Method, device, equipment and medium for removing water mist from rearview mirror

Abstract

The present application discloses a method, device, computer equipment and computer-readable storage medium for removing water mist from a rearview mirror. The method comprises the following steps: acquiring an image captured by a rearview mirror camera; processing the acquired image to obtain a mean square error of the corresponding image; and judging whether to heat the rearview mirror based on the obtained mean square error, so as to achieve heating of the rearview mirror when water mist exists on the rearview mirror, so as to evaporate the water mist on the rearview mirror and the rearview mirror camera, thereby ensuring that the rearview mirror camera can clearly capture the environment behind the vehicle, and further ensuring that the driver can observe the clear environment behind the vehicle captured by the camera through the rearview mirror, thereby improving the safety of vehicle driving.

Description

Technical Field

[0001] The present application relates to the technical field of lens mist control, and in particular to a method, device, computer equipment, and computer-readable storage medium for removing water and mist from a rearview mirror. Background Art

[0002] The rearview mirror is an important structure in the vehicle. Drivers often use the rearview mirror to observe the surrounding environment while driving. Therefore, the rearview mirror is of great significance to ensuring vehicle driving safety.

[0003] Traditional rearview mirrors are mechanical, consisting of a frame and a reflector, which reflect the environment behind the vehicle for the driver to observe. With the development of intelligent vehicles, rearview mirrors have also evolved from mechanical mirrors to digital mirrors. Digital mirrors primarily use cameras to capture the environment behind the vehicle, which is then displayed on a monitor for the driver to observe. This camera-captured rearview environment information can also serve as a basis for intelligent driving control.

[0004] In rainy weather or high humidity, the camera lens can easily get wet, which can cause the camera to not clearly capture the environment behind the vehicle, and the monitor to not clearly display the rear environment. This can easily lead to the driver being unable to accurately judge the rear situation based on the monitor display, which can cause traffic accidents.

[0005] Therefore, it is a technical problem that needs to be solved urgently to enable the rearview mirror camera to clearly capture the rear environment in rainy weather or in an environment with high air humidity. Summary of the Invention

[0006] The main purpose of this application is to provide a method, device, computer equipment and computer-readable storage medium for removing water mist from a rearview mirror, aiming to solve the technical problem that a rearview mirror camera cannot clear the rear environment in rainy weather or an environment with high air humidity.

[0007] In a first aspect, the present application provides a method for removing mist from a rearview mirror, the method comprising the following steps:

[0008] Acquire the image captured by the rearview mirror camera;

[0009] Processing the acquired image to obtain the mean square error of the corresponding image;

[0010] Whether to heat the rearview mirror is determined based on the obtained mean square error.

[0011] In some embodiments, determining whether to heat the rearview mirror based on the obtained mean square error specifically includes the following steps:

[0012] If the obtained mean square error is greater than a set first mean square error threshold, heating the rearview mirror;

[0013] If the obtained mean square error is less than a set second mean square error threshold, heating the rearview mirror is stopped;

[0014] The first mean square error threshold is greater than the second mean square error threshold.

[0015] In some embodiments, the specific steps of setting the first mean square error threshold include:

[0016] Acquire M first images, and determine the mean square error of each first image;

[0017] Calculating an average mean square error of the M first images according to the mean square error of each first image;

[0018] Setting the average mean square error of the M first images as the first mean square error threshold;

[0019] Wherein, the first image is acquired in a rainy and humid environment: or,

[0020] The specific steps of setting the second mean square error threshold include:

[0021] Acquire N second images, and determine the mean square error of each second image;

[0022] Calculating an average mean square error of N second images according to the mean square error of each second image;

[0023] Setting the average mean square error of N second images as the second mean square error threshold;

[0024] The second image is acquired in a rainless and dry environment.

[0025] In some embodiments, the rearview mirror is heated by a heating wire disposed in the rearview mirror camera.

[0026] In some embodiments, processing the acquired image to obtain the mean square error of the corresponding image specifically includes the following steps:

[0027] Calculate the mean square error of the R channel, G channel and B channel in the image respectively;

[0028] A weighted calculation is performed on the mean square errors of the R channel, the G channel, and the B channel to obtain the mean square error of the image.

