CN117451012A - Unmanned aerial vehicle aerial photography measurement method and system - Google Patents
Unmanned aerial vehicle aerial photography measurement method and system Download PDFInfo
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Abstract
The invention relates to the technical field of image processing, in particular to an unmanned aerial vehicle aerial photography measurement method and system, comprising the following steps: acquiring an RGB image set of unmanned aerial vehicle aerial photography; acquiring all images to be enhanced of an aerial RGB image set of each unmanned aerial vehicle according to the enhancement necessity of the aerial RGB image of each unmanned aerial vehicle; enhancing each image to be enhanced according to enhancement factors of R, G, B three-color channels of each image to be enhanced to obtain all enhanced images; and (5) measuring according to the enhanced image, and updating the area. The unmanned aerial vehicle aerial photography measurement result is more accurate.
Description
Technical Field
The invention relates to the technical field of image processing, in particular to an unmanned aerial vehicle aerial photography measurement method and system.
Background
Unmanned aerial vehicle shooting technology is a technology for shooting in the air by using an unmanned aerial vehicle, and the core of the technology is to use the unmanned aerial vehicle to carry shooting equipment, such as a camera and other sensors, to capture images or data of the ground or landscape from the air; can be applied to various applications including land mapping, environmental monitoring, urban planning, agriculture, forestry, mining, disaster management, etc.; therefore, proper enhancement processing is performed on aerial images, so that the detection accuracy is greatly improved.
However, the enhancement of the image based on the RGB channel generally uses a fixed enhancement coefficient, but due to complex scene conditions in the photographed image, the fixed enhancement coefficient may cause excessive enhancement or distortion of a part of the image, so that the accuracy of the subsequent image-based data measurement is low.
Disclosure of Invention
In order to solve the problems, the invention provides an unmanned aerial vehicle aerial photography measurement method and system.
The embodiment of the invention provides an unmanned aerial vehicle aerial photography measurement method, which comprises the following steps of:
acquiring an aerial RGB image set of an unmanned aerial vehicle, wherein the aerial RGB image set of the unmanned aerial vehicle comprises a plurality of aerial RGB images of the unmanned aerial vehicle;
acquiring a brightness histogram of each unmanned aerial vehicle aerial RGB image according to the brightness of all pixel points in each unmanned aerial vehicle aerial RGB image; acquiring the enhancement necessity of each aerial RGB image according to the brightness histogram of each aerial RGB image; screening all aerial RGB images of the unmanned aerial vehicle in the aerial RGB image set according to the enhancement necessity to obtain all images to be enhanced;
acquiring an enhancement factor of an R color channel of the image to be enhanced according to the R color channel histogram and the enhancement necessity of the image to be enhanced; acquiring enhancement factors of a G color channel of the image to be enhanced according to the G color channel histogram of the image to be enhanced and the enhancement necessity; acquiring enhancement factors of a B color channel of the image to be enhanced according to the B color channel histogram of the image to be enhanced and the enhancement necessity; acquiring an enhanced brightness value of each pixel point in the image to be enhanced according to the enhancement factor of the R, G, B color channel of the image to be enhanced;
and obtaining all the enhanced images according to the enhanced brightness value of each pixel point in the image to be enhanced.
Preferably, the method for obtaining the enhancement necessity of each unmanned aerial vehicle aerial RGB image according to the brightness histogram of each unmanned aerial vehicle aerial RGB image includes the following specific steps:
acquisition of the firstObtaining the brightness histogram change trend of the RGB image aerial taken by the unmanned aerial vehicle to obtain the +.>The brightness position of the RGB image aerial taken by the unmanned aerial vehicle is centralized, and the +.>Brightness histogram trend and the th of an aerial RGB image of an unmanned aerial vehicleThe product of the brightness position concentration of the RGB images aerial by the unmanned aerial vehicle is recorded as a first product +.>Will->As->Enhancement necessity of RGB image aerial by unmanned aerial vehicle,/->An exponential function based on a natural constant is represented.
