A surveying and mapping image enhancement method based on unmanned aerial vehicle remote sensing technology

Abstract

A survey image enhancement method based on unmanned aerial vehicle remote sensing technology, comprising: obtaining an original survey image based on an RGB image sensor; dividing the original survey image into at least a first image and a second image, the first image and the second image being frame-synchronized; outputting a regular image directly or after processing the first image; performing color enhancement or color weakening on at least one channel of the RGB three channels in the second image to obtain an enhanced image; and displaying the regular image and the enhanced image separately or together. The method solves the problem of low differentiation of different geographical regions in survey images, can better distinguish different geographical regions, and enhances the boundary information of different geographical regions.

Description

Technical Field

[0001] This application relates to the field of UAV remote sensing mapping, specifically to a mapping image enhancement method based on UAV remote sensing technology. Background Technology

[0002] Unmanned aerial vehicle (UAV) remote sensing technology has been widely used in geographic surveying and mapping. With the development of video technology, the mapping images acquired through UAV remote sensing technology can well meet the needs of surveyors. However, currently, in geographic surveying and mapping work, mapping images acquired based on UAV remote sensing technology may have the following shortcomings:

[0003] In urban surveying, due to the obstruction of tall buildings, the surveyed images may often lack images of certain areas, or images of certain areas may lack necessary information.

[0004] When using drones for mapping, due to varying distances from the ground or changes in altitude during movement, some details of geographical information and features may still be missing from the mapped images, resulting in low differentiation between different geographical regions. For example, changes in altitude during movement can lead to errors in the size proportions of certain areas; or, in wetland environments, it may be difficult to determine the specific outlines between water areas and grasslands.

[0005] Chinese patent application No. 202211074671.3 discloses a UAV mapping data processing system and method for modeling. It utilizes oblique photogrammetry technology in the image acquisition module to add a method of simultaneous exposure of four oblique perspective lenses, simultaneously acquiring images from both downward and oblique perspectives, and can access more surface information. During the oblique photogrammetry measurement process, relative and absolute positioning are required to directly measure the height of ground features such as buildings, resulting in images containing richer real-world environmental information.

[0006] Chinese patent application number 202110099444.5 discloses a method for enhancing remote sensing mapping images from unmanned aerial vehicles (UAVs). This method performs pixel-level enhancement processing on grayscale images to reduce image noise and obtain better mapping images.

[0007] Chinese patent application number 202210339484.7 discloses a method for enhancing remote sensing mapping images from unmanned aerial vehicles (UAVs), which uses a specific image optimization algorithm to increase the details of the mapping images. Summary of the Invention

[0008] This application provides a mapping image enhancement method based on UAV remote sensing technology, which solves the problem of low differentiation between different geographical regions in mapping images.

[0009] On the one hand, embodiments of this application provide a mapping image enhancement method based on UAV remote sensing technology, including:

[0010] Original mapping images are acquired using an RGB image sensor;

[0011] The original survey image is divided into at least a first image and a second image, and the first image and the second image are synchronized.

[0012] The first image is either directly output or processed and then output as a regular image.

[0013] At least one of the RGB three channels in the second image is enhanced or weakened to obtain an enhanced image;

[0014] The regular image and the enhanced image can be displayed separately or together.

[0015] In one embodiment, displaying the regular image and the enhanced image together includes: displaying the regular image and the enhanced image on two separate displays, or displaying them in a split-screen manner on the same display.

[0016] In one embodiment, the original mapping image is defined as comprising (1, 2, 3, ..., n-1, n, ...) frames (n is an even number);

[0017] The original survey image is divided into at least a first path image and a second path image, and the first path image and the second path image are synchronized, including: taking the (1, 2, 3, ..., n-1, n, ...)th frame of the original survey image as the first path image, and taking the (1, 2, 3, ..., n-1, n, ...)th frame of the original survey image as the second path image;

[0018] After performing color enhancement or color reduction on at least one of the RGB three channels of the nth frame of the second image to obtain the enhanced nth frame image, the method further includes: obtaining the nth frame image of the first image, and using the nth frame image of the first image as a reference frame, performing texture enhancement on the enhanced nth frame image.

