CN112839228B - Unmanned aerial vehicle image processing and transmitting method - Google Patents
Unmanned aerial vehicle image processing and transmitting method Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
- H04N19/134—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
- H04N19/167—Position within a video image, e.g. region of interest [ROI]
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
- G06V10/22—Image preprocessing by selection of a specific region containing or referencing a pattern; Locating or processing of specific regions to guide the detection or recognition
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
- G06V10/26—Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion
- G06V10/267—Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion by performing operations on regions, e.g. growing, shrinking or watersheds
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/14—Relay systems
- H04B7/15—Active relay systems
- H04B7/185—Space-based or airborne stations; Stations for satellite systems
- H04B7/18502—Airborne stations
- H04B7/18506—Communications with or from aircraft, i.e. aeronautical mobile service
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
- H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
- H04N19/17—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
- H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
- H04N19/182—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being a pixel
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
Abstract
An unmanned aerial vehicle image processing and transmission method relates to an image processing technology. It comprises the following steps: uniformly dividing an image shot by the unmanned aerial vehicle into a plurality of independent areas; judging the image information in each individual area, and dividing an important identification area, a secondary identification area and other identification areas; calculating the duty ratio of the important identification area in the image segmentation total area; setting a pixel compression value for each individual region corresponding to the important recognition region, the secondary recognition region and the other recognition regions; performing compression operation according to the pixel compression value set in each independent area; converting the compressed image information corresponding to each independent area into a corresponding data format for storage and transmission operation; after the ground receiving device finishes data receiving, the data is converted into a corresponding image by using an image restoration technology. The unmanned aerial vehicle image processing system is convenient for storing and transmitting images, so that the pressure of an unmanned aerial vehicle image processor is reduced, and the stability and high definition of unmanned aerial vehicle images are ensured.
Description
Technical Field
The invention relates to an image processing technology, in particular to an improvement of unmanned aerial vehicle image processing and transmission.
Background
The related technology of unmanned aerial vehicles at home and abroad is developed rapidly, and unmanned aerial vehicle systems are various in variety, wide in application and vivid in characteristics, so that the unmanned aerial vehicle systems have large differences in various aspects such as size, quality, voyage, endurance, flying height, flying speed, tasks and the like.
The unmanned aerial vehicle plays a great role in aerial photography, and due to the advantages of the unmanned aerial vehicle in control and popularization of various high-definition cameras, high-definition photos and high-definition videos aerial taken by the unmanned aerial vehicle are widely applied. As the popularity of high-definition photos and high-definition videos leads to higher and higher requirements on processors of high-definition images and high-definition videos, the space occupied by the images is larger and larger, the requirements on the processors and memories are higher and higher, the pressure on data transmission is higher and higher, particularly high-definition live video broadcasting is very attractive for the processors of unmanned aerial vehicles.
Although some companies develop image processing and transmission methods special for unmanned aerial vehicles, most of the processing methods are realized by image lossy compression, which has great damage to the image itself and great loss to the photographed high-definition picture.
Disclosure of Invention
Aiming at the defects and shortcomings of the prior art, the invention provides an unmanned aerial vehicle image processing and transmitting method, which can process pictures shot by an unmanned aerial vehicle under the current conditions and obtain more optimized image data, is convenient for storing and transmitting images, thereby relieving the pressure of an unmanned aerial vehicle image processor and ensuring the stability and high definition of unmanned aerial vehicle images.
