Display method, device and electronic rearview mirror system

Abstract

The present disclosure provides a display method, device and electronic rearview mirror system. Specifically, the display method comprises: acquiring a rear view image collected by a camera of the electronic rearview mirror system; determining whether the rear view image is a foggy image by using a pre-determined fog image determination model; in response to the rear view image being a foggy image, acquiring and determining a fog source causing the foggy image according to fog condition information of a corresponding region of the rear view image; in response to the fog source being lens fog, issuing a camera defogging signal; and in response to the fog source being environmental fog, performing defogging processing on the foggy image and issuing a display signal. In this way, the recognition of the foggy image and the determination of the matching processing mode for different fog sources are realized, the recognition of the object in the image is improved, and it is ensured that the electronic rearview mirror system can also realize accurate display under the condition of fogging, thereby improving the driving safety of the vehicle.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the field of automobile safety technology, and particularly relates to a display method and device and electronic rearview mirror system. BACKGROUND

[0002] With the continuous development of automobile electronic and electrical and camera technology, the application field of cameras gradually increases, and physical rearview mirrors have a tendency to be gradually replaced by electronic rearview mirror systems. Compared with traditional physical rearview mirrors, electronic rearview mirrors have many advantages: when it rains, the view will not be affected by rain hitting the glass window and the lens; when the external light is poor, the low-illumination function of the camera makes it easier to see objects; and the camera display rotates, and the like.

[0003] Even so, when the electronic rearview mirror system fogs, the objects are difficult to identify due to the fog blocking, which will also affect driving safety. SUMMARY

[0004] Therefore, the purpose of the present disclosure is to provide a display method, device and electronic rearview mirror system, to increase the image accuracy of the electronic rearview mirror system in the fogging condition and improve the driving safety.

[0005] To achieve the above purpose, in a first aspect, the present disclosure provides a display method applied to an electronic rearview mirror system, wherein the display method comprises:

[0006] acquiring a rearview image collected by a camera of the electronic rearview mirror system;

[0007] using a pre-determined fog image judgment model to determine whether the rearview image is a foggy image;

[0008] in response to the rearview image being a foggy image, acquiring and determining a fog source causing the foggy image according to fog condition information of a corresponding region of the rearview image;

[0009] in response to the fog source being a lens fog, issuing a camera defogging signal;

[0010] in response to the fog source being an environmental fog, performing defogging processing on the foggy image and issuing a display signal.

[0011] Further, the display method further comprises:

[0012] acquiring vehicle speed information;

[0013] in response to the vehicle speed information being greater than zero, issuing a camera defogging signal, performing defogging processing on the foggy image and issuing a display signal.

[0014] Further, the fog image judgment model comprises:

[0015] obtaining brightness and saturation of the image to be judged;

[0016] calculating a difference between the brightness and the saturation, and comparing the difference with a preset fog threshold value;

[0017] in response to the difference exceeding the preset fog threshold value, the image to be judged is a foggy image;

[0018] in response to the difference not exceeding the preset fog threshold value, the image to be judged is a normal image.

[0019] Further, the display method further comprises:

[0020] obtaining vehicle speed information;

[0021] adjusting the preset fog threshold value according to the vehicle speed information, wherein the preset fog threshold value and the vehicle speed information are negatively correlated.

[0022] Further, the display method further comprises:

[0023] obtaining a plurality of historical rearview images under foggy conditions and a plurality of historical rearview images under normal conditions;

[0024] extracting a vehicle body sub-image in the historical rearview images to form a training data set;

[0025] training an initial machine learning model through the training data set, and obtaining the foggy image judgment model after the training is completed.

[0026] Further, the step of performing de-fogging processing on the foggy image and issuing a display signal comprises:

[0027] processing the foggy image through a first logarithmic function to obtain an enhanced dark area image;

[0028] filtering the enhanced dark area image using a guided filter algorithm to obtain a filtered image;

[0029] performing automatic gain adjustment on the enhanced dark area image and the filtered image and fusing to obtain a gain image;

[0030] processing the gain image through a second logarithmic function to obtain a de-fogging image, wherein the second logarithmic function is used to compensate for the reduced brightness caused by the first logarithmic function.