Preferably, the acquiring a firstThe specific formula of the change trend of the brightness histogram of the RGB image aerial taken by the unmanned aerial vehicle is as follows:
in the method, in the process of the invention,representing the brightness maximum value of all pixel points in all the RGB images aerial photographed by the unmanned aerial vehicle; />Representing the minimum brightness value of all pixel points in all the RGB images aerial taken by the unmanned aerial vehicle; />Is indicated at +.>The brightness in the brightness histogram of the RGB image of the aerial photo of the unmanned aerial vehicle is +.>Corresponding vertical coordinate values; />Is indicated at +.>The brightness in the brightness histogram of the RGB image of the aerial photo of the unmanned aerial vehicle is +.>Corresponding to the ordinate value.
Preferably, the acquiring a firstThe brightness position concentration of the RGB image aerial taken by the unmanned aerial vehicle comprises the following specific methods:
the maximum brightness value of all pixel points in all the RGB images aerial photographed by the unmanned aerial vehicle is matched with the firstThe difference value of the brightness maximum values of all pixel points in the RGB image aerial taken by the unmanned aerial vehicle is recorded as a first difference value, and the +.>The difference value between the minimum brightness value of all pixel points in the aerial RGB image of the unmanned aerial vehicle and the minimum brightness value of all pixel points in the aerial RGB image of the unmanned aerial vehicle is recorded as a second difference value, and the ratio of the first difference value to the second difference value is used as the first difference value>The brightness position of the aerial RGB image of the unmanned aerial vehicle is centralized.
Preferably, the method for screening all aerial RGB images of the unmanned aerial vehicle in the aerial RGB image set according to the enhancement necessity to obtain all images to be enhanced comprises the following specific steps:
if at firstThe enhancement necessity of RGB images aerial taken by the unmanned aerial vehicle is greater than or equal to that of the RGB images aerial taken by the unmanned aerial vehicleIn threshold parameter->Will be->The RGB image aerial taken by the unmanned aerial vehicle is recorded as the image to be enhanced.
Preferably, the specific formula for obtaining the enhancement factor of the R color channel of the image to be enhanced according to the R color channel histogram and the enhancement necessity of the image to be enhanced is as follows:
in the method, in the process of the invention,enhancement factors representing R color channels of an image to be enhanced; />Representing enhancement necessity of an image to be enhanced; />Representing the average value of R color channel values of all pixel points in the image to be enhanced; />Representing the maximum value of the ordinate in the R color channel histogram of the image to be enhanced; />Representing the maximum value of R color channel values of all pixel points in the image to be enhanced; />Representing the minimum value of R color channel values of all pixel points in the image to be enhanced; />Representing a linear normalization function.
Preferably, the specific formula for obtaining the enhancement factor of the G color channel of the image to be enhanced according to the G color channel histogram and the enhancement necessity of the image to be enhanced is as follows:
in the method, in the process of the invention,enhancement factors representing the G color channel of the image to be enhanced; />Representing the average value of the G color channel values of all pixel points in the image to be enhanced; />Representing the maximum value of the ordinate in the histogram of the G color channel of the image to be enhanced;representing the maximum value of the G color channel values of all pixel points in the image to be enhanced; />Representing the minimum value of the G color channel values of all pixel points in the image to be enhanced; />Representing a linear normalization function.
Preferably, the specific formula for obtaining the enhancement factor of the B color channel of the image to be enhanced according to the B color channel histogram and the enhancement necessity of the image to be enhanced is as follows:
in the method, in the process of the invention,enhancement factors representing the B color channels of the image to be enhanced; />Representing the average value of the B color channel values of all pixel points in the image to be enhanced; />Representing the maximum value of the ordinate in the B color channel histogram of the image to be enhanced; />Representing the maximum value of the B color channel values of all pixel points in the image to be enhanced; />Representing the minimum value of the B color channel values of all pixel points in the image to be enhanced; />Representing a linear normalization function.
Preferably, the specific formula for obtaining the enhanced brightness value of each pixel point in the image to be enhanced according to the enhancement factor of the R, G, B color channel of the image to be enhanced is as follows:
in the method, in the process of the invention,representing the +.>Enhanced luminance values for individual pixels; />Representing the first image to be enhancedR color channel values for the individual pixels; />Representing the +.>G color channel values for the individual pixels; />Representing the +.>B color channel values for the individual pixels; />Enhancement factors representing R color channels of an image to be enhanced; />Enhancement factors representing the G color channel of the image to be enhanced; />Representing enhancement factors for the B color channels of the image to be enhanced.
