Vehicle surrounding environment image processing device and method, and monitoring system

Abstract

The present invention provides a vehicle surrounding environment image processing device and method, and a monitoring system. The processing device is configured to: receive a vehicle surrounding environment image from a vehicle-mounted camera and a vehicle surrounding environment light intensity from a vehicle-mounted photosensitive sensor; and process the environment image in different regions based on the environment light intensity and a reference image selected from a stored reference image set, and output the processed environment image to a display device in the vehicle, wherein the reference image is selected from the reference image set based on the environment light intensity, the reference image includes multiple regions, and each region has a first brightness threshold and a second brightness threshold that is smaller than the first brightness threshold.

Description

Technical Field

[0001] The invention relates to a processing device and method for vehicle surrounding environment image processing, and also relates to a vehicle surrounding environment monitoring system. Background Art

[0002] As a vehicle accessory, the rearview mirror allows the driver to see the situation behind and to the side of the vehicle. However, the viewing angle that the rearview mirror can project is very limited, and whether the rearview mirror is located on the sides of the vehicle body or in the middle and upper part of the windshield, these locations are not convenient for the driver to take a quick glance.

[0003] In order to solve the above-mentioned problems of rearview mirrors, a solution of using a rearview camera on a vehicle has emerged in the prior art, that is, using a rearview camera to provide a rearview function, which can not only expand the driver's visual range, but also save the driver from raising his head or shaking his head left and right to observe the situation behind or to the side. However, using a rearview camera to capture the image of the vehicle's surrounding environment has obvious defects in the case of poor ambient light, because the environment image captured by the rearview camera in the case of poor ambient light will be very blurred, so that the driver cannot obtain accurate information about the situation to the side or rear, which may cause traffic accidents. Summary of the invention

[0004] In view of the above problems in the prior art, the present invention aims to provide a processing solution for processing a vehicle surrounding environment image and a vehicle surrounding environment monitoring system.

[0005] According to an embodiment of the first aspect of the present invention, a processing device for processing vehicle surrounding environment images is provided, which is configured to: receive vehicle surrounding environment images from a vehicle-mounted camera and vehicle surrounding environment light intensity from a vehicle-mounted photosensitive sensor; and process the environment image in regions based on the ambient light intensity and a reference image selected from a stored reference image set, and output the processed environment image to a display device in the vehicle, wherein the reference image is selected from a reference image set based on the ambient light intensity, the reference image includes multiple regions, and each region has a first brightness threshold and a second brightness threshold that is less than the first brightness threshold; divide the environment image into multiple regions that correspond one-to-one in position to the multiple regions of the reference image; when the brightness value of an area of ​​the environment image is greater than the first brightness threshold of the corresponding area of ​​the reference image, reduce the brightness value of the area of ​​the environment image; and when the brightness value of an area of ​​the environment image is less than the second brightness threshold of the corresponding area of ​​the reference image, increase the brightness value of the area of ​​the environment image.

[0006] According to a feasible embodiment, the processing device is configured to determine the first brightness threshold and the second brightness threshold in the following manner: calculate the brightness value of each area of ​​the reference image; multiply the brightness value of an area of ​​the reference image by a first coefficient to obtain a first brightness threshold of the area, and the first coefficient is greater than 1; and multiply the brightness of an area of ​​the reference image by a second coefficient to obtain a second brightness threshold of the area, and the second coefficient is less than 1.

[0007] According to a feasible implementation, the reference image set includes multiple reference images taken under different ambient light intensities; and the processing device is configured to select a reference image corresponding to the ambient light intensity closest to the ambient light intensity around the vehicle from the reference image set as the reference image of the ambient image.

[0008] According to a feasible implementation manner, the reference image set at least includes reference images taken in an environment with cloudy daytime and good lighting at night.

[0009] According to a possible implementation, when the vehicle has multiple onboard cameras, the reference image set includes multiple reference image sets for each onboard camera.

[0010] According to a possible implementation, the processing device is further configured to determine an area of ​​interest among the plurality of areas of the environment image, and to reduce a first brightness threshold for the area of ​​interest and to increase a second brightness threshold for the area of ​​interest.

[0011] According to one possible embodiment, the processing device is configured to determine the following areas as areas of interest: (1) areas among multiple areas of the environmental image whose brightness values ​​are higher than a first brightness threshold to a first predetermined degree; and (2) areas among multiple areas of the environmental image whose brightness values ​​are lower than a second brightness threshold to a second predetermined degree.

