CN111145362B - Virtual-real fusion display method and system for airborne comprehensive vision system - Google Patents
Virtual-real fusion display method and system for airborne comprehensive vision system Download PDFInfo
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Abstract
The invention belongs to the field of onboard graphic image processing, and relates to a virtual-real fusion display method and system of an onboard comprehensive vision system. According to the virtual-real fusion display method of the airborne comprehensive vision system, disclosed by the invention, the accurate positions of the runway and the obstacle are accurately indicated through the sub-pixel accuracy matching of the real-time multi-mode video and the synthetic vision map picture, the comprehensive vision picture is enhanced in color and texture through image and graphic fusion, and the geometric correction fusion is further carried out on the three-dimensional image of the obstacle, so that the organic fusion display of the multi-mode video and the synthetic vision map picture is finally realized. The method can effectively improve the accurate perception of the space position form of the airfield runway and the obstacle by the pilot under the condition of low visibility, improve the situational awareness, reduce the typical accidents such as controllable flight collision, runway invasion and the like in the process of flying near and landing, and improve the safety of the aircraft.
Description
Technical Field
The invention belongs to the field of onboard graphic image processing, and relates to a virtual-real fusion display method of an onboard comprehensive vision system.
Background
And a Comprehensive Vision System (CVS) or an Enhanced Synthetic Vision System (ESVS), wherein the integrated vision system (CVS) or the Enhanced Synthetic Vision System (ESVS) is used for providing the pilot with equivalent visual video picture information of an airport runway, dangerous terrain and obstacles in the flight approaching stage through the fusion of the multi-mode video and the three-dimensional digital map. The method combines the advantages of large view field, high resolution and true color of a Synthetic Vision System (SVS) and the advantages of real-time multi-mode (long-wave infrared, short-wave infrared and millimeter wave) video penetrating weather obstacle imaging of an Enhanced Vision System (EVS). The virtual-real integrated comprehensive vision real-time picture obviously improves the scene consciousness of pilots and enhances the flight safety.
In the traditional comprehensive vision system, due to errors such as inherent navigation parameters and sensor calibration, a certain registration error exists between a synthesized vision picture and an enhanced vision picture, and in order to reduce perception barriers caused by inconsistency of virtual and real pictures, two existing solutions exist, one is to window and display a multi-mode video picture in the synthesized vision virtual picture in a picture-in-picture mode, and neglect inconsistency of window edges. Another is to superimpose a simplified displayed map wire frame (frame) graphic on the multi-modal video picture, indicating the runway, obstacle and terrain.
The two modes inevitably have certain picture inconsistency, and interfere the cognition and judgment of pilots on the environment. In addition, the synthesized view picture and the enhanced view picture do not obtain accurate registration and fusion, and lack accurate key position indication of runways, obstacles and the like and detail information of identifiable real scene color textures and the like.
Disclosure of Invention
The invention provides a method for fusion display of virtual and real images of a comprehensive view, which aims to improve the accuracy of virtual and real fusion of the comprehensive view and the readability of the images.
The technical scheme of the invention is as follows:
the virtual-real fusion display method of the airborne comprehensive vision system comprises the following steps:
1) Acquiring current airborne positioning information, corresponding map elevation data and an orthophoto, and combining flight attitude information to obtain a rough registration map picture consistent with a current frame of the multi-mode video sensor;
2) Taking the rough registration map picture as a floating image f and taking a current multi-mode video frame as a reference image f R Optimizing to obtain a corrected map picture with sub-pixel registration accuracy according to the established error energy function related to affine transformation between the floating image and the reference image;
3) Carrying out HSV color space decomposition on the corrected map picture to obtain decomposed chromaticity, saturation and brightness components, and carrying out image fusion on the brightness components and the multi-mode video;
4) Merging the fused brightness component with the chromaticity and saturation components of the color video frame, and outputting a fusion result;
5) And (3) superposing the established barrier model in the fused image picture in the step (4), and rendering and outputting a virtual-real fused comprehensive view picture.
Based on the scheme, the invention further optimizes the following steps:
optionally, step 1) specifically comprises: and inquiring and synthesizing a three-dimensional digital map database of the view based on airborne positioning information, obtaining map elevation data near an airport and a map orthographic image of a set range of the forward viewing direction of the airplane, and performing perspective projection transformation on map pictures (namely pictures rendered based on the map elevation data and the map orthographic image) by combining the flight attitude information and sensor internal parameters (main points, focal lengths and the like) obtained by calibrating the multi-mode video sensor to obtain a rough registration map picture consistent with the current frame of the multi-mode video sensor.
Optionally, in step 1), the rough registration map picture is drawn according to a pinhole imaging principle in computer vision.
Optionally, step 2) specifically comprises: adopting a Normalized Total Gradient (NTG) as an error energy function of affine transformation between the floating image and the reference image, and optimizing and solving the error energy function by an iteration method to obtain affine transformation parameters under the condition of minimum error energy function, namely, the geometric transformation relation between the floating image and the reference image; and finally, performing geometric transformation on the floating image to obtain a corrected map picture with sub-pixel registration accuracy.