The invention also provides an unmanned aerial vehicle aerial photography measurement system, which comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor realizes the steps of any unmanned aerial vehicle aerial photography measurement method when executing the computer program.
The technical scheme of the invention has the beneficial effects that: according to the method, the enhancement factors of R, G, B color channels of the image to be enhanced are obtained according to the R, G, B color channel histogram and the enhancement necessity of the image to be enhanced, so that the enhancement factors of R, G, B color channels are obtained in a self-adaptive mode according to the relative difference of the color channels in each image, images under different brightness and scene conditions are better adapted, the enhancement effect is better improved, and the aerial-vehicle aerial-photographing measurement result is more accurate.
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In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flow chart of steps of a unmanned aerial vehicle aerial photography measurement method of the present invention.
Detailed Description
In order to further describe the technical means and effects adopted by the invention to achieve the preset aim, the following detailed description is given below of a unmanned aerial vehicle aerial photographing measurement method and system according to the invention, which are specific embodiments, structures, features and effects thereof, with reference to the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" means that the embodiments are not necessarily the same. Furthermore, the particular features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
The invention provides a method and a system for unmanned aerial vehicle aerial photography measurement, which are specifically described below with reference to the accompanying drawings.
Referring to fig. 1, a flowchart of steps of a method for unmanned aerial vehicle aerial survey according to an embodiment of the present invention is shown, the method includes the steps of:
step S001: and acquiring an RGB image set of the unmanned aerial vehicle aerial photograph.
It should be noted that, when relevant measurement is performed on aerial images of the unmanned aerial vehicle, because the aerial images have brightness differences due to a large operation time span of the unmanned aerial vehicle, the present embodiment analyzes aerial images in different time periods to perform adaptive enhancement so as to improve image quality and increase accuracy of data measurement.
Specifically, in order to implement the unmanned aerial vehicle aerial photography measurement method provided in this embodiment, firstly, an RGB image set of unmanned aerial vehicle aerial photography needs to be collected, and the specific process is as follows:
taking a sampling time every 1 hour, sequentially shooting the same position area through a camera carried by the unmanned aerial vehicle each time to acquire RGB images aerial taken by the unmanned aerial vehicle, and collecting the RGB images for 24 hours; taking the unmanned aerial vehicle aerial RGB image at each sampling moment as an unmanned aerial vehicle aerial RGB image set.
So far, the RGB image set of the unmanned aerial vehicle is obtained through the method.
Step S002: and acquiring all images to be enhanced of the RGB image set of the unmanned aerial vehicle according to the enhancement necessity of each RGB image of the unmanned aerial vehicle.
It should be noted that, because of the difference in brightness between the aerial RGB images of the unmanned aerial vehicle at different sampling moments, for example, the aerial RGB images of the unmanned aerial vehicle at noon are higher in brightness and clearer, and the aerial RGB images of the unmanned aerial vehicle at evening or midnight are darker and more blurred; therefore, it is necessary to analyze the difference feature definition evaluation of the luminance statistical histograms of a plurality of images to measure the enhancement necessity corresponding to each image, and then screen the image with larger necessity for enhancement.
It should be noted that, since the luminance histogram represents the luminance distribution trend of the pixel points in the image, for the aerial image with lower luminance, the luminance histogram must have a larger number of pixels at the value with lower luminance, while the number of pixels gradually decreases with the increase of the luminance value, and the aerial image with brighter luminance is opposite; the trend of the brightness histogram of the darker aerial image is firstly high and then low, the trend of the brightness histogram of the brighter aerial image is firstly low and then high, and meanwhile, the trend of the curve of the aerial histogram of the brighter aerial image is presented as an increasing trend, and the trend of the curve of the brightness histogram of the darker aerial image is presented as a decreasing trend, so that the trend can be judged based on the pixel quantity difference corresponding to each brightness level in the brightness histogram; and then combining the brightness distribution spans of the brightness histograms to obtain the brightness span positions of the brightness histograms of all avionic images in the whole sampling period, wherein the brightness span positions represent the concentration trend of the brightness distribution in the images, if the brightness histogram positions are closer to the front, the pixels of the images are more concentrated and distributed at the position with darker brightness, otherwise, the pixels of the images are more concentrated and distributed at the position with brighter brightness, and finally, the enhancement necessity of the images is comprehensively measured by combining the indexes.