[0019] In one embodiment, at least one of the RGB channels in the second image is enhanced or weakened to obtain an enhanced image. The principle formula is as follows:

[0020]

[0021]

[0022]

[0023] R, G, and B are the brightness values ​​of the R, G, and B pixels in the image sensor, respectively; a and b are the spectral ranges of the image light picked up by the image sensor; fa(λ) is the spectral curve of the image light reaching the image sensor; R(λ), G(λ), and B(λ) are the spectral response curves of the image sensor, respectively; and e1, e2, and e3 are the coefficients for color enhancement or color reduction of the R, G, and B channels, respectively, with values ​​ranging from [0 to 200%].

[0024] In one embodiment, the enhanced image includes one or more of the following values: (e1=200%, e2=0, e3=0), (e1=0, e2=200%, e3=0), (e1=0, e2=0, e3=10%).

[0025] On the other hand, embodiments of this application provide another mapping image enhancement method based on UAV remote sensing technology, including:

[0026] Original mapping images are acquired using an RGB image sensor;

[0027] The original survey image is divided into at least a first image and a second image, wherein the first image and the second image are obtained by interleaving frames based on the original survey image;

[0028] The first image is either directly output or processed and then output as a regular image.

[0029] At least one of the RGB three channels in the second image is enhanced or weakened to obtain an enhanced image;

[0030] The regular image and the enhanced image can be displayed separately or together.

[0031] In one embodiment, displaying the regular image and the enhanced image together includes: displaying the regular image and the enhanced image on two separate displays, or displaying them in a split-screen manner on the same display.

[0032] In one embodiment, displaying the regular image and the enhanced image on two independent displays includes: the two independent displays alternately updating the regular image and the enhanced image, such that the update frame rate of the displayed image is half of the frame rate of the original survey image;

[0033] Alternatively, split-screen display on the same display includes: when the same display displays the regular image and the enhanced image in split-screen mode, the regular image and the enhanced image are updated alternately to make the update frame rate of the displayed image half of the frame rate of the original survey image.

[0034] In one embodiment, the original mapping image is defined as comprising (1, 2, 3, ..., n-1, n, ...) frames (n is an even number);

[0035] The original survey image is divided into at least a first image and a second image, wherein the first image and the second image are obtained by interleaving the original survey image, including: taking the (1, 3, 5, ..., n-1, ...)th frame of the original survey image as the first image, and taking the (2, 4, 6, ..., n, ...)th frame of the original survey image as the second image;

[0036] After performing color enhancement or color reduction on at least one of the RGB three channels of the nth frame of the second image to obtain the enhanced nth frame image, the method further includes: obtaining the (n-1)th frame image of the first image, and using the (n-1)th frame image of the first image as a reference frame, performing texture enhancement on the enhanced nth frame image.

[0037] In one embodiment, at least one of the RGB channels in the second image is enhanced or weakened to obtain an enhanced image. The principle formula is as follows:

[0038]

[0039]

[0040]

[0041] R, G, and B are the brightness values ​​of the R, G, and B pixels in the image sensor, respectively; a and b are the spectral ranges of the image light picked up by the image sensor; fa(λ) is the spectral curve of the image light reaching the image sensor; R(λ), G(λ), and B(λ) are the spectral response curves of the image sensor, respectively; and e1, e2, and e3 are the coefficients for color enhancement or color reduction of the R, G, and B channels, respectively, with values ​​ranging from [0 to 200%]. Attached Figure Description

[0042] Figure 1 The original survey image was obtained using unmanned remote sensing technology;

[0043] Figure 2The image obtained after performing a first-level enhancement on the R channel of the original survey image;

[0044] Figure 3 The image obtained after performing a second-level enhancement on the R channel of the original survey image;

[0045] Figure 4 The image obtained after applying the first level of attenuation to the R channel of the original survey image;

[0046] Figure 5 The image obtained after applying a second-order attenuation to the R channel of the original survey image;

[0047] Figure 6 The image obtained after performing a first-level enhancement on the G channel of the original survey image;

[0048] Figure 7 The image obtained after performing a second-level enhancement on the G channel of the original survey image;

[0049] Figure 8 The image obtained after applying first-order attenuation to the G channel of the original survey image;

[0050] Figure 9 The image obtained after applying a second-order attenuation to the G channel of the original survey image;

[0051] Figure 10 This is the image obtained after performing a first-level enhancement on the B channel of the original survey image;

[0052] Figure 11 The image obtained after performing a second-level enhancement on the B channel of the original survey image.

[0053] Figure 12 The image obtained after applying first-level attenuation to the B channel of the original survey image;

[0054] Figure 13 The image obtained after applying a second-order attenuation to the B channel of the original survey image;

[0055] Figure 14 This is a flowchart illustrating a mapping image enhancement method based on UAV remote sensing technology in one embodiment.

