Method for calculating number of pictures in oblique photography rectangular measurement area

Abstract

The invention belongs to the technical field of unmanned aerial vehicle oblique photography, and discloses an oblique photography rectangular measurement area photo number calculation method, which comprises the following steps: determining a proper ground resolution according to actual needs; calculating the projection of the image width on the ground according to the ground resolution; determining a lateral overlapping degree; determining the route spacing by combining the lateral overlapping degree; dividing the measuring area length by the route spacing to obtain the course route number; dividing the width of the measuring area by the horizontal coverage range of a single photo to obtain the number of each course photo; dividing the length of the measuring area by the vertical coverage range of the single photo to obtain the number of each lateral photo; and based on the calculation process, obtaining the total photo number of the final oblique photography. According to the method for calculating the number of the photos in the oblique photography rectangular measurement area, proper parameters can be determined according to needs before the unmanned aerial vehicle flies, repeated flight is avoided, resources are saved, and working efficiency is improved.

Description

Technical Field

[0001] The invention relates to the technical field of unmanned aerial vehicle oblique photography, and in particular to a method for calculating the number of oblique photography rectangular survey area photos. Background Art

[0002] Drone oblique photography technology is widely used in the field of 3D modeling and visualization. The various parameters set by the drone before collecting data have a great impact on the size of the oblique image dataset and the accuracy of the model. Too much overlap will lead to a large dataset and difficulty in subsequent model processing, while too little overlap will lead to incomplete model accuracy and structure, which cannot meet the needs of actual applications.

[0003] The existing technology's parameter settings are basically fixed within a certain range. Appropriate parameters are tried according to the range, but the corresponding parameters cannot be set and selected according to the actual application scenario. Often, unreasonable data selection is discovered after 3D modeling. Moreover, the process of oblique photography 3D modeling is extremely slow. If the wrong parameters are selected, it will waste a lot of time. After re-determining the parameters, the flight is repeated, resulting in a huge waste of resources.

[0004] Therefore, in response to the above problems, a technical solution is needed that can determine the appropriate parameters according to needs before the UAV flies to avoid repeated flights. For example, if there is a certain amount of target photos, it can be achieved by adjusting the GSD or overlap. Or if you want to achieve higher model quality without considering the amount of data, you can achieve it by lowering the flight altitude and increasing the overlap. Or for some new types of UAVs or lenses, only their basic parameters (such as the length and short sides of the sensor, focal length) are needed to determine the appropriate parameters. Summary of the invention

[0005] The purpose of the present invention is to provide a method for calculating the number of photos of a rectangular survey area in oblique photography, which can determine appropriate parameters according to needs before the UAV flies, avoid repeated flights, save resources and improve work efficiency.

[0006] To achieve the above object, the present invention provides a method for calculating the number of oblique photography rectangular measurement area photos, comprising the following steps:

[0007] Step S1, determining an appropriate ground resolution according to actual needs;

[0008] Step S2, calculating the projection of the image width on the ground according to the ground resolution determined in step S1;

[0009] Step S3, determining the lateral overlap;

[0010] Step S4, determining the route spacing in combination with the lateral overlap;

[0011] Step S5, dividing the length of the measurement area by the route spacing to obtain the number of heading routes;

[0012] Step S6: Divide the width of the survey area by the horizontal coverage of a single photo to obtain the number of photos in each heading direction; divide the length of the survey area by the vertical coverage of a single photo to obtain the number of photos in each lateral direction;

[0013] Step S7: Based on the above calculation process, the total number of photos of the final oblique photography is obtained.

[0014] Preferably, in step S1, a suitable ground resolution is determined according to actual needs, and then the flight altitude of the drone is determined as follows:

[0015]

[0016] Among them, H is the flight altitude, in meters; f is the focal length of the lens, in millimeters; GSD is the ground resolution, in meters; a is the pixel size, in millimeters; Among them, GSD determines the clarity of the photo, and thus determines the accuracy of the 3D model. By calculating H through GSD, the accuracy of the 3D model can be guaranteed before the flight.

[0017] Preferably, in step S2, according to the ground resolution GSD and the flight height H determined in step S1, the projection X of the image width on the ground is calculated as follows:

[0018]

[0019] Where x is the long dimension of the sensor.

[0020] Preferably, in step S3, the lateral overlap is determined as follows:

[0021]

[0022] Where X is the projection of the image width on the ground; N is the projection length of the non-overlapping part of the two images on the ground, and R2 is the lateral overlap.