Specifically, for the RGB image set of unmanned aerial vehicle aerial photographyAny pixel point of RGB image aerial taken by unmanned aerial vehicle is converted into formula +.>And acquiring the brightness of the pixel point. Wherein (1)>Indicate->Brightness of the pixel point of the RGB image aerial by the unmanned aerial vehicle; />Indicate->The pixel point of the RGB image aerial taken by the unmanned aerial vehicle +.>Color channel values; />Indicate->The pixel point of the RGB image aerial taken by the unmanned aerial vehicle +.>Color channel values; />Indicate->The pixel point of the RGB image aerial taken by the unmanned aerial vehicle +.>Color channel values; the image brightness conversion formula for obtaining the brightness of all the pixel points in the RGB image is the prior art, and the embodiment is not described herein in detail.
So far, the brightness of all pixel points in each unmanned aerial vehicle aerial RGB image is obtained.
Further, constructing a luminance histogram of each unmanned aerial vehicle aerial RGB image according to the luminance of the pixel points in each unmanned aerial vehicle aerial RGB image, taking the luminance as the horizontal axis of the luminance histogram, and taking the number of the pixel points as the vertical axis of the luminance histogram, thenThe method for calculating the enhanced necessity of the aerial RGB image of the unmanned aerial vehicle comprises the following steps:
in the method, in the process of the invention,indicate->The enhancement necessity of the RGB image aerial taken by the unmanned aerial vehicle; />Indicate->Brightness histogram variation trend of RGB images aerial by unmanned aerial vehicle; />Indicate->The brightness position of the RGB image aerial taken by the unmanned aerial vehicle is centralized; />Indicate->Brightness maximum value of all pixel points in RGB image aerial taken by unmanned aerial vehicle; />Indicate->Minimum brightness values of all pixel points in RGB images aerial by the unmanned aerial vehicle; />Is indicated at +.>The brightness in the brightness histogram of the RGB image of the aerial photo of the unmanned aerial vehicle is +.>Corresponding vertical coordinate values; />Is indicated at +.>The brightness in the brightness histogram of the RGB image of the aerial photo of the unmanned aerial vehicle is +.>Corresponding vertical coordinate values; />Representing the brightness maximum value of all pixel points in all the RGB images aerial photographed by the unmanned aerial vehicle; />Representing the minimum brightness value of all pixel points in all the RGB images aerial taken by the unmanned aerial vehicle; />An exponential function based on a natural constant is represented.
It should be noted that the number of the substrates,indicate->The brightness histogram trend of the RGB image aerial by the unmanned aerial vehicle, the smaller the value, the description of the +.>The brightness histogram of the aerial RGB image of the unmanned aerial vehicle shows a decreasing trend, the more likely it is to correspond to the darker image, so the greater the enhancement necessity is; if the value is greater, then the +.>The brightness histogram of the aerial RGB image of the unmanned aerial vehicle shows an increasing trend, the more likely the aerial RGB image is corresponding to a brighter image, the less the enhancement necessity is; />Indicate->The brightness position of the RGB image aerial taken by the unmanned aerial vehicle is centralized, if +.>The more the span of the luminance histogram of the RGB image aerial by the unmanned aerial vehicle is concentrated in the first half, i.e. the larger the value of the luminance position concentration, the more likely the image is to be a darker image, the greater the enhancement necessity, and vice versa.
Presetting a threshold parameterWherein the present embodiment uses/>To describe the example, the present embodiment is not particularly limited, wherein +.>Depending on the particular implementation.
If at firstThe enhancement necessity of the RGB image aerial taken by the unmanned aerial vehicle is greater than or equal to the threshold parameter +.>Will be->The RGB image aerial taken by the unmanned aerial vehicle is recorded as the image to be enhanced, if +.>The enhancement necessity of the RGB image aerial taken by the unmanned aerial vehicle is smaller than the threshold parameter +.>Will be->And marking the RGB images aerial by the unmanned aerial vehicle as target images, and further acquiring all images to be enhanced and target images of the RGB image set aerial by the unmanned aerial vehicle.