[0056] Figure 15 This is a diagram of an image processing framework for image enhancement in one embodiment;

[0057] Figure 16 This is a flowchart illustrating a mapping image enhancement method based on UAV remote sensing technology in another embodiment.

[0058] Figure 17This is a diagram of the image processing framework for image enhancement in another embodiment;

[0059] Figure 18 This is a schematic diagram showing the alternating updating and display of a regular image and two enhanced images.

[0060] Figure 19 This is a diagram of an image processing framework for image enhancement in another embodiment. Detailed Implementation

[0061] To make the technical problems, solutions, and beneficial effects of this invention clearer and more understandable, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0062] First, the two Chinese patent applications (CN202110099444.5 and CN202210339484.7) mentioned in the background section of this application are both based on obtaining the original survey image and performing image processing to achieve image enhancement. However, the inventors of this application have noted that image sensors all have at least three color channels: RGB.

[0063] Based on mapping images (e.g.) Figure 1 Using the original measured image, we conducted the following sets of experiments, enhancing and weakening the three RGB color channels at two levels, with the amplitude of the first level being smaller than that of the second level.

[0064] The first level of color enhancement in the R channel, such as... Figure 2 As shown.

[0065] The second level of color enhancement in the R channel, such as... Figure 3 As shown.

[0066] The R channel color is reduced at the first level, such as... Figure 4 As shown.

[0067] The second level of color reduction in the R channel, such as... Figure 5 As shown.

[0068] The first level of G channel color enhancement, such as... Figure 6 As shown.

[0069] G channel color enhancement level 2, such as Figure 7 As shown.

[0070] The first level of color reduction in the G channel, such as... Figure 8 As shown.

[0071] The second level of color reduction in the G channel, such as... Figure 9 As shown.

[0072] The B channel color enhancement level is the first level, such as... Figure 10 As shown.

[0073] The B channel color is enhanced at the second level, such as... Figure 11 As shown.

[0074] The color of the B channel is reduced at the first level, such as... Figure 12 As shown.

[0075] The color of the B channel is reduced at the second level, such as... Figure 13 As shown.

[0076] The above 12 sets of experiments show that:

[0077] 1.1 Comparison Figure 1 and Figure 2-3 As can be seen, enhancing the red channel (R channel) can improve the display of water areas and enhance the boundary information between water areas and other geographic features. For example... Figure 2-3 As indicated by the label "A".

[0078] 1.2 Comparison Figure 1 and Figure 4-5 As can be seen, reducing the red color did not significantly enhance the geographical feature information.

[0079] 2.1 Comparison Figure 1 and Figure 6-7 As can be seen, enhancing the green channel (G channel) can improve the display of vegetated or urban areas and enhance the boundary information between vegetated or urban areas and other geographic features. For example... Figure 6-7 As indicated by the label "B".

[0080] 2.2 Comparison Figure 1 and Figure 8-9 As can be seen, reducing the green color did not significantly enhance the geographical feature information.

[0081] 3.1 Comparison Figure 1 and Figure 10-11 As can be seen, enhancing the blue channel, i.e., channel B, did not significantly enhance the geographic feature information.

[0082] 3.2 Comparison Figure 1 and Figure 12-13 As can be seen, reducing the blue color can enhance the display of vegetation areas and improve the boundary information between vegetation areas and other geographical features. For example... Figure 2-13 As indicated by the label "C".

[0083] The reason for the above results is that different geographical features on the earth's surface absorb and reflect RGB differently. Therefore, when acquiring survey images, enhancing or weakening the RGB channels can also enhance the display of corresponding geographical features and better distinguish geographical boundaries.

[0084] Based on this, this application provides a mapping image enhancement method based on UAV remote sensing technology. Instead of processing the entire frame of the mapping image, it processes a single RGB channel within the image to enhance the geographic features of the mapping image and better distinguish geographic boundaries. This processing method differs from existing image processing approaches, focusing on processing a single color channel within the RGB image sensor.

[0085] like Figure 14 As shown, in one embodiment, the mapping image enhancement method based on UAV remote sensing technology includes:

[0086] S1.1: Acquire the original survey image based on the RGB image sensor.

[0087] S1.2: Divide the original survey image into at least a first image and a second image, and synchronize the frames of the first image and the second image.