[0031] Further, the step of performing automatic gain adjustment on the enhanced dark area image and the filtered image and fusing to obtain a gain image comprises:

[0032] The filtered image is subjected to first automatic gain adjustment to obtain a gain first sub-image;

[0033] The filtered image and the enhanced dark area image are fused and subjected to second automatic gain adjustment to obtain a gain second sub-image;

[0034] The gain first sub-image and the gain second sub-image are fused to obtain the gain image.

[0035] In a second aspect, the present disclosure further provides a display device applied to an electronic rearview mirror system, comprising:

[0036] An acquisition module configured to acquire a rearview image collected by a camera of the electronic rearview mirror system;

[0037] A judgment module configured to judge whether the rearview image is a foggy image by using a pre-determined foggy image judgment model;

[0038] A fog source analysis module configured to, in response to the rearview image being a foggy image, acquire and determine a fog source causing the foggy image according to fog condition information of a corresponding region of the rearview image;

[0039] A processing module configured to, in response to the fog source being lens fog, issue a camera defogging signal;

[0040] In response to the fog source being environmental fog, perform defogging processing on the foggy image and issue a display signal.

[0041] Further, the display device further comprises:

[0042] A training module configured to acquire a plurality of historical rearview images under foggy conditions and a plurality of historical rearview images under normal conditions;

[0043] Extract a vehicle body sub-image in the historical rearview images to constitute a training data set;

[0044] Train an initial machine learning model through the training data set, and obtain the foggy image judgment model after the training is completed.

[0045] In a third aspect, the present disclosure further provides an electronic rearview mirror system comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the method according to any one of the preceding aspects when executing the program.

[0046] It can be seen from the above that the display method, device and electronic rearview mirror system provided by the present disclosure, by acquiring a rear view image collected by a camera of the electronic rearview mirror system; using a pre-determined fog image judgment model to determine whether the rear view image is a foggy image; in response to the rear view image being a foggy image, acquiring and determining the fog source causing the foggy image according to the fog condition information of the corresponding area of the rear view image; in response to the fog source being lens fog, issuing a camera defogging signal; in response to the fog source being environmental fog, performing defogging processing on the foggy image and issuing a display signal. In this way, the recognition of the foggy image and the determination of the matching processing mode for different fog sources are realized, the recognition degree of the objects in the image is improved, and it is ensured that the electronic rearview mirror system can also realize accurate display under the condition of fogging, thereby improving the driving safety of the vehicle. In addition, the whole process is automatically operated without the need for the driver to operate, which avoids the distraction of the driver due to fogging, and further ensures the driving safety. BRIEF DESCRIPTION OF DRAWINGS

[0047] In order to more clearly illustrate the technical solutions in the present disclosure or the related art, the drawings needed to be used in the embodiments or the related art description will be briefly introduced. Obviously, the drawings in the following description are only embodiments of the present disclosure, and other drawings can also be obtained by those skilled in the art without creative labor.

[0048] Figure 1 A flowchart of a display method provided by an embodiment of the present disclosure is shown in the figure.

[0049] Figure 2 A flowchart of constructing a fog image judgment model provided by an embodiment of the present disclosure is shown in the figure.

[0050] Figure 3 A flowchart of a defogging method provided by an embodiment of the present disclosure is shown in the figure.

[0051] Figure 4 A partial structure diagram of a display device provided by an embodiment of the present disclosure is shown in the figure.

[0052] Figure 5 A partial structure diagram of an electronic rearview mirror system provided by an embodiment of the present disclosure is shown in the figure. DETAILED DESCRIPTION

[0053] In order to make the purpose, technical solutions and advantages of the present disclosure more clear, the present disclosure will be further described in detail below with reference to specific embodiments and drawings.

