enhancement parameter, a first sharpness enhancement parameter, and a first contrast enhancement parameter. The first image enhancement parameter can be used to adaptively increase the detail enhancement function of the image, adaptively enhance the sharpness, and adaptively increase the contrast stretching, thereby improving the infrared image quality.

[0132] The first weight can be expressed as M2 / M1. The value range of the first weight can be (1, 5], where M2 is a preset total mean value and M1 is the mean of the absolute values of the pixels in the detail layer of the original infrared image under rainy and snowy weather. The calculation formula of the first image enhancement parameter can be expressed as:

[0133] Detail1=M2 / M1*DetailNormal (1)

[0134] Among them, DetailNormal is the detail parameter under normal weather conditions, and Detail 1 is the first detail enhancement parameter.

[0135] Sharpen1= M2 / M1*SharpenNorma l (2)

[0136] SharpenNorma l is the image sharpness under normal weather conditions, and Sharpen1 is the first sharpness enhancement parameter.

[0137] Contrast1=M2 / M1*ContrastNorma l (3)

[0138] ContrastNormal is the image contrast under normal weather conditions, and Contrast1 is the first contrast enhancement parameter.

[0139] Here, the infrared image acquisition control device controls the infrared module to start the heating and dehumidification function on the acquisition lens, which can be understood as controlling the infrared module to perform heating and dehumidification processing on the acquisition lens, thereby removing rain and snow falling on the lens and improving the clarity of the acquisition lens.

[0140] In the above embodiment, in the rainy and snowy environment mode, the infrared module is controlled to heat and dehumidify the collection lens to remove dirt on the collection lens, and the infrared module is controlled to process the collected original infrared image according to the first image enhancement parameter, thereby improving the quality of infrared imaging in rainy and snowy weather.

[0141] In some embodiments, in S44, when the current weather type is severe weather, controlling the infrared module to start an image enhancement processing mode so that the infrared module performs image enhancement processing on the subsequent raw infrared image collected in real time may include:

[0142] When the current weather type is severe weather and the severe weather is sandstorm weather, the infrared module is controlled to start the dust removal function for the acquisition lens and configure the second image enhancement processing parameters so that the infrared module performs image enhancement processing on the subsequent real-time acquired original infrared images according to the second image enhancement processing parameters.

[0143] Here, the image enhancement processing mode may include processing the original infrared image with a second image enhancement parameter and activating a dust removal function. The second image enhancement parameter may be determined based on a conventional image parameter and a second weight. The conventional image parameter may be an image processing parameter under normal weather conditions, i.e., an image processing parameter under the conventional image processing mode. The second weight may be determined based on a mean of absolute pixel values of a detail layer of the original infrared image under dusty weather conditions and a preset overall mean.

[0144] The preset total mean can be the total average of the mean of the absolute values of the pixels of the detail layers of multiple original infrared images under normal weather conditions within the historical time period, that is, the absolute value of the pixels of the detail layer of each original infrared image under normal weather conditions within the historical time period is first averaged to obtain the mean of multiple pixel absolute values, and then the mean of the multiple pixel absolute values is averaged to obtain multiple preset total means.

[0145] Optionally, the second image enhancement parameters may include a second detail enhancement parameter, a second sharpness enhancement parameter, and a second contrast enhancement parameter. In the embodiment of the present application, the second image enhancement parameters can be used to adaptively increase the detail enhancement function of the image, adaptively enhance the sharpness, and adaptively increase the contrast stretching, thereby improving the quality of the infrared image.

[0146] The second weight can be expressed as M4 / M3. The value range of the second weight can be (1, 5], where M3 is a preset total mean value and M4 is the mean of the absolute values of the pixels in the detail layer of the original infrared image under dust weather. The calculation formula of the second image enhancement parameter can be expressed as:

[0147] Detail2= M4 / M3*DetailNormal (4)

[0148] Among them, DetailNormal is the detail processing parameter under normal weather conditions, and Detail 2 is the second detail enhancement parameter.