[0012] According to a feasible implementation, the processing device is configured to process the environmental image using an image processing model, taking the environmental image containing multiple regions as a model input, and outputting a region of interest among the multiple regions after processing by the image processing model.

[0013] According to a feasible implementation manner, the image processing model is a machine learning model.

[0014] According to a possible implementation, the processing device is configured to calculate the regional brightness value using the same calculation method for both a region of the reference image and a corresponding region of the environment image.

[0015] According to a feasible embodiment, the processing device is configured to calculate the brightness value of an area by at least one of the following: (1) calculating the average grayscale values ​​of all pixels in an area as the brightness value of the area; (2) calculating the percentage of the number of pixels in an area whose grayscale values ​​are higher than a first predetermined value and / or lower than a second predetermined value to the total number of pixels in the area, and determining the brightness value of the area based on the percentage.

[0016] According to an embodiment of the second aspect of the present invention, a vehicle surrounding environment monitoring system is provided, including a vehicle-mounted camera for capturing images of the vehicle's surrounding environment; a vehicle-mounted photosensor for sensing the light intensity of the vehicle's surrounding environment; a processing device as described above, which is communicatively connected to the vehicle-mounted camera and the photosensor, and is used to process the environmental image based on a reference image selected from a stored reference image set and the ambient light intensity, and output the processed environmental image; and a display device, which is communicatively connected to the processing device, and is used to display the processed environmental image in the vehicle.

[0017] According to an embodiment of the third aspect of the present invention, a method for processing a vehicle surrounding environment image is provided, optionally, the method is executed by the processing device as described above and / or the vehicle surrounding environment monitoring system as described above, the method comprising: receiving a vehicle surrounding environment image from a vehicle-mounted camera and a vehicle surrounding environment light intensity from a vehicle-mounted photosensor; and processing the environment image in a region-by-region manner based on the ambient light intensity and a reference image selected from a stored reference image set, and outputting the processed environment image to a display device in the vehicle, wherein the reference image is selected from a reference image set based on the ambient light intensity, the reference image comprises a plurality of regions, and each region has a first brightness threshold and a second brightness threshold less than the first brightness threshold; dividing the environment image into a plurality of regions corresponding one-to-one in position to the plurality of regions of the reference image; when the brightness value of a region of the environment image is greater than the first brightness threshold of the corresponding region of the reference image, reducing the brightness value of the region of the environment image; and when the brightness value of a region of the environment image is less than the second brightness threshold of the corresponding region of the reference image, increasing the brightness value of the region of the environment image.

[0018] It can be seen that according to an embodiment of the present invention, by processing the vehicle surrounding environment image in different regions, the problem of local overbrightness or local overdarkness of the image caused by excessively bright or dark ambient light is eliminated, thereby providing the driver with a clear vehicle surrounding environment image even when the ambient light around the vehicle is poor, which helps to improve driving safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 is a schematic block diagram of a vehicle surrounding environment monitoring system according to a possible embodiment of the present invention, which includes a processing device according to a possible embodiment of the present invention.

[0020] Figure 2 An exemplary process of image processing according to a possible embodiment of the present invention is schematically shown.

[0021] Figure 3 An exemplary process of determining the first brightness threshold and the second brightness threshold according to a feasible embodiment of the present invention is schematically shown.

[0022] Figure 4 is a flow chart of a method for vehicle surroundings image processing according to a possible implementation of the present invention. DETAILED DESCRIPTION

[0023] Hereinafter, some embodiments of the present invention are described with reference to the accompanying drawings.

[0024] Figure 1 The vehicle surrounding environment monitoring system 100 according to a feasible implementation mode of the present invention mainly comprises a vehicle-mounted camera 10, a photosensitive sensor 20, a processing device 30 and a display device 40. The components of the vehicle surrounding environment monitoring system 100 are introduced below.