[0054] It should be noted that the technical terms or scientific terms used in the embodiments of the present disclosure should be the general meanings understood by those skilled in the art to which the present disclosure belongs, unless otherwise defined. The terms "first", "second", and similar words used in the embodiments of the present disclosure do not represent any order, number or importance, but are only used to distinguish different components. The terms "include" or "contain" and similar words mean that the elements or objects before the words cover the elements or objects listed after the words and their equivalents, and do not exclude other elements or objects. The terms "connect" or "connected" and similar words are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect.

[0055] When the electronic rearview mirror system is foggy, it is difficult to identify objects due to the obstruction of fog, which will also affect driving safety. For environmental fogging, such as after the rain, in the morning of autumn and winter seasons, the fog is diffused in the atmosphere, and it is impossible to improve the identification of objects by wiping the camera or display screen. For camera fogging, such as from the underground garage to the ground road in summer, the fog on the camera needs to be removed. However, for the electronic rearview mirror system, it aims to maximize the restoration of the real-world object image. In the case of fog, the image with fog will also be seen on the display screen, which does not distinguish whether the image has fog, and even less distinguishes the source of the fog, so it is impossible to take targeted solutions, thereby causing traffic hazards.

[0056] Therefore, for this case, the present disclosure proposes a display method applied to an electronic rearview mirror system to improve the identification of objects in the rearview mirror image, and ultimately achieve the purpose of improving driving safety.

[0057] Please refer to Figure 1 , the display method comprises:

[0058] S101: acquiring a rear view image collected by a camera of the electronic rearview mirror system;

[0059] Here, the electronic rearview mirror system includes a camera and a display screen. The camera is located at the lower side of the front of the front row window of the vehicle, which is basically the same as the position of the physical rearview mirror. The display screen is usually located inside the driver's cabin for the convenience of the driver to observe, which is not specifically limited here.

[0060] S102: determining whether the rear view image is a foggy image by using a pre-determined fog image judgment model;

[0061] It should be noted that the pre-determined fog image judgment model can be a fog image judgment rule or a pre-trained fog image judgment model.

[0062] In real scenarios, fog can be classified according to horizontal visibility distance. For example, horizontal visibility distance is between 1-10 kilometers, which is light fog; horizontal visibility distance is less than 1 kilometer, which is fog; horizontal visibility distance is between 200-500 meters, which is heavy fog.

[0063] As understood by those skilled in the art, the influence of different levels of fog on the driver's judgment of objects in the real world is different. Therefore, the foggy image here should be understood as a rearview mirror image that affects the driver's judgment of objects in the real world, and should not be understood as a rearview mirror image formed in any foggy situation.

[0064] S1031: in response to the rearview image being a normal image, issuing a display signal;

[0065] Here, the aforementioned foggy image corresponds to the normal image, which should be understood as a rearview mirror image that does not affect the driver's judgment of objects in the real world, and should not be understood as a rearview mirror image that does not include any fog.

[0066] For normal images, a display signal can be issued directly. Here, the display signal can be used to display the rearview mirror image on the display screen.

[0067] S1032: in response to the rearview image being a foggy image, obtaining and determining the fog source causing the foggy image according to the fog information of the corresponding area of the rearview image;

[0068] Here, the area fog information can be obtained by networking to obtain weather information, or by a vehicle-mounted fog sensor, which is not specifically limited here.

[0069] It should be noted that the fog source of the foggy image is the environmental fog and the lens fog. Among them, the environmental fog refers to a large air humidity and a fog in the environmental space; the lens fog refers to a fog on the camera. If the area fog information shows that the environmental space has fog, the fog source is the environmental fog; otherwise, the fog source is the lens fog.

[0070] It should be understood that the fog source can exist both environmental fog and lens fog, and since the environmental fog cannot be eliminated, it can be processed according to the environmental fog.

[0071] Here, since the fog information is complex, it has the characteristics of emission and regionality, especially in mountainous areas, which is more obvious. Taking the rearview image as the starting point, first judging the rearview image to obtain the area fog information, not only can effectively monitor the lens fog, but also can obtain the area fog information specifically, avoid the interference of blind acquisition of fog information on the display method, and effectively guarantee the stability and reliability of the display method.