[0029] In some embodiments, after acquiring the image captured by the rearview mirror camera and before processing the acquired image to obtain the mean square error of the corresponding image, the following steps are further included:

[0030] The image is preprocessed using the Laplacian operator.

[0031] In some embodiments, acquiring the image captured by the rearview mirror camera specifically includes the following steps:

[0032] The images captured by the rearview mirror camera are sequentially acquired at preset time intervals.

[0033] In a second aspect, the present application further provides a device for removing water mist from a rearview mirror, the device comprising:

[0034] An image acquisition module, which is used to acquire images captured by the rearview mirror camera;

[0035] A mean square error calculation module is used to process the acquired image to obtain the mean square error of the corresponding image;

[0036] The heating control module is used to determine whether to heat the rearview mirror according to the obtained mean square error.

[0037] In some embodiments, the heating control module is further configured to:

[0038] If the obtained mean square error is greater than a set first mean square error threshold, heating the rearview mirror;

[0039] If the obtained mean square error is less than a set second mean square error threshold, heating the rearview mirror is stopped;

[0040] The first mean square error threshold is greater than the second mean square error threshold.

[0041] In some embodiments, the device for removing water mist from a rearview mirror is further used to:

[0042] Acquire M first images, and determine the mean square error of each first image;

[0043] Calculating an average mean square error of the M first images according to the mean square error of each first image;

[0044] Setting the average mean square error of the M first images as the first mean square error threshold;

[0045] Wherein, the first image is acquired in a rainy and humid environment: or,

[0046] Acquire N second images, and determine the mean square error of each second image;

[0047] Calculating an average mean square error of N second images according to the mean square error of each second image;

[0048] Setting the average mean square error of N second images as the second mean square error threshold;

[0049] The second image is acquired in a rainless and dry environment.

[0050] In some embodiments, the heating control module is further configured to heat the rearview mirror via a heating wire disposed in the rearview mirror camera.

[0051] In some embodiments, the mean square error calculation module is further configured to:

[0052] Calculate the mean square error of the R channel, G channel and B channel in the image respectively;

[0053] A weighted calculation is performed on the mean square errors of the R channel, the G channel, and the B channel to obtain the mean square error of the image.

[0054] In some embodiments, the device for removing water mist from a rearview mirror is further used to:

[0055] After acquiring the image captured by the rearview mirror camera, and before processing the acquired image to obtain the mean square error of the corresponding image, the image is pre-processed using a Laplace operator.

[0056] In some embodiments, the image acquisition module is further configured to:

[0057] The images captured by the rearview mirror camera are sequentially acquired at preset time intervals.

[0058] In a third aspect, the present application also provides a computer device, comprising a processor, a memory, and a computer program stored in the memory and executable by the processor, wherein when the computer program is executed by the processor, the steps of a method for removing water mist from a rearview mirror as described above are implemented.

[0059] In a fourth aspect, the present application also provides a computer-readable storage medium, on which a computer program is stored, wherein when the computer program is executed by a processor, the steps of the method for removing water mist from a rearview mirror as described above are implemented.

[0060] The present application provides a method, apparatus, computer device and computer-readable storage medium for removing water mist from a rearview mirror. The method comprises the following steps: acquiring an image captured by a rearview mirror camera; processing the acquired image to obtain a mean square error of the corresponding image; and determining whether to heat the rearview mirror based on the obtained mean square error. The method heats the rearview mirror when water mist is present on the rearview mirror, thereby evaporating the water mist on the rearview mirror and the rearview mirror camera, ensuring that the rearview mirror camera can clearly capture the environment behind the vehicle, and that the driver can clearly observe the clear environment behind the vehicle captured by the camera through the rearview mirror, thereby improving vehicle driving safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0062] Figure 1 A schematic flow chart of a method for removing water mist from a rearview mirror provided in an embodiment of the present application;

[0063] Figure 2 for Figure 1 A flowchart of the sub-step of determining whether to heat the rearview mirror according to the obtained mean square error;

[0064] Figure 3 A schematic block diagram of a device for removing mist from a rearview mirror provided in an embodiment of the present application;

[0065] Figure 4 This is a schematic block diagram of the structure of a computer device involved in one embodiment of the present application.