So far, all images to be enhanced of the RGB image set of the unmanned aerial vehicle are obtained through the method.
Step S003: and enhancing each image to be enhanced according to the enhancement factors of the R, G, B three-color channels of each image to be enhanced, and obtaining all the enhanced images.
It should be noted that, since the brightness difference can be decomposed into the numerical value differences of R, G, B three channels of the RGB image, it is necessary to obtain R, G, B three channel histograms corresponding to each image to be enhanced, and then analyze the distribution trend of the histograms to determine the enhancement factor; the brightness of the image is measured based on the transverse and longitudinal data span ratio of the three-channel histogram, and the average value of the R, G, B three-color channel values can reflect the overall color brightness trend level of the image, so that the enhancement factors can be dequantized through the average value of the R, G, B three-color channel values and the span of the transverse and longitudinal axes.
Specifically, taking any image to be enhanced as an example, constructing an R color channel histogram, a G color channel histogram and a B color channel histogram of the image to be enhanced according to R, G, B three-color channel values of pixel points in the image to be enhanced, taking the R color channel value as the horizontal axis of the R color channel histogram, taking the number of pixel points as the vertical axis of the R color channel histogram, taking the G color channel value as the horizontal axis of the G color channel histogram, taking the number of pixel points as the vertical axis of the G color channel histogram, taking the B color channel value as the horizontal axis of the B color channel histogram, and taking the number of pixel points as the vertical axis of the B color channel histogram, the method for calculating the enhancement factor of R, G, B three-color channels of the image to be enhanced is as follows:
in the method, in the process of the invention,enhancement factors representing R color channels of an image to be enhanced; />Representing enhancement necessity of an image to be enhanced; />Representing the average value of R color channel values of all pixel points in the image to be enhanced; />Representing the maximum value of the ordinate in the R color channel histogram of the image to be enhanced; />Representing the maximum value of R color channel values of all pixel points in the image to be enhanced; />Representing the minimum value of R color channel values of all pixel points in the image to be enhanced; />Enhancement factors representing the G color channel of the image to be enhanced; />Representing the average value of the G color channel values of all pixel points in the image to be enhanced; />Representing the maximum value of the ordinate in the histogram of the G color channel of the image to be enhanced; />Representing the maximum value of the G color channel values of all pixel points in the image to be enhanced; />Representing the minimum value of the G color channel values of all pixel points in the image to be enhanced; />Enhancement factors representing the B color channels of the image to be enhanced; />Representing the average value of the B color channel values of all pixel points in the image to be enhanced; />B color channel straight representing an image to be enhancedMaximum value of ordinate in the square; />Representing the maximum value of the B color channel values of all pixel points in the image to be enhanced; />Representing the minimum value of the B color channel values of all pixel points in the image to be enhanced; />Representing a linear normalization function.
It should be noted that, the average value of the R, G, B three color channel values can reflect the overall color brightness trend level of the image, and if the three values are smaller, the color brightness of the overall image is darker, so that the corresponding enhancement factor of the image to be enhanced is larger;the data span ratio of the abscissa and the ordinate of the three-channel histogram is represented respectively, and the R, G, B statistical characteristics of different images can be reflected, if the corresponding ratio of the channel histogram is larger, the histogram is reflected to be higher and narrower, the corresponding image to be enhanced is darker according to the image characteristics, so that the enhancement factor is larger, otherwise, the smaller the enhancement factor is, the lower the histogram is reflected to be wider, and the corresponding image to be enhanced is brighter, and the enhancement factor is smaller. Then the enhancement necessity of the image to be enhanced is combined, namely, the enhancement factor becomes larger as the enhancement necessity is larger, and becomes smaller as the enhancement necessity is larger.
Specifically, the first image to be enhancedThe method for calculating the enhanced brightness value of each pixel point comprises the following steps:
in the method, in the process of the invention,representing the +.>Enhanced luminance values for individual pixels; />Representing the first image to be enhancedR color channel values for the individual pixels; />Representing the +.>G color channel values for the individual pixels; />Representing the +.>B color channel values for the individual pixels; />Enhancement factors representing R color channels of an image to be enhanced; />Enhancement factors representing the G color channel of the image to be enhanced; />Representing enhancement factors for the B color channels of the image to be enhanced.