[0072] S1041: in response to the fog source being lens fog, issuing a camera defogging signal;

[0073] Here, the electronic rearview mirror system includes a camera defogging component, such as a heating tube. When the controller of the heating tube receives the camera defogging signal, the camera can be defogged by starting the heating tube.

[0074] It should be understood that the heating tube here is only an example and is not a limitation of the camera defogging component. Other defogging methods and components can also be used by those skilled in the art, which will not be described in detail here.

[0075] S1042: in response to the fog source being environmental fog, performing defogging processing on the foggy image and issuing a display signal.

[0076] It should be noted that the method of removing processing can be a defogging algorithm based on image enhancement, a defogging algorithm based on image restoration, or a defogging algorithm based on deep learning, etc., which will not be described in detail here.

[0077] According to the defogging processed image, a display signal is issued to display it on the display screen, which helps the driver to identify the real world objects and improves the driving safety.

[0078] As can be seen, in this way, the recognition of the foggy image and the determination of the matching processing method for different fog sources are realized, the recognition degree of the objects in the image is improved, and it is ensured that the electronic rearview mirror system can also realize accurate display under the condition of fogging, and the vehicle driving safety is improved. In addition, the whole process is automatically operated without the need for the driver to operate, which avoids the distraction of the driver due to fogging, and further ensures the driving safety.

[0079] In some embodiments, the display method further comprises:

[0080] obtaining vehicle speed information;

[0081] Here, the way to obtain the vehicle speed information is prior art, which will not be described here.

[0082] In response to the vehicle speed information being greater than zero, a camera defogging signal is issued and the foggy image is defogged and a display signal is issued.

[0083] Camera defogging takes time, which can be a few seconds or a few minutes. When the vehicle is in a driving state, defogging processing is performed on the foggy image at the same time and a display signal is issued, which helps to ensure safe driving during defogging.

[0084] In some embodiments, the fog image judgment model comprises:

[0085] obtaining the brightness and saturation of the image to be judged;

[0086] calculating a difference between the brightness and the saturation, comparing the difference with a preset fog threshold value;

[0087] in response to the difference exceeding the preset fog threshold value, the image to be judged is a fog image;

[0088] in response to the difference not exceeding the preset fog threshold value, the image to be judged is a normal image.

[0089] It should be noted that the concentration of fog is in a positive relationship with the difference between the brightness and the saturation, the greater the difference between the brightness and the saturation, the greater the concentration of fog, the lower the horizontal visibility; on the contrary, the smaller the difference between the brightness and the saturation, the smaller the concentration of fog, the higher the horizontal visibility.

[0090] For example, the difference between the brightness and the saturation of an image of a sunny day is close to zero, for example, 0.18%, while the difference between the brightness and the saturation of an image of a foggy day is greater, for example, 6.36%.

[0091] Optionally, the preset fog threshold value can be 3%, 5%, etc., which will not be listed here. Those skilled in the art can adjust the preset fog threshold value according to the requirement for visibility during driving.

[0092] Further, the display method further comprises:

[0093] obtaining vehicle speed information;

[0094] adjusting the preset fog threshold value according to the vehicle speed information; wherein the preset fog threshold value and the vehicle speed information are in a negative correlation.

[0095] It should be understood that the higher the vehicle speed, the higher the requirement for horizontal visibility; the lower the vehicle speed, the lower the requirement for horizontal visibility.

[0096] When the vehicle speed increases, the preset fog threshold value is reduced, thereby reducing the accuracy of judging the fog image, so that part of the rear view image suitable for low-speed driving but not suitable for high-speed driving is judged as a fog image, which is displayed after being processed by the defogging process, which is conducive to ensuring the safety of high-speed driving.

[0097] On the contrary, when the vehicle speed decreases, the preset fog threshold value is increased, thereby enhancing the accuracy of judging the fog image, so that part of the rear view image judged as a fog image under high-speed driving conditions is processed as a normal image, which can save computing resources while ensuring driving safety.