[0149] Sharpen2= M4 / M3*SharpenNorma l (5)

[0150] SharpenNorma 1 is the image sharpness processing parameter under normal weather conditions, and Sharpen2 is the second sharpness enhancement parameter.

[0151] Contrast2=M4 / M3*ContrastNorma l (6)

[0152] ContrastNormal is the image contrast processing parameter under normal weather conditions, and Contrast2 is the second contrast enhancement parameter.

[0153] Here, the infrared image acquisition control device controlling the infrared module to start the dust removal function on the acquisition lens can be understood as controlling the infrared module to perform dust removal on the acquisition lens, thereby removing the sand and dust falling on the lens and improving the clarity of the acquisition lens.

[0154] In the above embodiment, in the dusty environment mode, the infrared image acquisition control device controls the infrared module to remove dust from the acquisition lens, thereby removing the dust on the acquisition lens and achieving the purpose of cleaning the acquisition lens, and controls the infrared module to process the collected original infrared image according to the second image enhancement parameter, thereby improving the quality of infrared imaging in dusty weather.

[0155] It should be noted that, in severe weather including rain and snow, the infrared image acquisition control device can control the infrared module to start an image enhancement processing mode including the first image enhancement parameter and the heating and dehumidification function.

[0156] In severe weather including dusty weather, the infrared module is controlled to start an image enhancement processing mode including a second image enhancement parameter and a dust removal function.

[0157] When the severe weather includes rain, snow and sandstorm, the infrared image acquisition control device first determines whether the severe weather is rain, snow or sandstorm, and then starts the corresponding image enhancement processing mode according to the corresponding weather type.

[0158] In some embodiments, in S44, when the current weather type is severe weather, controlling the infrared module to start an image enhancement processing mode so that the infrared module performs image enhancement processing on the subsequent raw infrared image collected in real time may include:

[0159] When the first weather type, the second weather type and / or the third weather type are severe weather, determining that the current weather type is severe weather;

[0160] The infrared module is controlled to perform image enhancement processing on the subsequent real-time acquired original infrared images according to the image enhancement parameters.

[0161] Here, severe weather may include but is not limited to rainy, snowy, and sandy weather.

[0162] When the first weather type, the second weather type, and / or the third weather type are inclement weather, determining that the current weather type is inclement weather may be: when the first weather type is inclement weather and the second weather type is inclement weather, the current weather type may be determined to be inclement weather. Alternatively, when the first weather type is inclement weather and the third weather type is inclement weather, the current weather type may be determined to be inclement weather. Alternatively, when the first weather type is inclement weather, the second weather type is inclement weather, and the third weather type is inclement weather, the current weather type may be determined to be inclement weather.

[0163] The harsh environment mode may include an image enhancement processing mode. In the image enhancement processing mode, the image processing parameters are image enhancement parameters.

[0164] The image enhancement parameters may be determined based on the image general parameters and a third weight, wherein the third weight is determined based on the average absolute value of the pixel of the detail layer of the original infrared image under the current weather conditions and a preset total average.

[0165] Optionally, the image enhancement parameters may include but are not limited to image detail enhancement parameters, image sharpness enhancement parameters, and image contrast enhancement parameters.

[0166] In the embodiment of the present application, the image detail enhancement function, the sharpness adaptively enhanced and the contrast stretching adaptively increased can be used through the image enhancement parameters, thereby improving the quality of the infrared image.

[0167] The third weight can be expressed as M6 / M5. The value range of the third weight can be (1, 5], where M6 is the preset total mean value and M5 is the mean of the absolute values of the pixels in the detail layer of the original infrared image under the current severe weather conditions. The calculation formula of the second image enhancement parameter can be expressed as:

[0168] Detai l 3= M6 / M5*Detai l Norma l (7)

[0169] Among them, Detail Normal is the detail processing parameter under normal weather conditions, and Detail 3 is the detail enhancement parameter under severe weather conditions.