Further, the brightness value after enhancement of each pixel point in the image to be enhanced is taken as the brightness of each pixel point in the image to be enhanced, and is recorded as the enhanced image, so that each enhanced image is obtained.
So far, all the enhanced images are obtained by the method.
Step S004: and (5) measuring according to the enhanced image, and updating the area.
Specifically, all the enhanced images are recorded as target images, semantic segmentation is performed on all the target images, all the target images are divided into areas with similar attributes, such as buildings, roads, vegetation and the like, the characteristic information mean value of the area is extracted from the areas of all the target images to serve as the characteristic information of the current area, the characteristic information, such as the area, of the current area is used for updating the area in the map information.
Through the steps, the unmanned aerial vehicle aerial photography measurement method is completed.
The invention also provides an unmanned aerial vehicle aerial photography measurement system, which comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor realizes the steps of any unmanned aerial vehicle aerial photography measurement method when executing the computer program.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the invention, but any modifications, equivalent substitutions, improvements, etc. within the principles of the present invention should be included in the scope of the present invention.
Claims (10)
1. The unmanned aerial vehicle aerial photography measurement method is characterized by comprising the following steps of:
acquiring an aerial RGB image set of an unmanned aerial vehicle, wherein the aerial RGB image set of the unmanned aerial vehicle comprises a plurality of aerial RGB images of the unmanned aerial vehicle;
acquiring a brightness histogram of each unmanned aerial vehicle aerial RGB image according to the brightness of all pixel points in each unmanned aerial vehicle aerial RGB image; acquiring the enhancement necessity of each aerial RGB image according to the brightness histogram of each aerial RGB image; screening all aerial RGB images of the unmanned aerial vehicle in the aerial RGB image set according to the enhancement necessity to obtain all images to be enhanced;
acquiring an enhancement factor of an R color channel of the image to be enhanced according to the R color channel histogram and the enhancement necessity of the image to be enhanced; acquiring enhancement factors of a G color channel of the image to be enhanced according to the G color channel histogram of the image to be enhanced and the enhancement necessity; acquiring enhancement factors of a B color channel of the image to be enhanced according to the B color channel histogram of the image to be enhanced and the enhancement necessity; acquiring an enhanced brightness value of each pixel point in the image to be enhanced according to the enhancement factor of the R, G, B color channel of the image to be enhanced;
and obtaining all the enhanced images according to the enhanced brightness value of each pixel point in the image to be enhanced.
2. The unmanned aerial vehicle aerial photography measurement method according to claim 1, wherein the step of obtaining the enhancement necessity of each unmanned aerial vehicle aerial photography RGB image according to the brightness histogram of each unmanned aerial vehicle aerial photography RGB image comprises the following specific steps:
acquisition of the firstObtaining the brightness histogram change trend of the RGB image aerial taken by the unmanned aerial vehicle to obtain the +.>The brightness position of the RGB image aerial taken by the unmanned aerial vehicle is centralized, and the +.>Brightness histogram trend and +.>The product of the brightness position concentration of the RGB images aerial by the unmanned aerial vehicle is recorded as a first product +.>Will->As->Personal unmanned aerial vehicleEnhancement necessity of an aerial RGB image, < ->An exponential function based on a natural constant is represented.
3. The unmanned aerial vehicle aerial survey method of claim 2, wherein the acquiring the firstThe specific formula of the change trend of the brightness histogram of the RGB image aerial taken by the unmanned aerial vehicle is as follows:
in the method, in the process of the invention,representing the brightness maximum value of all pixel points in all the RGB images aerial photographed by the unmanned aerial vehicle; />Representing the minimum brightness value of all pixel points in all the RGB images aerial taken by the unmanned aerial vehicle; />Is indicated at +.>The brightness in the brightness histogram of the RGB image of the aerial photo of the unmanned aerial vehicle is +.>Corresponding vertical coordinate values; />Is indicated at +.>The brightness in the brightness histogram of the RGB image of the aerial photo of the unmanned aerial vehicle is +.>Corresponding to the ordinate value.