[0025] The vehicle-mounted camera 10 is arranged at any suitable position on the vehicle, and is used to capture the environmental image around the vehicle (hereinafter referred to as the environmental image). The vehicle-mounted camera 10 is installed, for example, at the front of the vehicle, the side of the vehicle, or around the vehicle body. The vehicle-mounted camera 10 can be implemented as one or more of a front-view camera, a rear-view camera, and a surround-view camera. The vehicle-mounted camera 10 can be installed on the vehicle in the form of replacing the vehicle's rearview mirror, or it can be installed on a vehicle with a rearview mirror, that is, the vehicle-mounted camera 10 is set on the basis of retaining the rearview mirror. In one embodiment, the vehicle-mounted camera 10 is installed in the housing of the vehicle's rearview mirror, and is used to capture the environmental information behind and to the side of the vehicle. The vehicle-mounted camera 10 can be implemented as a plurality of vehicles, which are installed at different positions on the vehicle.

[0026] The photosensitive sensor 20 is installed on the vehicle and is used to sense the ambient light intensity around the vehicle (hereinafter referred to as ambient light intensity). The photosensitive sensor 20 can be set anywhere on the vehicle. In one embodiment, the photosensitive sensor 20 can be set relatively close to the vehicle-mounted camera 10, so that the ambient light intensity when the vehicle-mounted camera 10 captures the environmental image can be sensed more accurately. In the case where there are multiple vehicle-mounted cameras on the vehicle, a photosensitive sensor can be set near each vehicle-mounted camera to sense the ambient light intensity of the environment in which the vehicle-mounted camera captures the environmental image.

[0027] The processing device 30 is in communication with the vehicle camera 10 and the light sensor 20, and receives the environment image from the vehicle camera 10 and the environment light intensity from the light sensor 20. The processing device 30 processes the environment image by region based on the environment light intensity and the reference image, and outputs the processed environment image.

[0028] The processing device 30 may be arranged in an electronic control unit (ECU) of the vehicle. The processing device 30 may be implemented in hardware or software or in a combination of software and hardware.

[0029] For the hardware-implemented portion, it can be implemented in one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, electronic units designed to perform its functions, or a combination thereof.

[0030] For the parts implemented in software, they may be implemented with the aid of microcodes, program codes or code segments, and may also be stored in a machine-readable storage medium such as a storage component.

[0031] The display device 40 is in communication with the processing device 30 and is used to display the processed environment image. The display device 40 can be implemented as a variety of devices capable of displaying images in the vehicle, and the display device 40 receives the processed environment image from the processing device 30 and presents the image to the driver. The display device 40 can be implemented, for example, as a central control screen of the vehicle, or a head-up display (HUD), or a display screen of a driver's smart device (e.g., a tablet computer, a smart phone).

[0032] Below, refer to Figure 2 , describes an exemplary process 200 of image processing according to an embodiment of the present invention, which process 200 can be performed in the processing device 30.

[0033] The processing device 30 receives an environment image and an environment light intensity (block 210 ). For example, the processing device 30 receives an environment image from the vehicle-mounted camera 10 and receives an environment light intensity from the light-sensitive sensor 20 .

[0034] Next, the processing device 30 selects a reference image based on the ambient light intensity (block 220).

[0035] In one embodiment, a reference image set is pre-stored in a storage device (not shown) of the vehicle. The reference image set includes a plurality of reference images, which are taken under different ambient light intensities and are marked with the ambient light intensities at which they were taken. The shooting scenes of the reference images include, for example, scenes with reference significance such as cloudy days or well-lit nights. The processing device 30 compares the received ambient light intensity with the shooting ambient light intensity of each reference image, and determines the reference image corresponding to the shooting ambient light intensity that is closest to the received ambient light intensity (for example, the smallest difference between the two) as the reference image used for this processing, that is, the selected reference image.

[0036] In addition, when a vehicle is equipped with multiple onboard cameras, there may be multiple reference image sets for each onboard camera, and each time processing is performed, a reference image set corresponding to the onboard camera that captures the environment image is selected.

[0037] After selecting the reference image, the processing device 30 calculates first and second brightness thresholds for each region of the reference image (block 230 ).

[0038] The reference image has a plurality of regions, each region has a first brightness threshold and a second brightness threshold, and the second brightness threshold is greater than the third brightness threshold. Figure 3 An exemplary process for determining the first brightness threshold and the second brightness threshold is schematically illustrated.

[0039] See also Figure 3 , dividing the reference image into a plurality of regions (block 232). In one embodiment, the reference image may be equally divided into a plurality of regions (e.g., 4*4 regions). In another embodiment, the edge portion of the image may be divided into a plurality of regions with larger areas, and the middle portion of the image may be divided into a plurality of regions with smaller areas. The present invention does not limit the specific division method of the plurality of regions of the reference image.