[0170] Sharpen3= M6 / M5*SharpenNorma l (8)

[0171] SharpenNorma l is the image sharpness processing parameter under normal weather conditions, and Sharpen3 is the sharpness enhancement parameter under severe weather conditions.

[0172] Contrast3=M6 / M5*ContrastNorma l (9)

[0173] ContrastNormal is the image contrast processing parameter under normal weather conditions, and Contrast3 is the contrast enhancement parameter under severe weather conditions.

[0174] In the above embodiment, since the image enhancement parameters are greater than the conventional image parameters, controlling the infrared module to process the captured infrared image according to the image enhancement parameters in a harsh environment can adaptively enhance the image and improve the quality of the infrared image.

[0175] Figure 5 A schematic diagram of an infrared image provided by an embodiment of the present application is shown. Figure 6 A schematic diagram of an enhanced infrared image provided by an embodiment of the present application is shown. On rainy days, the infrared image collected by the infrared module according to the general environment mode can be as follows Figure 5 As shown. The infrared image collected by the infrared module according to the rain and snow environment mode can be as follows Figure 6 As shown. Figure 5 and Figure 6 , it can be found that Figure 6 The infrared image shown is Figure 5 The infrared image shown is clearer and has better imaging quality.

[0176] In order to have a more comprehensive understanding of the infrared image acquisition control method provided in the embodiment of the present application, a specific example is used below for illustration, wherein the sensor is set to be a rain or snow sensor. Figure 7 A flow chart of another infrared image acquisition control method provided by an embodiment of the present application is shown as follows: Figure 7 As shown, the infrared image acquisition control method includes:

[0177] S71, obtaining sensor data collected by the rain and snow sensor in real time.

[0178] S72: Determine a first weather type based on the sensor data collected in real time.

[0179] S73, obtaining the original infrared image collected by the infrared module in real time.

[0180] S74, performing image quality analysis on the original infrared image to obtain an image quality analysis result.

[0181] Here, the image quality analysis method is consistent with the image quality analysis method in the aforementioned embodiment and will not be described again here.

[0182] S75: Determine the second weather type based on the image quality analysis result.

[0183] S76, inputting the original infrared image into the image weather recognition model to obtain a third weather type.

[0184] S77: Determine the current weather type based on the first weather type, the second weather type, and the third weather type. If the current weather type is severe weather, proceed to S78. If the current weather type is normal weather, proceed to S79.

[0185] S78, setting the image configuration (ie, image processing mode) of the infrared module to an adaptive enhancement configuration (ie, image enhancement processing mode).

[0186] Here, the image detail enhancement function, sharpness and contrast enhancement can be adaptively increased through the adaptive enhancement configuration, thereby improving the quality of the infrared image.

[0187] S79, setting the image configuration of the infrared module to a normal configuration (ie, a normal image processing mode).

[0188] S710, controlling infrared image output.

[0189] In some embodiments, after setting the image configuration of the infrared module to the adaptive enhancement configuration at S78, the infrared image acquisition control method further includes:

[0190] In the case of severe weather such as rain or snow, the heating and dehumidification functions are activated;

[0191] In the case of severe sandstorms, the dust removal function must be activated.

[0192] In some embodiments, S77, determining the current weather type based on the first weather type, the second weather type, and the third weather type may include:

[0193] If the first weather type is rainy or snowy in the previous time period and the first weather type is non-rainy or snowy in the current time period, it is determined whether the current weather type is severe weather based on the second weather type and the third weather type.

[0194] Here, if the current weather type is still inclement weather, the infrared module's image configuration remains unchanged. If the current weather type is not inclement weather, the infrared module's image configuration is switched from the adaptive enhanced configuration to the normal configuration, and the heating and dehumidification function or the dust removal function is turned off (i.e., the heating, dehumidification and dust removal modules are controlled to stop working).