[0088] S1.3: Output the first image directly or process it to output a regular image. A regular image refers to the observation image that the camera normally acquires and outputs.

[0089] S1.4: Enhance or degrade the color of at least one of the RGB channels in the second image to obtain an enhanced image.

[0090] S1.5: Display regular images and enhanced images separately or together.

[0091] In one embodiment, displaying a regular image and an enhanced image together includes: displaying the regular image and the enhanced image on two separate displays, or displaying them in a split-screen manner on the same display.

[0092] In one embodiment, the original mapping image is defined as comprising (1, 2, 3, ..., n-1, n, ...) frames (n being an even number).

[0093] The original survey image is divided into at least a first image and a second image, and the first image and the second image are synchronized, including: taking the (1, 2, 3, ..., n-1, n, ...)th frame of the original survey image as the first image, and taking the (1, 2, 3, ..., n-1, n, ...)th frame of the original survey image as the second image.

[0094] After performing color enhancement or color reduction on at least one of the RGB three channels of the nth frame of the second image to obtain the enhanced nth frame image, the method further includes: obtaining the nth frame image of the first image, and using the nth frame image of the first image as a reference frame to perform texture enhancement on the enhanced nth frame image. Figure 15 The image processing flowchart of this embodiment is shown. Using the first image as a reference frame for texture enhancement of the enhanced second image can further improve the texture information of the enhanced image and better distinguish the boundaries of different geographical regions.

[0095] In one embodiment, at least one of the RGB channels in the second image is enhanced or weakened to obtain an enhanced image. The principle formula is as follows:

[0096]

[0097]

[0098]

[0099] R, G, and B are the brightness values ​​of the R, G, and B pixels in the image sensor, respectively. a and b are the spectral ranges of the image light picked up by the image sensor. fa(λ) is the spectral curve of the image light reaching the image sensor. R(λ), G(λ), and B(λ) are the spectral response curves of the image sensor, respectively. e1, e2, and e3 are the coefficients for color enhancement or color reduction of the R, G, and B channels, respectively. The values ​​of e1, e2, and e3 range from [0, 200%].

[0100] In one embodiment, the enhanced image includes one or more values ​​from the following: (e1=200%, e2=0, e3=0), (e1=0, e2=200%, e3=0), (e1=0, e2=0, e3=10%). Through Figure 2-13 Experiments show that these three sets of values ​​are preferred. It should be noted that in some embodiments, only one set of values ​​is selected for image enhancement, and one enhanced image is output. In other embodiments, multiple sets of values ​​can be selected for image enhancement, and multiple enhanced images are output, each corresponding to a different set of values. Of course, multiple enhanced images can be selectively output and displayed according to user settings, or all can be output and displayed in a split-screen format along with the regular image.

[0101] In the mapping image enhancement method based on UAV remote sensing technology provided in the above embodiments, the first and second images are frame-synchronized with the original mapping images. This means that each update of a regular image and an enhanced image requires processing one frame, which consumes significant hardware resources, especially when image enhancement is deployed on a UAV, placing high demands on the UAV's hardware, power supply, transmission, and storage. Therefore, minimizing these resource requirements during image enhancement is a crucial consideration.

[0102] like Figure 16 As shown, in one embodiment, the mapping image enhancement method based on UAV remote sensing technology includes:

[0103] S2.1: Acquire the original survey image based on the RGB image sensor.

[0104] S2.2: Divide the original survey image into at least a first image and a second image, wherein the first image and the second image are obtained by interleaving the original survey image.

[0105] S2.3: Output the first image directly or process it to output a regular image. A regular image refers to the observation image that the camera normally acquires and outputs.

[0106] S2.4: Enhance or degrade the color of at least one of the RGB channels in the second image to obtain an enhanced image.

[0107] S2.5: Display regular images and enhanced images separately or together.

[0108] In this embodiment, since the first and second images are no longer frame-synchronized with the original survey image, but are obtained by interleaving the original survey image, the processing of half frames of the first and second images can be eliminated, greatly reducing resource requirements.

[0109] In one embodiment, displaying a regular image and an enhanced image together includes: displaying the regular image and the enhanced image on two separate displays, or displaying them in a split-screen manner on the same display.

[0110] In one embodiment, displaying a regular image and an enhanced image on two separate displays includes: the two separate displays alternately updating the regular image and the enhanced image, such that the update frame rate of the displayed image is half the frame rate of the original survey image.