[0023] Preferably, in step S4, the route spacing D is determined in combination with the lateral overlap, as shown below:

[0024]

[0025] Preferably, the length of the measurement area is divided by the route spacing to obtain the number of heading routes K1, as shown below:

[0026]

[0027] Where L is the length of the survey area. Considering that the number of routes is an integer, we round it up to get

[0028] Preferably, in step S6, the width of the survey area is divided by the horizontal coverage of a single photo to obtain the number of photos per heading n1, as shown below:

[0029]

[0030] Where W is the width of the measurement area; C w is the coverage width of a single photo;

[0031] Similarly, the number of side photos in each line is n2, as shown below:

[0032]

[0033] Among them, C L is the coverage length of a single photo.

[0034] Preferably, in step S7, based on the above calculation process, the total number of photos n of the final oblique photography is obtained as follows:

[0035]

[0036] Therefore, the present invention adopts the above-mentioned method for calculating the number of photos of a rectangular survey area in oblique photography, which can determine appropriate parameters according to needs before the UAV flies, avoid repeated flights, save resources, and improve work efficiency.

[0037] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a flow chart of a method for calculating the number of photos of a rectangular measurement area in oblique photography according to the present invention;

[0039] Figure 2 It is a comparison diagram of the errors between the results obtained by the photo number calculation method of the present invention and the actual flight data. DETAILED DESCRIPTION

[0040] The technical solution of the present invention is further described below through the accompanying drawings and embodiments.

[0041] like Figure 1 As shown, the present invention provides a method for calculating the number of oblique photography rectangular measurement area photos, comprising the following steps:

[0042] Step S1, determining an appropriate ground resolution according to actual needs;

[0043] Step S2, calculating the projection of the image width on the ground according to the ground resolution determined in step S1;

[0044] Step S3, determining the lateral overlap;

[0045] Step S4, determining the route spacing in combination with the lateral overlap;

[0046] Step S5, dividing the length of the measurement area by the route spacing to obtain the number of heading routes;

[0047] Step S6: Divide the width of the survey area by the horizontal coverage of a single photo to obtain the number of photos in each heading direction; divide the length of the survey area by the vertical coverage of a single photo to obtain the number of photos in each lateral direction;

[0048] Step S7: Based on the above calculation process, the total number of photos of the final oblique photography is obtained.

[0049] Example

[0050] The purpose of selecting a smaller area for surveying is to avoid excessive overlap, which will lead to an excessively large number of data sets and have a greater impact on subsequent actual flights and subsequent 3D modeling. The UAV is flown in the direction of the long side of the survey area, which can cover the area to a greater extent and improve the image quality. At the same time, it can avoid the UAV constantly turning when flying along the short side, which will lead to a decrease in work efficiency.

[0051] The size of the dataset and the accuracy of the model are not only related to the camera parameters, but also closely related to the flight parameters set when the drone is flying. For example, the flight altitude will affect the ground resolution and thus indirectly affect the model accuracy. The study is about flat and open areas, and the impact of elevation and altitude on the parameters is not considered. The parameter selection and the impact of parameter selection on the number of photos can be carried out according to the following steps:

[0052] S1. First, determine the appropriate ground resolution GSD according to actual needs, and then determine the flight altitude of the drone, as shown below:

[0053]

[0054] Among them, H is the flight altitude in meters, f is the focal length of the lens in millimeters, GSD is the ground resolution in meters, and a is the pixel size in millimeters. GSD determines the clarity of the photo, and thus determines the accuracy of the 3D model. By calculating H through GSD, the accuracy of the 3D model can be guaranteed before the flight.

[0055] S2. The length / width covered by a single photo is the product of GSD and pixel length / width. Based on the GSD and flight altitude H determined in step S1, calculate the projection X of the image width on the ground as follows:

[0056]

[0057] Where x is the long dimension of the sensor.

[0058] S3. Determine the lateral overlap, that is, the ratio of the non-overlapping portion to the image width, as follows:

[0059]

[0060] Where X is the projection of the image width on the ground; N is the projection length of the non-overlapping part of the two images on the ground, and R2 is the lateral overlap.

[0061] The heading overlap refers to the overlap between the flight clips on the same route, and the lateral overlap refers to the overlap between the flight clips of two adjacent routes. The lateral spacing refers to the distance between adjacent routes. Different lateral overlaps have their own appropriate lateral spacing, so the corresponding lateral spacing under different overlaps must be determined first.