[0040] Next, the processing device 30 calculates the brightness value of each region of the reference image (block 234). The processing device 30 may calculate the brightness value of each region in a variety of ways, and may calculate the regional brightness value in different ways for different regions of the same reference image. Two embodiments of calculating the regional brightness value are described below.

[0041] In one embodiment of calculating the regional brightness value, the average brightness value of the grayscale values ​​of all pixels in a region is calculated, and the average brightness value is used as the brightness value of the region.

[0042] In another embodiment of calculating the brightness value of a region, the percentage of the number of pixels in the region whose brightness values ​​are greater than a first predetermined value and / or less than a second predetermined value to the total number of pixels in the region is counted, and the brightness value of the region is determined based on the percentage, for example, by looking up the brightness value of a region with a certain percentage in a pre-set percentage-brightness value comparison table (for example, the comparison table contains the correspondence between percentage intervals and brightness values).

[0043] In this embodiment, the first predetermined value can be understood as a higher brightness value, that is, pixels with brightness values ​​greater than the predetermined value may be too bright. The second predetermined value can be understood as a lower brightness value, that is, pixels with brightness values ​​less than the predetermined value may be too dark.

[0044] It can be understood that, for the same area, all pixels in the area may be darker, all pixels in the area may be brighter, or some pixels may be darker and other pixels may be brighter.

[0045] Next, the calculated brightness value of a region of the reference image is multiplied by a first coefficient, which is greater than 1, to obtain a first brightness threshold of the region, that is, a threshold used to determine whether the corresponding region of the environment image is too bright. The calculated brightness value of a region of the reference image is multiplied by a second coefficient, which is less than 1, to obtain a second brightness threshold of the region, that is, a threshold used to determine whether the corresponding region of the environment image is too dark.

[0046] After determining a plurality of regions of the reference image and a first brightness threshold and a second brightness threshold of each region, the processing device 30 processes the environment image region by region.

[0047] The processing device 30 divides the environment image into a plurality of regions and calculates a brightness value of each region (block 240 ).

[0048] In one embodiment, the environment image is divided into a plurality of regions corresponding one-to-one to the plurality of regions of the selected reference image in terms of image position, that is, the number of regions of the environment image is equal to the number of regions of the selected reference image, and the regions of the two regions correspond one-to-one in terms of position. The brightness value of each region of the environment image is calculated in the same manner as the brightness value of the corresponding region of the selected reference image. For example, if the brightness value of a region of the environment image is calculated by the grayscale mean, the brightness value of the corresponding region of the environment image should also be calculated by the grayscale mean.

[0049] After obtaining a plurality of regions of the environment image and the brightness values ​​of the respective regions, the processing device 30 identifies a region of interest in the environment image (block 250 ).

[0050] The region of interest may include a region where the regional brightness value is higher than a first brightness threshold for the region by a first predetermined degree (e.g., 30%), or is lower than a second brightness threshold for the region by a second predetermined degree (e.g., 35%). The first predetermined degree and the second predetermined degree may be equal or unequal.

[0051] The region of interest may also include a region of a predetermined object, for example, a strong light source region such as a vehicle headlight, which often appears locally too bright.

[0052] In one embodiment, an image processing model is used to process an environmental image. In this embodiment, an environmental image containing multiple regions is used as a model input, and after being processed by the image processing model, an area of ​​interest in the multiple regions is output. The image processing model can be implemented as a machine learning model. The machine learning model is, for example, a trained machine learning model. During the training process, a large number of environmental images taken by different vehicle-mounted cameras under various lighting environments are used as samples to train the machine learning model.

[0053] After the region of interest in the environment image is identified, the non-region of interest and the region of interest are processed separately.

[0054] For the non-interested region in the environment image, processing is performed based on the calculated first brightness threshold and second brightness threshold (block 260). For the non-interested region in the environment image, if the brightness value of a region is greater than the first brightness threshold of the corresponding region of the reference image (i.e., the region corresponding to the selected reference image at the position), the region is considered to be too bright, and the brightness value of the region is reduced, for example, to the first brightness threshold. If the brightness value of a region is less than the second brightness threshold, the region is considered to be too dark, and the brightness value of the region is increased, for example, to the second brightness threshold.