[0098] In some embodiments, as shown in Figure 2 the display method further comprises:

[0099] S201: acquire a plurality of historical rear view images under foggy conditions and a plurality of historical rear view images under normal conditions;

[0100] Here, the foggy condition refers to a state that interferes with the driver's recognition of objects in the real world, rather than any foggy state. Correspondingly, the normal condition refers to a state that does not interfere with the driver's recognition of objects in the real world, not specifically referring to a sunny state, but also to a light fog state.

[0101] S202: extract the vehicle body sub-image in the historical rear view image to form a training data set;

[0102] It should be noted that the objects in the historical rear view image are diverse, and the extraction of the vehicle body sub-image can reduce the difficulty of training and improve the training efficiency and accuracy.

[0103] S203: train an initial machine learning model through the training data set, and obtain the fog image judgment model after training.

[0104] Here, the initial machine learning model can be a neural network model, such as LeNet model, AlexNet model, GoogLeNet model, etc.

[0105] Further, the vehicle body sub-image in the rear view image is input into the fog image judgment model, so as to realize the judgment of whether the rear view image is a foggy image.

[0106] As an alternative embodiment, S201: acquire a plurality of historical rear view images under foggy conditions and a plurality of historical rear view images under normal conditions, can be replaced by: acquire a plurality of historical rear view images under different speeds under foggy conditions and a plurality of historical rear view images under different speeds under normal conditions. At this time, the fog image judgment model considers the speed factor.

[0107] When judging the rear view image, the speed information also needs to be acquired, and the fog image judgment model is used to judge the rear view image under the speed condition.

[0108] In some embodiments, the present disclosure also provides a specific de-fogging method.

[0109] Please refer to Figure 3 , the step of de-fogging processing the foggy image and sending a display signal comprises:

[0110] S301: process the foggy image through a first logarithmic function to obtain an enhanced dark area image; such processing can remove the interfering signal, which is beneficial to the processing of S302 step, and the overall effect of the picture will be dark.

[0111] S302: filtering the enhanced dark area image by using a guided filter algorithm to obtain a filtered image; in this way, a clear outline of the image can be obtained.

[0112] It should be noted that for an input image p, an output image q is obtained by filtering through a guided image I, wherein p and I are both inputs of the algorithm.

[0113] For example, the guided image can be the same as the enhanced dark area image, and in this case, the algorithm becomes an edge-preserving filter.

[0114] S303: performing automatic gain adjustment on the enhanced dark area image and the filtered image and fusing to obtain a gain image; by automatic gain control, the brightness of the dark area is enhanced, and image flickering caused by image processing adjustment overshoot can be prevented.

[0115] S304: processing the gain image by using a second logarithmic function to obtain a defogging image; the second logarithmic function is used to compensate for the reduced brightness caused by the first logarithmic function. Finally, the image exposure is improved, the overall dark image in S301 is compensated, and the overall brightness enhancement effect is achieved.

[0116] In some embodiments, the step of performing automatic gain adjustment on the enhanced dark area image and the filtered image and fusing to obtain a gain image comprises:

[0117] performing first automatic gain adjustment on the filtered image to obtain a gain first sub-image; the first automatic gain adjustment can be Boost gain / Tone curve, which is not limited herein.

[0118] performing second automatic gain adjustment on the filtered image and the enhanced dark area image after fusing to obtain a gain second sub-image; the second automatic gain adjustment can be Gain / Coring, which is not limited herein.

[0119] fusing the gain first sub-image and the gain second sub-image to obtain the gain image.

[0120] By using multiple automatic gain and pattern fusion, the effect of automatic gain can be effectively guaranteed.

[0121] It should be noted that the method of the embodiments of the present disclosure can be executed by a single device, such as a computer or a server, etc. The method of the embodiments can also be applied to a distributed scenario, and be completed by multiple devices cooperating with each other. In the case of such a distributed scenario, one of the multiple devices can only execute one or more steps in the method of the embodiments of the present disclosure, and the multiple devices can interact with each other to complete the method.

[0122] It should be noted that some embodiments of the present disclosure have been described above. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in a different order and still achieve desirable results. Additionally, the processes depicted in the accompanying figures do not necessarily require the particular order shown or sequential order in order to achieve the desired results. In certain implementations, multitasking and parallel processing can be advantageous.