In order to achieve the above purpose, the invention adopts the following technical scheme: it comprises the following steps: (1) uniformly dividing an image shot by the unmanned aerial vehicle into N independent areas through an image processor arranged on the unmanned aerial vehicle; (2) judging the image information in each individual area by an image processor arranged on the unmanned aerial vehicle by using an image recognition technology, and dividing an important recognition area A, a secondary recognition area B and other recognition areas C; the divided important recognition areas A are sequentially named as follows: high pixel areas A1 to An; the divided secondary identification areas B are named in order: middle pixel areas B1 to Bn; the other divided recognition areas C are sequentially named: low pixel regions C1 to Cn; meanwhile, calculating the duty ratio of the important identification area A in the image segmentation total area; (3) setting pixel compression values for each individual area corresponding to the important identification area A, the secondary identification area B and the other identification areas C through an image processor arranged on the unmanned aerial vehicle; wherein the pixel compression value of the important recognition area A is 100%; the pixel compression value of the secondary identification area B is 50% -60%; the pixel compression value of the other recognition areas C is 20% -30%; (4) performing compression operation according to the pixel compression values set by each independent area through an image processor arranged on the unmanned aerial vehicle; meanwhile, converting the compressed image information corresponding to each independent area into a corresponding data format for storage; (5) transmitting the data converted according to the image information to a ground receiving device through an image processor arranged on the unmanned aerial vehicle; (6) after the ground receiving device finishes data receiving, the data is converted into a corresponding image by using an image restoration technology.
In the step (1), the number of the equally divided individual areas n=9, 16, 25, 36 and … is increased by n= (3+m) 2 Where m=0, 1, 2, 3, 4 ….
In the step (1), the default initial value n=9 of the number of the divided individual areas, and the step (2) is adopted to judge that if the duty ratio of the important identification area a does not exceed 50%, the pixel compression operation of each individual area is executed; if the ratio of the important identification area A exceeds 50%, the number of the divided areas is automatically increased and changed to N=16; after the division is completed, the judgment in the step (2) is carried out again, and if the duty ratio of the important identification area A does not exceed 50%, the compression operation of each individual area is executed; if the ratio exceeds 50%, the number of the divided areas is automatically increased and changed to n=25; and so on, the value N of the segmentation area finally meets the condition that the proportion of the important identification area A in the total image area is not more than 50 percent.
In the step (5), the transmission mode is segment continuous transmission; the image processor is provided with an independent compression processing function, a data conversion function and a data transmission function, and each function can independently and continuously operate; immediately converting the pixel compression of the single region into corresponding data after the image processor completes the pixel compression of the single region; after finishing data conversion, starting data transmission; meanwhile, other independent areas can still carry out pixel compression, data conversion and data transmission operation.
The working principle of the invention is as follows: uniformly dividing an image shot by the unmanned aerial vehicle into N independent areas through an image processor arranged on the unmanned aerial vehicle; judging the image information in each independent area by using an image recognition technology, further dividing an important recognition area A, a secondary recognition area B and other recognition areas C, and further perfecting a segmentation value N according to the duty ratio of the important recognition area A; setting pixel compression values corresponding to an important identification area A, a secondary identification area B and other identification areas C, and then carrying out image compression operation by an image processor according to the pixel compression values corresponding to the independent areas; after the image compression is completed, the image processor converts the image into corresponding data for storage and transmission according to the compressed image information; after the ground receiving device finishes data receiving, the data is converted into a corresponding image by using an image restoration technology.
After the technical scheme is adopted, the invention has the beneficial effects that: the method is characterized by changing the mode of lossy compression of the whole image by the traditional unmanned aerial vehicle, dividing the image into a plurality of areas, and carrying out pixel compression according to different demand proportions; the method is flexible and changeable, and on the premise of ensuring stable and high-definition images, redundant pixels of the images are greatly reduced, the storage space of the unmanned aerial vehicle is saved, and the pressure of an image processor of the unmanned aerial vehicle is reduced; in the transmission process of image data, segmented continuous transmission is adopted, so that the transmission efficiency of images is effectively improved.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only some embodiments of the invention, and that other drawings can be obtained according to these drawings without inventive faculty for a person skilled in the art.
FIG. 1 is a flow chart of an image processing and transmission method of the present invention;
fig. 2 is a schematic diagram illustrating steps (1), (2) in a specific embodiment.