[0066] The realization of the objectives, functional features and advantages of this application will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0067] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0068] The flowcharts shown in the accompanying drawings are for illustrative purposes only and do not necessarily include all contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may be decomposed, combined, or partially merged, so the actual execution order may vary depending on the actual situation.

[0069] The present invention provides a method, device, computer device, and computer-readable storage medium for removing water mist from a rearview mirror. The device for removing water mist from a rearview mirror can be applied to a computer device, such as a vehicle controller, an onboard computer, or the like.

[0070] The following describes some embodiments of the present application in detail with reference to the accompanying drawings. In the absence of conflict, the following embodiments and features therein may be combined with each other.

[0071] Please refer to Figure 1 , Figure 1 A schematic flow chart of a method for removing mist from a rearview mirror provided in an embodiment of the present application.

[0072] like Figure 1 As shown, the method includes steps S1 to S3.

[0073] Step S1: Acquire an image captured by a rearview mirror camera.

[0074] Characteristically, since the camera in the digital rearview mirror captures the environment behind the vehicle in the form of video, and the images captured by the rearview mirror are photographic images, individual images can be extracted from the video captured by the camera at preset time intervals. For example, a frame can be extracted from the latest video captured by the camera every 5 seconds as the captured image.

[0075] Step S2: Process the acquired image to obtain the mean square error of the corresponding image.

[0076] In some embodiments, after acquiring the image captured by the rearview mirror camera, before processing the acquired image to obtain the mean square error of the corresponding image, the method further includes: pre-processing the image using a Laplace operator to improve the sharpness of the image.

[0077] Specifically, the mean square error of the R, G, and B channels of the image is calculated separately, and the mean square error of the R, G, and B channels is weighted with different weights to obtain the mean square error of the image. Here, the R, G, and B channels represent the red, green, and blue color channels in the image, respectively.

[0078] As a preferred implementation, the mean square error of the image is weightedly calculated according to the R channel accounting for 40%, the G channel accounting for 30%, and the B channel accounting for 30% to obtain the final mean square error of the image.

[0079] Step S3: Determine whether to heat the rearview mirror based on the obtained mean square error.

[0080] It is worth noting that the mean square error is the average of the sum of the squares of the distances of each data point from the true value, that is, the average of the sum of squared errors. The larger the mean square error of an image, the more severe the image distortion, and the smaller the mean square error, the closer the image is to the true value.

[0081] like Figure 2 As shown, it is determined whether the mean square error of the camera image is greater than a first variance threshold. If so, the rearview mirror is heated. After heating the rearview mirror, it is determined whether the mean of the camera image is less than a second variance threshold. If so, heating the rearview mirror is stopped. If so, heating the rearview mirror continues until the mean square error is less than the second mean square error threshold.

[0082] In some embodiments, the specific step of setting the first mean square error threshold includes: acquiring M first images, wherein the M first images are all acquired in rainy weather and in an environment with relatively high humidity, and M is greater than or equal to 1000. The first images can be acquired by directly taking photos or by capturing videos and extracting key frames from the videos. For example, when acquiring 1000 first images, the mean square error of each of the 1000 first images is calculated, and the mean square error of the R channel, G channel, and B channel of each image is weighted to obtain the mean square error of each first image; then, the average mean square error of the 1000 first images is calculated based on the mean square error of each first image, and the average mean square error of the 1000 first images is set as the first mean square error threshold. If the mean square error captured by the camera is greater than the set first mean square error threshold, it indicates that there is water or fog on the camera lens. In this case, the rearview mirror and the rearview mirror camera are heated to evaporate the water vapor, thereby achieving dehumidification and defogging of the rearview mirror and the rearview mirror camera.