[0123] Based on the same inventive concept, the present disclosure also provides a display device corresponding to the method of any of the above embodiments.

[0124] Reference Figure 4 , the display device is applied to an electronic rearview mirror system, and includes:

[0125] The acquisition module 401 is configured to acquire a rearview image collected by a camera of the electronic rearview mirror system;

[0126] The determination module 402 is configured to determine whether the rearview image is a foggy image by using a pre-determined foggy image determination model;

[0127] The fog source analysis module 403 is configured to, in response to the rearview image being a foggy image, acquire and determine a fog source causing the foggy image according to fog condition information of a corresponding region of the rearview image;

[0128] The processing module 404 is configured to, in response to the fog source being lens fog, issue a camera defogging signal;

[0129] in response to the fog source being environmental fog, perform defogging processing on the foggy image and issue a display signal.

[0130] In some embodiments, the acquisition module 401 is further configured to acquire vehicle speed information;

[0131] The processing module is further configured to, in response to the vehicle speed information being greater than zero, issue a camera defogging signal, perform defogging processing on the foggy image, and issue a display signal.

[0132] In some embodiments, the foggy image determination model includes:

[0133] obtaining brightness and saturation of the image to be judged;

[0134] calculating a difference between the brightness and the saturation, and comparing the difference with a preset fog threshold;

[0135] in response to the difference exceeding the preset fog threshold, the image to be judged is a foggy image;

[0136] in response to the difference not exceeding the preset fog threshold, the image to be judged is a normal image.

[0137] In some embodiments, further comprising:

[0138] the obtaining module 401 is further configured to obtain vehicle speed information;

[0139] the judging module 402 is further configured to adjust the preset fog threshold according to the vehicle speed information; wherein the preset fog threshold and the vehicle speed information are negatively correlated.

[0140] In some embodiments, the display device further comprises:

[0141] the training module is configured to: obtain historical rearview images under foggy conditions and historical rearview images under normal conditions;

[0142] extract vehicle body sub-images in the historical rearview images to form a training data set;

[0143] train an initial machine learning model through the training data set, and obtain the foggy image judgment model after the training is completed.

[0144] In some embodiments, the processing module 404 is configured to:

[0145] process the foggy image through a first logarithmic function to obtain an enhanced dark area image;

[0146] filter the enhanced dark area image through a guided filter algorithm to obtain a filtered image;

[0147] perform automatic gain adjustment on the enhanced dark area image and the filtered image and fuse them to obtain a gain image;

[0148] process the gain image through a second logarithmic function to obtain a defogging image; wherein the second logarithmic function is used to compensate for the reduced brightness caused by the first logarithmic function.

[0149] In some embodiments, the processing module 404 is configured to:

[0150] performing first automatic gain adjustment on the filtered image to obtain a gain first sub-image;

[0151] performing second automatic gain adjustment on the fusion of the filtered image and the enhanced dark area image to obtain a gain second sub-image;

[0152] performing fusion on the gain first sub-image and the gain second sub-image to obtain the gain image.

[0153] For the convenience of description, the above apparatus is described in various modules in terms of functions. Of course, the functions of the modules can be implemented in one or more software and / or hardware when implementing the present disclosure.

[0154] The apparatus of the above embodiments is used to implement the corresponding display method in any of the above embodiments, and has the beneficial effects of the corresponding method embodiments, which are not described here again.

[0155] Based on the same inventive concept, the present disclosure also provides an electronic rearview mirror system corresponding to any of the above method embodiments, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the display method of any of the above embodiments when executing the program.

[0156] Figure 5 A more specific part of the hardware structure of the electronic rearview mirror system provided in the embodiment is shown, which can include a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040 and a bus 1050. The processor 1010, the memory 1020, the input / output interface 1030 and the communication interface 1040 are connected to each other through the bus 1050 for communication within the device.

[0157] The processor 1010 can be implemented by a general CPU (Central Processing Unit, central processor), a microprocessor, an ASIC (Application Specific Integrated Circuit, application specific integrated circuit) or one or more integrated circuits, etc., for executing related programs to implement the technical solutions provided by the embodiments of the present disclosure.