[0055] For the processing of the regions of interest in the environment image, first adjust the first brightness threshold and the second brightness threshold for these regions (box 270) to make the brightness adjustment for these regions more sensitive and moderate. For example, lower the first brightness threshold for the region of interest, and increase the second brightness threshold for the region of interest. In a specific implementation, the first brightness threshold can be adjusted in this way, that is, when the brightness value of a region of the reference image is multiplied by the first coefficient to obtain the first brightness value, the first coefficient is reduced (for example, the first coefficient is reduced from the original 1.3 to 1.1). Similarly, the second brightness threshold can be adjusted by increasing the second coefficient (for example, the second coefficient is increased from the original 0.7 to 0.8).

[0056] Next, the region of interest in the environment image is processed based on the adjusted first brightness threshold and second brightness threshold (block 280). For the region of interest in the environment image, if the brightness value of a region is greater than the adjusted first brightness threshold, the brightness value of the region is reduced, for example, reduced to the adjusted first brightness threshold. If the brightness value of a region is less than the adjusted second brightness threshold, the brightness value of the region is increased, for example, raised to the adjusted second brightness threshold.

[0057] After completing the region-by-region processing of the environment image, the processing device 30 outputs the processed environment image to the display device 40 for presentation to the driver in the vehicle (block 390 ).

[0058] Figure 4 A method 300 for vehicle surrounding environment image processing according to a feasible embodiment of the present invention is shown. The method 300 can be executed by the processing device 30 and / or the system 100 as described above, so the above description of the processing device 30 and the system 100 is also applicable here.

[0059] In step 310 , an image of the vehicle's surroundings from a vehicle-mounted camera and an intensity of the vehicle's surrounding light from a vehicle-mounted photosensitive sensor are received.

[0060] In step 320 , the environment image is processed region by region based on the environment light intensity and a reference image selected from a stored reference image set, and the processed environment image is output to a display device in the vehicle.

[0061] The reference image is selected from a reference image set based on ambient light intensity. The reference image includes multiple regions, and each region has a first brightness threshold and a second brightness threshold that is smaller than the first brightness threshold.

[0062] In step 320, the following steps may be performed: dividing the environmental image into a plurality of regions that correspond one-to-one in position to the plurality of regions of the reference image; when the brightness value of a region of the environmental image is greater than a first brightness threshold of the corresponding region of the reference image, lowering the brightness value of the region of the environmental image; and when the brightness value of a region of the environmental image is less than a second brightness threshold of the corresponding region of the reference image, increasing the brightness value of the region of the environmental image.

[0063] It is to be understood that all operations in the method described above are merely exemplary, and the present invention is not limited to any operation in the method or the order of these operations, but should cover all other equivalent transformations under the same or similar concept.

[0064] The present invention also provides a machine-readable storage medium storing executable instructions, which, when executed, enables the machine to execute the method 300 described above.

[0065] The present invention also provides a camera for a vehicle, the camera comprising a microprocessor having the processing function of the processing device 30 as described above, so that the camera can process the captured environmental image in the above-mentioned area and output the processed environmental image. In one embodiment, the camera for a vehicle is realized by integrating the above-mentioned vehicle-mounted camera 10 and the above-mentioned processing device 30.

[0066] The above description is provided to enable any person skilled in the art to implement the various aspects described herein. Various modifications to these aspects are apparent to those skilled in the art, and the general principles defined herein may be applied to other aspects. Therefore, the claims are not intended to be limited to the aspects shown herein. All structural and functional equivalents of elements of the various aspects described herein that are known or to be known to those skilled in the art will be expressly included herein by reference and are intended to be covered by the claims.

Claims

1. A processing device for vehicle surrounding environment image processing, which is configured to: Receiving an image of the vehicle's surroundings from an on-board camera and an intensity of the vehicle's surrounding light from an on-board photosensitive sensor; and Processing the environment image region by region based on the environment light intensity and a reference image selected from a stored reference image set, and outputting the processed environment image to a display device in the vehicle, in, The reference image set includes a plurality of reference images captured under different ambient light intensities, and the reference image is a reference image selected by the processing device from the reference image set and corresponding to the ambient light intensity closest to the ambient light intensity around the vehicle; The reference image includes a plurality of regions, and each region has a first brightness threshold and a second brightness threshold that is smaller than the first brightness threshold; Dividing the environment image into a plurality of regions corresponding one-to-one in position to the plurality of regions of the reference image; When the brightness value of a region of the environment image is greater than a first brightness threshold of a corresponding region of the reference image, reducing the brightness value of the region of the environment image; and When the brightness value of a region of the environment image is less than a second brightness threshold of a corresponding region of the reference image, the brightness value of the region of the environment image is increased.