Detailed Description
Referring to fig. 1, the technical scheme adopted in this embodiment is as follows: it comprises the following steps: (1) uniformly dividing an image shot by the unmanned aerial vehicle into N independent areas through an image processor arranged on the unmanned aerial vehicle; (2) judging the image information in each individual area by an image processor arranged on the unmanned aerial vehicle by using an image recognition technology, and dividing an important recognition area A, a secondary recognition area B and other recognition areas C; the divided important recognition areas A are sequentially named as follows: high pixel areas A1 to An; the divided secondary identification areas B are named in order: middle pixel areas B1 to Bn; the other divided recognition areas C are sequentially named: low pixel regions C1 to Cn; meanwhile, calculating the duty ratio of the important identification area A in the image segmentation total area; (3) setting pixel compression values for each individual area corresponding to the important identification area A, the secondary identification area B and the other identification areas C through an image processor arranged on the unmanned aerial vehicle; the pixel compression value of the important identification area A is 100%, so that the pixels of the important identification area A of the image are ensured to the greatest extent, and the stability and the high definition of the image are further ensured; the pixel compression value of the secondary identification area B is 50% -60%, the pixels of the secondary identification area B are reduced, the image is ensured to have a certain definition, and meanwhile, the storage space of the image can be effectively reduced; the pixel compression value of other recognition areas C is 20% -30%, so that the storage space of the image is greatly reduced, and the transmission efficiency of the image is further improved; (4) performing compression operation according to the pixel compression values set by each independent area through an image processor arranged on the unmanned aerial vehicle; compared with the compression of the whole image, the compression of the single area effectively reduces the pressure of an unmanned aerial vehicle image processor, thereby improving the image compression processing time; meanwhile, converting the compressed image information corresponding to each independent area into a corresponding data format for storage; (5) transmitting the data converted according to the image information to a ground receiving device through an image processor arranged on the unmanned aerial vehicle; (6) after the ground receiving device finishes data receiving, the data is converted into a corresponding image by using an image restoration technology; the pixels of the generated image are far smaller than those of the image shot by the unmanned aerial vehicle, so that the storage space is saved.
Further, in the step (1), the number of the divided individual areas is n=9, 16, 25, 36 and …, and the increment rule is n= (3+m) 2 Where m=0, 1, 2, 3, 4 ….
Further, in the step (1), the default initial value n=9 of the number of the divided individual areas is determined in the step (2), and if the duty ratio of the important identification area a does not exceed 50%, the pixel compression operation is performed for each individual area; if the ratio of the important identification area A exceeds 50%, the number of the divided areas is automatically increased and changed to N=16; after the division is completed, the judgment in the step (2) is carried out again, and if the duty ratio of the important identification area A does not exceed 50%, the compression operation of each individual area is executed; if the ratio exceeds 50%, the number of the divided areas is automatically increased and changed to n=25; and so on, the value N of the segmentation area finally meets the condition that the proportion of the important identification area A in the total image area is not more than 50 percent. The image processing mode can reduce pixels of images shot by the unmanned aerial vehicle to the greatest extent, and further greatly saves the storage space of the unmanned aerial vehicle.
As shown in fig. 2, the steps (1) and (2) are illustrated as follows:
the image is divided into nine individual regions of the same area. Assuming that the main purpose of unmanned aerial vehicle shooting is to show the condition of a ship in a river, an important identification area A shown in the figure is easily divided by analyzing the segmented image, and the important identification areas are sequentially named as a high pixel area A1, a high pixel area A2, a high pixel area A3 and a high pixel area A4; setting an image on a river bank as a secondary identification area B, and sequentially naming the secondary identification area B as a middle pixel area B1 and a middle pixel area B2; the image in the sky is set as another recognition area C, and is named a low pixel area C1, a low pixel area C2, and a low pixel area C3 in this order. The duty ratio of the important identification areas A in the image segmentation total area is calculated, and the number of the important identification areas A is four through statistics, wherein the duty ratio is 4/9. Therefore, the duty ratio of the important recognition area a does not exceed 50%, and the image processor performs pixel compression for each individual area by the corresponding pixel compression value.