[0158] The memory 1020 can be implemented in the form of a ROM (Read Only Memory), a RAM (Random Access Memory), a static storage device, a dynamic storage device, etc. The memory 1020 can store an operating system and other application programs, and when the technical solutions provided in the embodiments of the present specification are implemented by software or firmware, the related program codes are stored in the memory 1020 and are called and executed by the processor 1010.

[0159] The input / output interface 1030 is configured to connect an input / output module to realize information input and output. The input / output module can be configured as a component in the device (not shown in the figure) or can be externally connected to the device to provide corresponding functions. The input device can include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output device can include a display, a speaker, a vibrator, an indicator light, etc.

[0160] The communication interface 1040 is configured to connect a communication module (not shown in the figure) to realize communication interaction between the device and other devices. The communication module can realize communication through a wired manner (such as a USB, a network cable, etc.) or through a wireless manner (such as a mobile network, WIFI, Bluetooth, etc.).

[0161] The bus 1050 includes a channel for transmitting information between various components (such as the processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040) of the device.

[0162] It should be noted that although the above device only shows the processor 1010, the memory 1020, the input / output interface 1030, the communication interface 1040, and the bus 1050, in the specific implementation process, the device can also include other components necessary for normal operation. In addition, those skilled in the art can understand that the above device can also only include components necessary for implementing the solutions of the embodiments of the present specification, and does not have to include all the components shown in the figure.

[0163] The electronic rearview mirror system of the above embodiments is used to implement the corresponding display method in any of the above embodiments, and has the beneficial effects of the corresponding method embodiments, which are not described here again.

[0164] Based on the same inventive concept, the present disclosure also provides a non-transitory computer-readable storage medium storing computer instructions for causing the computer to execute the display method according to any of the above embodiments.

[0165] The computer readable media of the embodiments can include permanent and non-permanent, removable and non-removable media, which can be implemented by any method or technology to store information. The information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage device, or any other non-transmission medium that can be used to store information accessible to a computing device.

[0166] The storage medium of the above embodiments stores computer instructions for causing the computer to perform the display method as described in any of the above embodiments, and has the beneficial effects of the corresponding method embodiments, which are not described here again.

[0167] Those skilled in the art should understand that the discussion of any of the above embodiments is only exemplary and is not intended to imply that the scope of the present disclosure (including claims) is limited to these examples; under the idea of the present disclosure, the above embodiments or technical features between different embodiments can also be combined, the steps can be implemented in any order, and there are many other changes of different aspects of the embodiments of the present disclosure as described above. In order to be brief, they are not provided in detail.

[0168] In addition, in order to simplify the description and discussion, and so as not to make the embodiments of the present disclosure difficult to understand, the well-known power / ground connections of integrated circuit (IC) chips and other components can or can not be shown in the provided drawings. In addition, the devices can be shown in the form of block diagrams in order to avoid making the embodiments of the present disclosure difficult to understand, and this also takes into account the fact that the details of the implementation of these block diagram devices are highly dependent on the platform to be implemented the embodiments of the present disclosure (i.e. these details should be fully within the understanding of those skilled in the art). Where specific details (e.g. circuits) are set forth in order to describe an exemplary embodiment of the present disclosure, it will be apparent to those skilled in the art that the embodiments of the present disclosure can be implemented without these specific details or with variations on these specific details. Therefore, these descriptions should be considered illustrative rather than limiting.

[0169] While the present disclosure has been described in connection with certain embodiments thereof, many modifications, substitutions, and variations will be apparent to those of ordinary skill in the art from the foregoing description. For instance, other memory architectures (e.g., dynamic RAM (DRAM)) can use the embodiments discussed.

[0170] Embodiments of the disclosure are intended to cover all such alternatives, modifications, and variations as falling within the broad scope of the appended claims. Accordingly, any one or more of the above-described embodiments can be combined with any one or more of the above-described embodiments in any manner within the scope of the disclosure.