[0083] In some embodiments, the specific step of setting the second mean square error threshold includes: acquiring N second images, wherein the N second images are all acquired in a rainless and dry environment, and N is greater than or equal to 1000. The second images can be acquired by directly taking photos or by capturing a video and extracting key frames from the video. For example, when acquiring 1000 second images, the mean square error of each of the 1000 second images is calculated, and the mean square error of the R channel, G channel, and B channel of each second image is calculated separately. After weighted calculation, the mean square error of each second image is obtained; then, the average mean square error of the 1000 second images is calculated based on the mean square error of each second image, and the average mean square error of the 1000 second images is set as the second mean square error threshold. After heating the rearview mirror lens, if the mean square error of the image is less than the set second mean square error threshold, it indicates that the water mist has been cleared and the image captured by the rearview mirror camera is sufficiently clear, and the rearview mirror heating is stopped.

[0084] The first mean square error threshold is greater than the second mean square error threshold.

[0085] As a preferred embodiment, a heating wire can be provided on the rearview mirror camera to heat the rearview mirror and the rearview mirror. When the mean square error of the image captured by the camera is greater than a first mean square error threshold, the controller can send a start heating signal, causing the heating wire to start heating, thereby evaporating the water mist on the rearview mirror and the rearview mirror camera. When the mean square error of the image captured by the camera is less than a second mean square error threshold, the controller can send a stop heating signal, causing the heating wire to stop heating.

[0086] An embodiment of the present application provides a method for removing water mist from a rearview mirror, by acquiring an image captured by a rearview mirror camera; processing the acquired image to obtain a mean square error of the corresponding image; and judging whether to heat the rearview mirror based on the obtained mean square error, so as to achieve heating of the rearview mirror when water mist exists on the rearview mirror, so as to evaporate the water mist on the rearview mirror and the rearview mirror camera, thereby ensuring that the rearview mirror camera can clearly capture the environment behind the vehicle, and the driver can clearly observe the clear environment behind the vehicle captured by the camera through the rearview mirror, thereby improving the safety of vehicle driving.

[0087] Please refer to Figure 3 , Figure 3 A schematic block diagram of a device for removing mist from a rearview mirror provided in an embodiment of the present application.

[0088] like Figure 3 As shown, the device includes: an image acquisition module, a mean square error calculation module, and a heating control module.

[0089] The image acquisition module is used to acquire images captured by the rearview mirror camera;

[0090] The mean square error calculation module is used to process the acquired image to obtain the mean square error of the corresponding image;

[0091] The heating control module is used to determine whether to heat the rearview mirror according to the obtained mean square error.

[0092] Wherein, the heating control module is further used for:

[0093] If the obtained mean square error is greater than a set first mean square error threshold, heating the rearview mirror;

[0094] If the obtained mean square error is less than a set second mean square error threshold, heating the rearview mirror is stopped;

[0095] The first mean square error threshold is greater than the second mean square error threshold.

[0096] Wherein, the device for removing water mist from the rearview mirror is also used for:

[0097] Acquire M first images, and determine the mean square error of each first image;

[0098] Calculating an average mean square error of the M first images according to the mean square error of each first image;

[0099] Setting the average mean square error of the M first images as the first mean square error threshold;

[0100] Wherein, the first image is acquired in a rainy and humid environment: or,

[0101] Acquire N second images, and determine the mean square error of each second image;

[0102] Calculating an average mean square error of N second images according to the mean square error of each second image;

[0103] Setting the average mean square error of N second images as the second mean square error threshold;

[0104] The second image is acquired in a rainless and dry environment.

[0105] Wherein, the heating control module is further used to heat the rearview mirror through a heating wire arranged in the rearview mirror camera.

[0106] The mean square error calculation module is also used for:

[0107] Calculate the mean square error of the R channel, G channel and B channel in the image respectively;

[0108] A weighted calculation is performed on the mean square errors of the R channel, the G channel, and the B channel to obtain the mean square error of the image.

[0109] Wherein, the device for removing water mist from the rearview mirror is also used for:

[0110] After acquiring the image captured by the rearview mirror camera, and before processing the acquired image to obtain the mean square error of the corresponding image, the image is pre-processed using a Laplace operator.