[0195] On the other hand, an embodiment of the present application further provides an infrared image acquisition and control device. Figure 8 FIG. 1 shows a schematic diagram of the structure of an infrared image acquisition control device provided in an embodiment of the present application. Figure 8 As shown, the infrared image acquisition control device may include:

[0196] A first weather determination module 81 is configured to obtain sensor data representing the current weather conditions collected by a predetermined sensor, and determine a first weather type in the current environment of the target field of view based on the sensor data;

[0197] The original image acquisition module 82 is used to acquire the original infrared image collected by the infrared module in real time for the target field of view;

[0198] a second weather determination module 83 configured to perform an image quality analysis on the original infrared image based on the detail layer of the original infrared image, and determine a second weather type in the current environment of the target field of view based on the image quality analysis result; and / or to perform image recognition on the original infrared image using an image weather recognition model to identify a third weather type in the current environment of the target field of view;

[0199] The mode control module 84 is used to determine the current weather type based on the first weather type, the second weather type and / or the third weather type. When the current weather type is severe weather, the mode control module 84 controls the infrared module to start the image enhancement processing mode so that the infrared module performs image enhancement processing on the original infrared images subsequently collected in real time.

[0200] In some embodiments, the first weather determination module 81 is specifically configured to:

[0201] Acquire rain and snow sensing data collected by the rain and snow sensor, and determine whether the first weather type in the current environment of the target field of view is rain and snow weather based on the rain and snow sensing data.

[0202] In some embodiments, the original image acquisition module 82 is specifically configured to:

[0203] When the current ambient temperature satisfies the image detection conditions, obtaining the original infrared image captured by the infrared module in real time for the target field of view; and / or,

[0204] Acquire the original infrared image collected by the infrared module in real time for the target field of view at a preset time interval; and / or,

[0205] When the first weather type meets the preset type, the original infrared image collected by the infrared module in real time for the target field of view is obtained.

[0206] In some embodiments, the second weather determination module 83 may include:

[0207] A first quantity determination submodule is configured to extract a detail layer from the original infrared image and determine the number of first pixels in the detail layer whose absolute values of the pixel values are not greater than a preset detail threshold;

[0208] a second number and a third number determining submodule, configured to calculate a pixel mean of the original infrared image, and determine the number of second pixels in the original infrared image whose pixel values are smaller than the pixel mean, and the number of third pixels whose pixel values are smaller than a preset pixel value;

[0209] The result obtaining submodule is used to obtain the image quality analysis result of the original infrared image based on the difference between the number of the first pixels and the first preset threshold, and the difference between the number of the second pixels and the number of the third pixels.

[0210] In some embodiments, the result obtaining submodule may be specifically used to:

[0211] When the number of the first pixels is greater than the first preset threshold and the number of the second pixels is not greater than the number of the third pixels, the image quality analysis result of the original infrared image is blurred.

[0212] In some embodiments, the second weather determination module 83 may include:

[0213] A detail layer extraction submodule is used to extract detail layers from a plurality of first original infrared images collected by the infrared module within a current time period to obtain a plurality of first detail layers;

[0214] An image conversion submodule, configured to perform image absolute value conversion on each first detail layer to obtain a first absolute value image corresponding to each first detail layer;

[0215] a mean calculation submodule, configured to perform pixel mean calculation on each first absolute value image to obtain a first pixel mean of each first absolute value image;

[0216] The analysis result determination submodule is used to determine the image quality analysis result based on the size of each first pixel mean value and a preset total mean value.

[0217] In some embodiments, the analysis result determination submodule may be specifically configured to:

[0218] When each first pixel mean is less than a preset total mean, the image quality analysis result is determined to be blurred.