4. The unmanned aerial vehicle aerial survey method of claim 2, wherein the acquiring the firstThe brightness position concentration of the RGB image aerial taken by the unmanned aerial vehicle comprises the following specific methods:
the maximum brightness value of all pixel points in all the RGB images aerial photographed by the unmanned aerial vehicle is matched with the firstThe difference value of the brightness maximum values of all pixel points in the RGB image aerial taken by the unmanned aerial vehicle is recorded as a first difference value, and the +.>The difference value between the minimum brightness value of all pixel points in the aerial RGB image of the unmanned aerial vehicle and the minimum brightness value of all pixel points in the aerial RGB image of the unmanned aerial vehicle is recorded as a second difference value, and the ratio of the first difference value to the second difference value is used as the first difference value>The brightness position of the aerial RGB image of the unmanned aerial vehicle is centralized.
5. The unmanned aerial vehicle aerial photography measurement method according to claim 1, wherein the specific method for screening all unmanned aerial vehicle aerial photographed RGB images in the unmanned aerial vehicle aerial photographed RGB image set according to the enhancement necessity to obtain all images to be enhanced comprises the following steps:
if at firstRGB image of unmanned aerial vehicle aerial photoIs greater than or equal to the threshold parameter +.>Will be->The RGB image aerial taken by the unmanned aerial vehicle is recorded as the image to be enhanced.
6. The unmanned aerial vehicle aerial photography measurement method according to claim 1, wherein the specific formula for acquiring the enhancement factor of the R color channel of the image to be enhanced according to the R color channel histogram and the enhancement necessity of the image to be enhanced is:
in the method, in the process of the invention,enhancement factors representing R color channels of an image to be enhanced; />Representing enhancement necessity of an image to be enhanced; />Representing the average value of R color channel values of all pixel points in the image to be enhanced; />Representing the maximum value of the ordinate in the R color channel histogram of the image to be enhanced; />Representing the maximum value of R color channel values of all pixel points in the image to be enhanced;representation ofThe minimum value of R color channel values of all pixel points in the image to be enhanced; />Representing a linear normalization function.
7. The unmanned aerial vehicle aerial photography measurement method according to claim 1, wherein the specific formula for acquiring the enhancement factor of the G color channel of the image to be enhanced according to the G color channel histogram and the enhancement necessity of the image to be enhanced is:
in the method, in the process of the invention,enhancement factors representing the G color channel of the image to be enhanced; />Representing the average value of the G color channel values of all pixel points in the image to be enhanced; />Representing the maximum value of the ordinate in the histogram of the G color channel of the image to be enhanced; />Representing the maximum value of the G color channel values of all pixel points in the image to be enhanced; />Representing the minimum value of the G color channel values of all pixel points in the image to be enhanced; />Representing a linear normalization function.
8. The unmanned aerial vehicle aerial photography measurement method according to claim 1, wherein the specific formula for acquiring the enhancement factor of the B color channel of the image to be enhanced according to the B color channel histogram and the enhancement necessity of the image to be enhanced is:
in the method, in the process of the invention,enhancement factors representing the B color channels of the image to be enhanced; />Representing the average value of the B color channel values of all pixel points in the image to be enhanced; />Representing the maximum value of the ordinate in the B color channel histogram of the image to be enhanced; />Representing the maximum value of the B color channel values of all pixel points in the image to be enhanced; />Representing the minimum value of the B color channel values of all pixel points in the image to be enhanced; />Representing a linear normalization function.
9. The unmanned aerial vehicle aerial photography measurement method according to claim 1, wherein the specific formula for obtaining the enhanced brightness value of each pixel point in the image to be enhanced according to the enhancement factor of the R, G, B color channel of the image to be enhanced is as follows:
in the method, in the process of the invention,representing the +.>Enhanced luminance values for individual pixels; />Representing the +.>R color channel values for the individual pixels; />Representing the +.>G color channel values for the individual pixels; />Representing the +.>B color channel values for the individual pixels; />Enhancement factors representing R color channels of an image to be enhanced; />Enhancement factors representing the G color channel of the image to be enhanced; />Representing enhancement factors for the B color channels of the image to be enhanced.
10. A unmanned aerial vehicle aerial survey system comprising a memory, a processor and a computer program stored in the memory and running on the processor, wherein the processor, when executing the computer program, implements the steps of a unmanned aerial vehicle aerial survey method as claimed in any one of claims 1 to 9.
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