[0111] Among them, the image acquisition module is also used to:

[0112] The images captured by the rearview mirror camera are sequentially acquired at preset time intervals.

[0113] It should be noted that those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices and modules and units can refer to the corresponding processes in the aforementioned embodiments and will not be repeated here.

[0114] The apparatus provided in the above embodiment can be implemented in the form of a computer program. The computer program can be used in Figure 4 Runs on the computer equipment shown.

[0115] See also Figure 4 , Figure 4 This is a schematic block diagram of the structure of a computer device provided in an embodiment of the present application. The computer device can be a vehicle controller or an onboard computer.

[0116] like Figure 4 As shown, the computer device includes a processor, a memory, and a network interface connected via a system bus, wherein the memory may include a non-volatile storage medium and an internal memory.

[0117] The non-volatile storage medium can store an operating system and a computer program. The computer program includes program instructions, which, when executed, can cause the processor to execute any one of the methods for removing water mist from the rearview mirror.

[0118] The processor is used to provide computing and control capabilities and support the operation of the entire computer equipment.

[0119] The internal memory provides an environment for the operation of the computer program in the non-volatile storage medium. When the computer program is executed by the processor, the processor can execute any method for removing water mist from the rearview mirror.

[0120] The network interface is used for network communication, such as sending assigned tasks, etc. Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0121] It should be understood that the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc.

[0122] In one embodiment, the processor is configured to execute a computer program stored in the memory to implement the following steps:

[0123] Acquire the image captured by the rearview mirror camera;

[0124] Processing the acquired image to obtain the mean square error of the corresponding image;

[0125] Whether to heat the rearview mirror is determined based on the obtained mean square error.

[0126] In one embodiment, when the processor determines whether to heat the rearview mirror based on the obtained mean square error, it is used to implement:

[0127] If the obtained mean square error is greater than a set first mean square error threshold, heating the rearview mirror;

[0128] If the obtained mean square error is less than a set second mean square error threshold, heating the rearview mirror is stopped;

[0129] The first mean square error threshold is greater than the second mean square error threshold.

[0130] In one embodiment, the processor is configured to implement:

[0131] Acquire M first images, and determine the mean square error of each first image;

[0132] Calculating an average mean square error of the M first images according to the mean square error of each first image;

[0133] Setting the average mean square error of the M first images as the first mean square error threshold;

[0134] Wherein, the first image is acquired in a rainy and humid environment: or,

[0135] Acquire N second images, and determine the mean square error of each second image;

[0136] Calculating an average mean square error of N second images according to the mean square error of each second image;

[0137] Setting the average mean square error of N second images as the second mean square error threshold;

[0138] The second image is acquired in a rainless and dry environment.

[0139] In one embodiment, the processor is configured to heat the rearview mirror via a heating wire disposed in the rearview mirror camera.

[0140] In one embodiment, when the processor processes the acquired image to obtain the mean square error of the corresponding image, it is used to implement:

[0141] Calculate the mean square error of the R channel, G channel and B channel in the image respectively;

[0142] A weighted calculation is performed on the mean square errors of the R channel, the G channel, and the B channel to obtain the mean square error of the image.

[0143] In one embodiment, after acquiring the image captured by the rearview mirror camera, the processor is used to pre-process the image using a Laplace operator before processing the acquired image to obtain the mean square error of the corresponding image.

[0144] In one embodiment, when the processor acquires the image captured by the rearview mirror camera, it is configured to sequentially acquire the images captured by the rearview mirror camera at preset time intervals.

[0145] An embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored. The computer program includes program instructions. The method implemented when the program instructions are executed can refer to the various embodiments of the present application.

[0146] The computer-readable storage medium may be an internal storage unit of the computer device described in the aforementioned embodiment, such as a hard disk or memory of the computer device. The computer-readable storage medium may also be an external storage device of the computer device, such as a plug-in hard disk, a SmartMedia Card (SMC), a Secure Digital (SD) card, a flash memory card, etc., equipped on the computer device.