[0219] In some embodiments, the second weather determination module 83 may include:

[0220] A bad weather determination submodule is used to determine that the second weather type in the current environment of the target field of view is bad weather when the image quality analysis result is blurred;

[0221] The normal weather determination submodule is used to determine that the second weather type in the current environment of the target field of view is normal weather when the image quality analysis result is clear.

[0222] In some embodiments, the mode control module 84 may include:

[0223] a first mode control submodule, configured to, when the current weather type is severe weather, and the severe weather is rain or snow, control the infrared module to activate a heating and dehumidification function on the acquisition lens, and configure first image enhancement processing parameters so that the infrared module performs image enhancement processing on the raw infrared image subsequently acquired in real time according to the first image enhancement processing parameters; and / or,

[0224] The second mode control submodule is used to control the infrared module to start the dust removal function on the acquisition lens when the current weather type is severe weather and the severe weather is sandstorm weather, and configure the second image enhancement processing parameters so that the infrared module performs image enhancement processing on the original infrared image subsequently acquired in real time according to the second image enhancement processing parameters.

[0225] In some embodiments, the infrared image acquisition control device may further include:

[0226] The normal mode control module is used to control the infrared module to start the normal image processing mode when the current weather type is normal weather, so that the infrared module performs normal image processing on the original infrared images subsequently collected in real time.

[0227] In some embodiments, the mode control module 84 may specifically include:

[0228] a severe weather determination module, configured to determine that the current weather type is severe weather when the first weather type, the second weather type, and / or the third weather type are severe weather;

[0229] The enhancement processing module is used to control the infrared module to perform image enhancement processing on the original infrared image subsequently collected in real time according to the image enhancement parameters.

[0230] It should be noted that the infrared image acquisition and control device provided in the above embodiment, in implementing the infrared image acquisition and control process, is merely illustrated by the division of the aforementioned program modules. In actual applications, the aforementioned processing can be assigned to different program modules as needed, that is, the internal structure of the device can be divided into different program modules to complete all or part of the method steps described above. Furthermore, the infrared image acquisition and control device provided in the above embodiment and the infrared image acquisition and control method embodiment are based on the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0231] In another aspect of the embodiments of the present application, an infrared image acquisition and control device is provided. Figure 9 FIG. 1 shows a schematic diagram of the structure of an infrared image acquisition and control device provided by the present application. Figure 9 As shown, the infrared image acquisition and control device includes a processor 91 and a memory 92. The memory 92 stores a computer program that can be executed by the processor. When the computer program is executed by the processor, the infrared image acquisition and control method described in any embodiment of the present application is implemented. The infrared image acquisition and control device can achieve the same technical effect as the infrared image acquisition and control method provided in the aforementioned embodiment. To avoid repetition, they will not be described here.

[0232] The present application also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the computer program implements the various processes of the above-mentioned infrared image acquisition control method embodiment and can achieve the same technical effects. To avoid repetition, the details are not described here. The computer-readable storage medium is, for example, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0233] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. An infrared image acquisition control method, characterized in that: include: Obtaining sensor data representing a current weather condition collected by a predetermined sensor, and determining a first weather type in a current environment of a target field of view based on the sensor data; Obtain the original infrared image collected by the infrared module in real time for the target field of view; Performing an image quality analysis on the original infrared image based on the image detail layer of the original infrared image, and determining a second weather type under the current environment of the target field of view according to the image quality analysis result; wherein, performing the image quality analysis on the original infrared image based on the detail layer of the original infrared image includes: extracting a detail layer from the original infrared image, determining the number of first pixels in the detail layer whose absolute values of pixel values are not greater than a preset detail threshold; calculating a pixel mean of the original infrared image, and determining the number of second pixels in the original infrared image whose pixel values are less than the pixel mean, and the number of third pixels whose pixel values are less than a preset pixel value; obtaining an image quality analysis result of the original infrared image based on a difference between the number of first pixels and a first preset threshold, and a difference between the number of second pixels and the number of third pixels; Performing image recognition on the original infrared image using an image weather recognition model to determine a third weather type under the current environment of the target field of view; The current weather type is determined based on the first weather type, the second weather type, and the third weather type. When the current weather type is severe weather, the infrared module is controlled to start an image enhancement processing mode, and image enhancement processing parameters are configured so that the infrared module performs image enhancement processing on the original infrared images subsequently acquired in real time. The image enhancement processing parameters are configured, including: determining a weight based on a ratio of a mean of the absolute values of pixels in a detail layer to a preset total mean, and determining the image enhancement processing parameters based on a product of the weight and the image processing parameters in a conventional image processing mode. The preset total mean is calculated based on the mean of the absolute values of pixels in the detail layer of a plurality of original infrared images under conventional weather conditions within a historical time period.