2. The processing device according to claim 1, wherein: The processing device is configured to determine the first brightness threshold and the second brightness threshold by: Calculate the brightness value of each area of ​​the reference image; Multiplying a brightness value of a region of the reference image by a first coefficient to obtain a first brightness threshold of the region, wherein the first coefficient is greater than 1; as well as The brightness of a region of the reference image is multiplied by a second coefficient to obtain a second brightness threshold of the region, where the second coefficient is less than 1.

3. The processing device according to claim 1 or 2, wherein the reference image set at least comprises reference images taken in an environment with good lighting during the day and at night; and In the case that the vehicle has multiple onboard cameras, the reference image set includes multiple reference image sets for each onboard camera.

4. The processing device according to claim 1, wherein: The processing device is further configured to determine a region of interest among the plurality of regions of the environment image, and to reduce a first brightness threshold for the region of interest and to increase a second brightness threshold for the region of interest.

5. The processing device according to claim 4, wherein: The processing device is configured to determine the following areas as areas of interest: (1) an area in a plurality of areas of an environmental image, the brightness of which is higher than a first brightness threshold by a first predetermined degree; and (2) A region among a plurality of regions of the environment image whose brightness value is lower than a second brightness threshold value by a second predetermined degree.

6. A processing device as claimed in claim 4 or 5, wherein: The processing device is configured to process the environmental image using an image processing model, taking the environmental image containing multiple areas as a model input, and outputting an area of ​​interest among the multiple areas after processing by the image processing model, wherein the image processing model is a machine learning model.

7. The processing device according to claim 1, wherein: The processing device is configured to calculate the regional brightness value using the same calculation method for both a region of the reference image and a corresponding region of the environment image.

8. The processing device according to claim 1, wherein: The processing device is configured to calculate a brightness value of a region by at least one of the following: (1) Calculate the average grayscale value of all pixels in a region as the brightness value of the region; and (2) Calculating the percentage of the number of pixels in a region whose grayscale values ​​are higher than a first predetermined value and / or lower than a second predetermined value to the total number of pixels in the region, and determining the brightness value of the region based on the percentage.

9. A vehicle surrounding environment monitoring system, comprising: An on-board camera, used to capture images of the vehicle's surroundings; On-vehicle photosensor, used to sense the light intensity around the vehicle; The processing device according to any one of claims 1 to 8, being communicatively connected to the vehicle-mounted camera and the light-sensitive sensor, for processing an environmental image based on a reference image selected from a stored reference image set and the ambient light intensity, and outputting the processed environmental image; as well as The display device is communicatively connected to the processing device and is used for displaying the processed environment image in the vehicle.

10. A method for processing a vehicle surrounding environment image, optionally, the method is performed by the processing device according to any one of claims 1 to 8 and / or the vehicle surrounding environment monitoring system according to claim 9, the method comprising: Receiving the vehicle surrounding environment image from the vehicle-mounted camera and the vehicle surrounding environment light intensity from the vehicle-mounted photosensitive sensor; as well as Processing the environment image region by region based on the environment light intensity and a reference image selected from a stored reference image set, and outputting the processed environment image to a display device in the vehicle, The reference image set includes a plurality of reference images captured under different ambient light intensities, and the reference image is a reference image selected from the reference image set and corresponding to an ambient light intensity closest to an ambient light intensity around the vehicle, and the reference image includes a plurality of regions, and each region has a first brightness threshold and a second brightness threshold that is smaller than the first brightness threshold; Dividing the environment image into a plurality of regions corresponding one-to-one in position to the plurality of regions of the reference image; When the brightness value of a region of the environment image is greater than a first brightness threshold of a corresponding region of the reference image, reducing the brightness value of the region of the environment image; and When the brightness value of a region of the environment image is less than a second brightness threshold of a corresponding region of the reference image, the brightness value of the region of the environment image is increased.

Images