Further, in the step (5), the transmission mode is segment continuous transmission; the image processor is provided with an independent compression processing function, a data conversion function and a data transmission function, and each function can independently and continuously operate; immediately converting the pixel compression of the single region into corresponding data after the image processor completes the pixel compression of the single region; after finishing data conversion, starting data transmission; meanwhile, other independent areas can still carry out pixel compression, data conversion and data transmission operation; the segment continuous transmission can effectively reduce the time required by the data transmission process, thereby improving the data transmission efficiency.
After the technical scheme is adopted, the invention has the beneficial effects that: the method is characterized by changing the mode of lossy compression of the whole image by the traditional unmanned aerial vehicle, dividing the image into a plurality of areas, and carrying out pixel compression according to different demand proportions; the method is flexible and changeable, and on the premise of ensuring stable and high-definition images, redundant pixels of the images are greatly reduced, the storage space of the unmanned aerial vehicle is saved, and the pressure of an image processor of the unmanned aerial vehicle is reduced; in the transmission process of image data, segmented continuous transmission is adopted, so that the transmission efficiency of images is effectively improved.
The foregoing is merely illustrative of the present invention and not restrictive, and other modifications and equivalents thereof may occur to those skilled in the art without departing from the spirit and scope of the present invention.
Claims (3)
1. The unmanned aerial vehicle image processing and transmitting method is characterized in that: it comprises the following steps: (1) uniformly dividing an image shot by the unmanned aerial vehicle into N independent areas through an image processor arranged on the unmanned aerial vehicle; (2) judging the image information in each individual area by an image processor arranged on the unmanned aerial vehicle by using an image recognition technology, and dividing an important recognition area A, a secondary recognition area B and other recognition areas C; the divided important recognition areas A are sequentially named as follows: high pixel areas A1 to An; the divided secondary identification areas B are named in order: middle pixel areas B1 to Bn; the other divided recognition areas C are sequentially named: low pixel regions C1 to Cn; meanwhile, calculating the duty ratio of the important identification area A in the image segmentation total area; (3) setting pixel compression values for each individual area corresponding to the important identification area A, the secondary identification area B and the other identification areas C through an image processor arranged on the unmanned aerial vehicle; wherein the pixel compression value of the important recognition area A is 100%; the pixel compression value of the secondary identification area B is 50% -60%; the pixel compression value of the other recognition areas C is 20% -30%; (4) performing compression operation according to the pixel compression values set by each independent area through an image processor arranged on the unmanned aerial vehicle; meanwhile, converting the compressed image information corresponding to each independent area into a corresponding data format for storage; (5) transmitting the data converted according to the image information to a ground receiving device through an image processor arranged on the unmanned aerial vehicle; (6) after the ground receiving device finishes data receiving, the data is converted into a corresponding image by using an image restoration technology;
in the step (1), the default initial value n=9 of the number of the divided individual areas, and the step (2) is adopted to judge that if the duty ratio of the important identification area a does not exceed 50%, the pixel compression operation of each individual area is executed; if the ratio of the important identification area A exceeds 50%, the number of the divided areas is automatically increased and changed to N=16; after the division is completed, the judgment in the step (2) is carried out again, and if the duty ratio of the important identification area A does not exceed 50%, the compression operation of each individual area is executed; if the ratio exceeds 50%, the number of the divided areas is automatically increased and changed to n=25; and so on, the value N of the segmentation area finally meets the condition that the proportion of the important identification area A in the total image area is not more than 50 percent.
2. The unmanned aerial vehicle image processing and transmission method of claim 1, wherein: in the step (1), the number of the divided individual areas n=9, 16, 25, 36 and … is increased by n= (3+m) 2, where m=0, 1, 2, 3 and 4 ….
3. The unmanned aerial vehicle image processing and transmission method of claim 1, wherein: in the step (5), the transmission mode is segment continuous transmission; the image processor is provided with an independent compression processing function, a data conversion function and a data transmission function, and each function can independently and continuously operate; immediately converting the pixel compression of the single region into corresponding data after the image processor completes the pixel compression of the single region; after finishing data conversion, starting data transmission; meanwhile, other independent areas can still carry out pixel compression, data conversion and data transmission operation.
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