[0111] Alternatively, split-screen display on the same monitor may include: when displaying a regular image and an enhanced image on the same monitor, the regular image and the enhanced image are updated alternately so that the update frame rate of the displayed image is half of the frame rate of the original survey image.

[0112] It should be noted that the displayed image update frame rate is half the frame rate of the original survey image, which is only achievable in this embodiment because only one second image has been separated from the original survey image. In other embodiments, the original survey image can be interleaved to output multiple second images. For example, two second images can be separated to obtain two enhanced images. These two enhanced images can choose different values ​​(e1, e2, e3). In this case, the image update frame rate will be 1 / 3 of the frame rate of the original survey image.

[0113] Figure 17 The diagram shows the image processing workflow framework for the two second-channel images. Figure 18 This shows an alternating update display of the regular image and the enhanced image.

[0114] It should be noted that a display may have a fixed refresh rate. The alternating display of regular and enhanced images referred to in this embodiment refers to image updates, which may not have a one-to-one correspondence with the display's refresh rate. For example, the image may only be updated once every two refreshes of the display.

[0115] In one embodiment, the original mapping image is defined as comprising (1, 2, 3, ..., n-1, n, ...) frames (n is an even number);

[0116] The original survey image is divided into at least a first image and a second image. The first image and the second image are obtained based on the interleaved frame output of the original survey image, including: taking the (1, 3, 5, ..., n-1, ...)th frame of the original survey image as the first image, and taking the (2, 4, 6, ..., n, ...)th frame of the original survey image as the second image;

[0117] After performing color enhancement or color reduction on at least one of the RGB three channels of the nth frame of the second image to obtain the enhanced nth frame image, the method further includes: obtaining the (n-1)th frame image of the first image, and using the (n-1)th frame image of the first image as a reference frame to perform texture enhancement on the enhanced nth frame image. Figure 19 The image processing flowchart of this embodiment is shown. Using the first image as a reference frame for texture enhancement of the enhanced second image can further improve the texture information of the enhanced image and better distinguish the boundaries of different geographical regions.

[0118] In one embodiment, at least one of the RGB channels in the second image is enhanced or weakened to obtain an enhanced image. The principle formula is as follows:

[0119]

[0120]

[0121]

[0122] R, G, and B are the brightness values ​​of the R, G, and B pixels in the image sensor, respectively. a and b are the spectral ranges of the image light picked up by the image sensor. fa(λ) is the spectral curve of the image light reaching the image sensor. R(λ), G(λ), and B(λ) are the spectral response curves of the image sensor, respectively. e1, e2, and e3 are the coefficients for color enhancement or color reduction of the R, G, and B channels, respectively. The values ​​of e1, e2, and e3 range from [0, 200%].

[0123] In one embodiment, the enhanced image includes one or more values ​​from the following: (e1=200%, e2=0, e3=0), (e1=0, e2=200%, e3=0), (e1=0, e2=0, e3=10%). Through Figure 2-13 Experiments show that these three sets of values ​​are more preferred. It should be noted that in some embodiments, only one set of values ​​is selected for image enhancement, and one enhanced image is output. In other embodiments, multiple sets of values ​​can be selected for image enhancement, and multiple enhanced images are output, each corresponding to a different set of values, for example... Figure 17 Enhanced Image 1 and Enhanced Image 2 in the image are obtained from two different sets of values. Of course, multiple enhanced images can be selectively output and displayed according to user settings, or all of them can be output and displayed in a split-screen format along with regular images. Correspondingly, if multiple enhanced images are displayed in a split-screen format with regular images, these images will be updated and displayed alternately.

[0124] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A mapping image enhancement method based on UAV remote sensing technology, characterized in that, include: Original mapping images are acquired using an RGB image sensor; The original survey image is divided into at least a first image and a second image, and the first image and the second image are synchronized. The first image is either directly output or processed and then output as a regular image. At least one of the RGB three channels in the second image is color-enhanced or color-reduced to obtain an enhanced image; the enhanced image enhances the boundary information between the water area, the urban area, and the vegetation area; The regular image and the enhanced image can be displayed separately or together; The R channel of the RGB three channels in the second image is enhanced to obtain an enhanced image, thereby enhancing the boundary information between the water area and other geographical feature areas; Alternatively, the G channel can be enhanced to obtain an enhanced image, thereby enhancing the boundary information between urban areas and other geographic feature areas; or the B channel can be weakened to obtain an enhanced image, thereby enhancing the boundary information between vegetated areas and other geographic feature areas. The principle formula is as follows: ； R, G, and B are the brightness values ​​of the R, G, and B pixels in the image sensor, respectively; a and b are the spectral ranges of the image light picked up by the image sensor; fa(λ) is the spectral curve of the image light reaching the image sensor; R(λ), G(λ), and B(λ) are the spectral response curves of the image sensor, respectively; and e1, e2, and e3 are the coefficients for color enhancement or color reduction of the R, G, and B channels, respectively, with values ​​ranging from [0, 200%].