[0147] In the description of this application, it should be noted that the terms "upper" and "lower" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on this application. Unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or an indirect connection through an intermediate medium, or it can be internal communication between two elements. For those of ordinary skill in the art, the specific meanings of the above terms in this application can be understood according to the specific circumstances.

[0148] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or system comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or system. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or system comprising the element.

[0149] The serial numbers of the embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments. The above description is only a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in this application, and these modifications or replacements should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A method for removing water mist from a rearview mirror, characterized in that: The following steps are involved: Acquire the image captured by the rearview mirror camera; Processing the acquired image to obtain the mean square error of the corresponding image; Determine whether to heat the rearview mirror according to the obtained mean square error; The step of determining whether to heat the rearview mirror according to the obtained mean square error specifically includes the following steps: If the obtained mean square error is greater than a set first mean square error threshold, heating the rearview mirror; If the obtained mean square error is less than a set second mean square error threshold, heating the rearview mirror is stopped; Wherein, the first mean square error threshold is greater than the second mean square error threshold; The specific steps of setting the first mean square error threshold include: Acquire M first images, and determine the mean square error of each first image; Calculating an average mean square error of the M first images according to the mean square error of each first image; Setting the average mean square error of the M first images as the first mean square error threshold; Wherein, the first image is acquired in a rainy and humid environment: or, The specific steps of setting the second mean square error threshold include: Acquire N second images, and determine the mean square error of each second image; Calculating an average mean square error of N second images according to the mean square error of each second image; Setting the average mean square error of N second images as the second mean square error threshold; The second image is acquired in a rainless and dry environment.

2. The method for removing water mist from a rearview mirror according to claim 1, characterized in that: The rearview mirror is heated by a heating wire arranged in the rearview mirror camera.

3. The method for removing water mist from a rearview mirror according to claim 1, characterized in that: The processing of the acquired image to obtain the mean square error of the corresponding image specifically includes the following steps: Calculate the mean square error of the R channel, G channel and B channel in the image respectively; A weighted calculation is performed on the mean square errors of the R channel, the G channel, and the B channel to obtain the mean square error of the image.

4. The method for removing water mist from a rearview mirror according to claim 1, characterized in that: After acquiring the image captured by the rearview mirror camera and before processing the acquired image to obtain the mean square error of the corresponding image, the method further includes the following steps: The image is preprocessed using the Laplacian operator.

5. The method for removing water mist from a rearview mirror according to claim 1, characterized in that: The acquisition of the image captured by the rearview mirror camera specifically includes the following steps: The images captured by the rearview mirror camera are sequentially acquired at preset time intervals.

6. A device for removing water mist from a rearview mirror, characterized in that: include: An image acquisition module, which is used to acquire images captured by the rearview mirror camera; A mean square error calculation module is used to process the acquired image to obtain the mean square error of the corresponding image; a heating control module, which is used to determine whether to heat the rearview mirror according to the obtained mean square error; Wherein, the heating control module is further used for: If the obtained mean square error is greater than a set first mean square error threshold, heating the rearview mirror; If the obtained mean square error is less than a set second mean square error threshold, heating the rearview mirror is stopped; Wherein, the first mean square error threshold is greater than the second mean square error threshold; Wherein, the device for removing water mist from the rearview mirror is also used for: Acquire M first images, and determine the mean square error of each first image; Calculating an average mean square error of the M first images according to the mean square error of each first image; Setting the average mean square error of the M first images as the first mean square error threshold; Wherein, the first image is acquired in a rainy and humid environment: or, Acquire N second images, and determine the mean square error of each second image; Calculating an average mean square error of N second images according to the mean square error of each second image; Setting the average mean square error of N second images as the second mean square error threshold; The second image is acquired in a rainless and dry environment.

7. A computer device, characterized in that: The computer device includes a processor, a memory, and a computer program stored in the memory and executable by the processor, wherein when the computer program is executed by the processor, the steps of the method for removing water mist from a rearview mirror as described in any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, the steps of the method for removing water mist from a rearview mirror according to any one of claims 1 to 5 are implemented.

Images