[0062] S4. Combined with the lateral overlap, determine the flight line spacing D, that is, the size of the image width projected on the ground, as shown below:

[0063]

[0064] S5. Divide the length of the survey area by the route spacing to obtain the number of heading routes K1, as shown below:

[0065]

[0066] Where L is the length of the survey area. Considering that the number of routes is an integer, we round it up to get

[0068] S6. Divide the width of the survey area by the horizontal coverage of a single photo to obtain the number of photos per heading n1, as shown below:

[0069]

[0070] Where W is the width of the measurement area; C w is the coverage width of a single photo.

[0071] Similarly, the number of side photos in each line is n2, as shown below:

[0072]

[0073] Among them, C L is the coverage length of a single photo.

[0074] S7. Since the research object is a regular grid flight pattern, the total number of routes is the number of heading routes multiplied by the number of single route photos. This is because in general, the heading spacing D is relatively small, and there is no need to fly and take photos on the long side of the survey area.

[0075] Therefore, when the heading spacing D is small, the total number of photos n of the final oblique photography is obtained as follows:

[0076]

[0077] like Figure 2 As shown, the X-axis represents the heading overlap, the Y-axis represents the lateral overlap, and the Z-axis is the error between the calculation method of the present invention and the actual flight data. Experimental results show that the error between the actual flight photos and the data obtained by the present invention is kept within 5%.

[0078] Therefore, the present invention adopts the above-mentioned method for calculating the number of photos of a rectangular survey area in oblique photography, which can determine appropriate parameters according to needs before the UAV flies, avoid repeated flights, save resources, and improve work efficiency.

[0079] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or replace the technical solution of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solution to deviate from the spirit and scope of the technical solution of the present invention.

Claims

1. A method for calculating the number of photos of a rectangular survey area in oblique photography, characterized in that: The following steps are involved: Step S1, determining an appropriate ground resolution according to actual needs; Step S2, calculating the projection of the image width on the ground according to the ground resolution determined in step S1; Step S3, determining the lateral overlap; Step S4, determining the route spacing in combination with the lateral overlap; Step S5, dividing the length of the measurement area by the route spacing to obtain the number of heading routes; Step S6: Divide the width of the survey area by the horizontal coverage of a single photo to obtain the number of photos in each heading direction; divide the length of the survey area by the vertical coverage of a single photo to obtain the number of photos in each lateral direction; Step S7: Based on the above calculation process, the total number of photos of the final oblique photography is obtained.

2. The method for calculating the number of rectangular area photos of oblique photography according to claim 1, characterized in that: In step S1, the appropriate ground resolution is determined according to actual needs, and then the flight altitude of the UAV is determined as follows: Among them, H is the flight altitude, in meters; f is the focal length of the lens, in millimeters; GSD is the ground resolution, in meters; a is the pixel size, in millimeters; Among them, GSD determines the clarity of the photo, and thus determines the accuracy of the 3D model. By calculating H through GSD, the accuracy of the 3D model can be guaranteed before the flight.

3. The method for calculating the number of rectangular area photos of oblique photography according to claim 2, characterized in that: In step S2, according to the ground resolution GSD and the flight altitude H determined in step S1, the projection X of the image width on the ground is calculated as follows: Where x is the long dimension of the sensor.

4. The method for calculating the number of rectangular area photos of oblique photography according to claim 3, characterized in that: In step S3, the lateral overlap is determined as follows: Where X is the projection of the image width on the ground; N is the projection length of the non-overlapping part of the two images on the ground, and R2 is the lateral overlap.

5. The method for calculating the number of rectangular area photos in oblique photography according to claim 4, characterized in that: In step S4, the route spacing D is determined in combination with the lateral overlap, as shown below:

6. The method for calculating the number of rectangular area photos in oblique photography according to claim 5, characterized in that: In step S5, the length of the survey area is divided by the route spacing to obtain the number of heading routes K1, as shown below: Where L is the length of the survey area. Considering that the number of routes is an integer, we round it up to get 7. The method for calculating the number of rectangular area photos in oblique photography according to claim 6, characterized in that: In step S6, the width of the survey area is divided by the horizontal coverage of a single photo to obtain the number of photos per heading n1, as shown below: Where W is the width of the measurement area; C w is the coverage width of a single photo; Similarly, the number of side photos in each line is n2, as shown below: Among them, C L is the coverage length of a single photo.

8. The method for calculating the number of rectangular area photos in oblique photography according to claim 7, characterized in that: In step S7, based on the above calculation process, the total number of photos n of the final oblique photography is obtained as follows:

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