2. The method as described in claim 1, characterized in that, Displaying the regular image and the enhanced image together includes: displaying the regular image and the enhanced image on two separate displays, or displaying them in a split-screen manner on the same display.

3. The method as described in claim 1 or 2, characterized in that, The original mapping image is defined as including (1,2,3,.…,n-1,n,……) frames (n is an even number); Dividing the original survey image into at least a first path image and a second path image, wherein the first path image and the second path image frames are synchronized, includes: taking the (1,2,3,.…,n-1,n,..…)th frame of the original survey image as the first path image, and taking the (1,2,3,.…,n-1,n,……)th frame of the original survey image as the second path image; After performing color enhancement or color reduction on at least one of the RGB three channels of the nth frame of the second image to obtain the enhanced nth frame image, the method further includes: obtaining the nth frame image of the first image, and using the nth frame image of the first image as a reference frame, performing texture enhancement on the enhanced nth frame image.

4. The method as described in claim 1, characterized in that, The enhanced image includes one or more of the following values: (e1=200%,e2=0,e3=0), (e1=0,e2=200%,e3=0), (e1=0,e2=0,e3=10%).

5. A mapping image enhancement method based on UAV remote sensing technology, characterized in that, include: Original mapping images are acquired using an RGB image sensor; The original survey image is divided into at least a first image and a second image, wherein the first image and the second image are obtained by interleaving frames based on the original survey image; The first image is either directly output or processed and then output as a regular image. At least one of the RGB three channels in the second image is color-enhanced or color-reduced to obtain an enhanced image; the enhanced image enhances the boundary information between the water area, the urban area, and the vegetation area; The regular image and the enhanced image can be displayed separately or together; The R channel of the RGB three channels in the second image is enhanced to obtain an enhanced image, thereby enhancing the boundary information between the water area and other geographical feature areas; Alternatively, the G channel can be enhanced to obtain an enhanced image, thereby enhancing the boundary information between urban areas and other geographic feature areas; or the B channel can be weakened to obtain an enhanced image, thereby enhancing the boundary information between vegetated areas and other geographic feature areas. The principle formula is as follows: ； R, G, and B are the brightness values ​​of the R, G, and B pixels in the image sensor, respectively; a and b are the spectral ranges of the image light picked up by the image sensor; fa(λ) is the spectral curve of the image light reaching the image sensor; R(λ), G(λ), and B(λ) are the spectral response curves of the image sensor, respectively; and e1, e2, and e3 are the coefficients for color enhancement or color reduction of the R, G, and B channels, respectively, with values ​​ranging from [0, 200%].

6. The method as described in claim 5, characterized in that, Displaying the regular image and the enhanced image together includes: displaying the regular image and the enhanced image on two separate displays, or displaying them in a split-screen manner on the same display.

7. The method as described in claim 6, characterized in that, Displaying the regular image and the enhanced image on two independent displays includes: the two independent displays alternately updating the regular image and the enhanced image, such that the update frame rate of the displayed image is half of the frame rate of the original survey image; Alternatively, split-screen display on the same display includes: when the same display displays the regular image and the enhanced image in split-screen mode, the regular image and the enhanced image are updated alternately to make the update frame rate of the displayed image half of the frame rate of the original survey image.

8. The method according to any one of claims 5-7, characterized in that, The original mapping image is defined as including (1,2,3,.…,n-1,n,……) frames (n is an even number); The original survey image is divided into at least a first image and a second image, wherein the first image and the second image are obtained by interleaving the original survey image, including: taking the (1,3,5,..…,n-1,……)th frame of the original survey image as the first image, and taking the (2,4,6,..…,n,.…)th frame of the original survey image as the second image; After performing color enhancement or color reduction on at least one of the RGB three channels of the nth frame of the second image to obtain the enhanced nth frame image, the method further includes: obtaining the (n-1)th frame image of the first image, and using the (n-1)th frame image of the first image as a reference frame, performing texture enhancement on the enhanced nth frame image.

Images