Claims

1. A display method applied to an electronic rearview mirror system, wherein, The display method comprises: obtaining a rear view image collected by a camera of the electronic rearview mirror system; determining whether the rear view image is a foggy image by using a pre-determined foggy image determination model; in response to the rear view image being a foggy image, obtaining and determining a fog source causing the foggy image according to fog condition information of a corresponding region of the rear view image; in response to the fog source being lens fog, issuing a camera defogging signal; in response to the fog source being environmental fog, performing defogging processing on the foggy image and issuing a display signal; wherein the step of performing defogging processing on the foggy image and issuing a display signal comprises: processing the foggy image by a first logarithmic function to obtain an enhanced dark region image; filtering the enhanced dark region image by using a guided filter algorithm to obtain a filtered image; performing automatic gain adjustment on the enhanced dark region image and the filtered image and fusing to obtain a gain image; processing the gain image by a second logarithmic function to obtain a defogged image; wherein the second logarithmic function is used to compensate for the reduced brightness caused by the first logarithmic function.

2. The display method according to claim 1, wherein, The display method further comprises: obtaining vehicle speed information; in response to the vehicle speed information being greater than zero, issuing a camera defogging signal while performing defogging processing on the foggy image and issuing a display signal.

3. The display method according to claim 1, wherein The foggy image determination model comprises: obtaining brightness and saturation of a to-be-determined image; calculating a difference value between the brightness and the saturation, and comparing the difference value with a pre-set foggy threshold value; in response to the difference value exceeding the pre-set foggy threshold value, the to-be-determined image is a foggy image; in response to the difference value not exceeding the pre-set foggy threshold value, the to-be-determined image is a normal image.

4. The display method according to claim 3, wherein The display method further comprises: obtaining vehicle speed information; adjusting the pre-set foggy threshold value according to the vehicle speed information; wherein the pre-set foggy threshold value and the vehicle speed information are negatively correlated.

5. The display method according to claim 1, wherein The display method further comprises: obtaining historical rear view images under a plurality of foggy conditions and historical rear view images under a plurality of normal conditions; extracting vehicle body sub-images in the historical rear view images to form a training data set; training an initial machine learning model by using the training data set, and obtaining the foggy image determination model after the training is completed.

6. The display method according to claim 1, wherein The step of performing automatic gain adjustment on the enhanced dark region image and the filtered image and fusing to obtain a gain image comprises: performing first automatic gain adjustment on the filtered image to obtain a gain first sub-image; performing second automatic gain adjustment on the filtered image and the enhanced dark region image after fusing to obtain a gain second sub-image; fusing the gain first sub-image and the gain second sub-image to obtain the gain image.

7. A display device applied to an electronic rearview mirror system, comprising: an obtaining module configured to obtain a rear view image collected by a camera of the electronic rearview mirror system; a determining module configured to determine whether the rear view image is a foggy image by using a pre-determined foggy image determination model; The fog source analysis module is configured to, in response to the rear view image being a foggy image, acquire and determine, according to fog condition information of a corresponding region of the rear view image, a fog source causing the foggy image; The processing module is configured to, in response to the fog source being lens fog, issue a camera defogging signal; in response to the fog source being environmental fog, perform defogging processing on the foggy image and issue a display signal; The function processing module processes the foggy image through a first logarithmic function to obtain an enhanced dark region image; The filter module filters the enhanced dark region image using a guided filter algorithm to obtain a filtered image; The adjustment fusion module automatically adjusts and fuses the enhanced dark region image and the filtered image to obtain a gain image; The function compensation module processes the gain image through a second logarithmic function to obtain a defogged image; wherein the second logarithmic function is used to compensate for the reduced brightness caused by the first logarithmic function.

8. The display device of claim 7, wherein, The display device further comprises: The training module is configured to acquire historical rear view images under several foggy conditions and historical rear view images under several normal conditions; extracts body sub-images in the historical rear view images to form a training data set; train an initial machine learning model through the training data set, and obtain the foggy image judgment model after the training is completed.

9. An electronic rearview mirror system comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the computer program comprising: The processor implements the method of any one of claims 1 to 6 when executing the program.

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