2. The infrared image acquisition control method according to claim 1, characterized in that: The acquiring sensor data representing the current weather state collected by the set sensor, and determining the first weather type in the current environment of the target field of view according to the sensor data, includes: Acquire rain and snow sensing data collected by a rain and snow sensor, and determine whether a first weather type in an environment currently located in a target field of view is rain and snow weather according to the rain and snow sensing data.

3. The infrared image acquisition control method according to claim 1, characterized in that: The obtaining of the image quality analysis result of the original infrared image based on the difference between the number of the first pixels and the first preset threshold, and the difference between the number of the second pixels and the number of the third pixels, includes: When the number of the first pixels is greater than the first preset threshold and the number of the second pixels is not greater than the number of the third pixels, the image quality analysis result of the original infrared image is blurred.

4. The infrared image acquisition control method according to claim 1, characterized in that: The performing image quality analysis on the original infrared image based on the detail layer of the original infrared image further includes: Extracting detail layers from a plurality of first original infrared images collected by the infrared module within a current time period to obtain a plurality of first detail layers; Performing image absolute value conversion on each of the first detail layers to obtain a first absolute valued image corresponding to each of the first detail layers; Calculating a pixel mean for each first absolute value image to obtain a first pixel mean for each first absolute value image; An image quality analysis result is determined based on the magnitude of each first pixel mean value and a preset total mean value.

5. The infrared image acquisition control method according to claim 1, characterized in that: The determining, according to the image quality analysis result, the second weather type of the current environment of the target field of view includes: When the image quality analysis result is blurred, determining that the second weather type in the current environment of the target field of view is severe weather; When the image quality analysis result is clear, it is determined that the second weather type in the current environment of the target field of view is normal weather.

6. The infrared image acquisition control method according to claim 1, characterized in that: When the current weather type is severe weather, controlling the infrared module to start an image enhancement processing mode and configuring image enhancement processing parameters so that the infrared module performs image enhancement processing on a subsequent raw infrared image collected in real time, including: When the current weather type is severe weather, and the severe weather is rain or snow, controlling the infrared module to activate a heating and dehumidification function on the acquisition lens, and configuring first image enhancement processing parameters so that the infrared module performs image enhancement processing on the original infrared image subsequently acquired in real time according to the first image enhancement processing parameters; and / or, When the current weather type is severe weather and the severe weather is sandstorm weather, the infrared module is controlled to start the dust removal function for the acquisition lens, and the second image enhancement processing parameters are configured so that the infrared module performs image enhancement processing on the subsequent real-time acquired original infrared image according to the second image enhancement processing parameters.

7. An infrared image acquisition and control device, characterized in that: The method comprises a processor and a memory, wherein the memory stores a computer program executable by the processor, and when the computer program is executed by the processor, the infrared image acquisition control method according to any one of claims 1 to 6 is implemented.

8. An infrared image acquisition system, characterized in that: It includes an infrared module and the infrared image acquisition and control device as claimed in claim 7; The infrared module is used to collect and output infrared images of the target field of view.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by the controller, the infrared image acquisition control method according to any one of claims 1 to 6 is implemented.

Images