Optionally, in step 3), the luminance component and the multi-mode video are subjected to image fusion, specifically, a fusion method based on saliency is adopted, and a laplace operator is applied pixel by pixel in the luminance component image of the color video frame and the multi-mode video frame, so as to obtain an initial saliency image; guiding and filtering the initial saliency image, and outputting a smooth saliency image; and taking the saliency image brightness value as a weighting weight, carrying out pixel-by-pixel weighted average on the brightness component of the color video frame and the multi-mode video frame, and outputting the fused brightness component.
Optionally, in step 5), the obstacle model is obtained by recalculating the obstacle point, line, plane position and texture coordinates in the three-dimensional space according to the geometric transformation relation between the floating image and the reference image (corresponding to the corrected map image obtained in step 2).
The on-board positioning information includes longitude, latitude and altitude; the flight attitude information includes pitch, roll, yaw data.
Correspondingly, the invention also provides an onboard comprehensive vision system virtual-real fusion display system, which comprises:
the coarse registration module is used for acquiring current airborne positioning information, corresponding map elevation data and an orthographic image, and combining flight attitude information to obtain a coarse registration map picture consistent with the current frame of the multi-mode video sensor;
the fine registration module is used for taking the coarse registration map picture as a floating image f and taking a current multi-mode video frame as a reference image f R Optimizing to obtain a corrected map picture with sub-pixel registration accuracy according to the established error energy function related to affine transformation between the floating image and the reference image;
the brightness component fusion module is used for carrying out HSV color space decomposition on the corrected map picture to obtain decomposed chromaticity, saturation and brightness components, and carrying out image fusion on the brightness components and the multi-mode video;
the HSV component merging module is used for merging the fused brightness component with the chromaticity and saturation components of the color video frame and outputting a fusion result;
and the rendering output module is used for superposing the established barrier model in the fused image picture, and rendering and outputting the virtual-real fused comprehensive view picture.
Optionally, the obstacle model is obtained by obtaining a corrected map picture obtained by the fine registration module and recalculating the positions of obstacle points, lines, surfaces and texture coordinates in a three-dimensional space.
Correspondingly, the invention also provides an onboard device which comprises a processor and a program memory, wherein the program stored in the program memory is loaded by the processor to execute the virtual-real fusion display method of the onboard comprehensive vision system.
The invention has the following advantages:
according to the invention, through accurate registration and natural fusion of the real-time multi-mode video and the comprehensive view three-dimensional map picture, the enhanced comprehensive view system display picture with real colors and textures is output, the runway, dangerous terrain and high and large obstacle information are accurately indicated, the space scene perception capability of pilots on the runway and the obstacles of the airport under the condition of low visibility (including haze, rain and snow, sand and dust and night vision conditions) can be improved, and then the typical accidents such as controllable flight collision, runway invasion and the like in the process of approaching and landing of the airplane are reduced, and the safety of the airplane is improved.
Drawings
Fig. 1 is a schematic flow chart of a virtual-real fusion display method of an airborne integrated vision system.
Fig. 2 is a schematic diagram of a geometric correction flow of an obstacle model.
Detailed Description
The invention is further described in detail below with reference to the drawings and examples.
In order to accurately indicate key positions such as runways, obstacles and the like in an output picture of the integrated vision system and simultaneously truly display scene color texture information, the embodiment provides a virtual-real fusion display method of an airborne integrated vision system, which is mainly divided into two parts, namely map video registration and image and graphic fusion, as shown in fig. 1.
1. Map video registration section:
firstly, an airborne GPS information (longitude, latitude and altitude) is utilized to inquire a three-dimensional digital map database of the synthesized view, and map elevation data and orthographic images in the vicinity of an airport and in a certain range of the forward direction of the airplane are obtained. And performing perspective projection transformation on the map picture by combining external parameters such as flight attitude information (pitching, rolling and yawing) and internal parameters such as principal point and focal length obtained by calibrating the multi-mode video sensor, and drawing a rough registration map picture consistent with the current frame of the multi-mode video sensor according to a pinhole imaging principle in computer vision.
Secondly, considering that the map picture and the comprehensive view real-time multi-mode video frame meet the affine transformation relation of the two-dimensional plane, taking the map picture as a floating image f and taking the multi-mode video frame as a reference image f R An error energy function is established for affine transformation between the floating image and the reference image. In this embodiment a normalized total gradient (Normalized Total Gradient, NTG) is used as an energy function of affine transformation between floating and reference images, i.e
In the above-mentioned method, the step of,
is a gradient sign, II 1 Is the L1 norm.
And optimizing and solving the error energy function by an iteration method, and obtaining affine transformation parameters under the condition of minimum error energy function, namely the geometric transformation from the floating image to the reference image.
And finally, performing geometric transformation on the floating image to obtain a corrected map picture which is registered with the reference image by sub-pixels.
2. Image graphics fusion:
firstly, carrying out HSV color space decomposition on the registered map picture to obtain decomposed chrominance, saturation and brightness image components. Because the multi-mode video frame has only a luminance component, the luminance component of the map picture is image-fused with the multi-mode video. In the process of image fusion, a fusion method based on saliency is adopted. And extracting an image saliency initial value by using a Laplacian operator, and outputting fusion weights after carrying out smooth optimization on the initial saliency image by using a guide filter. And further carrying out pixel-by-pixel weighted average on the map picture brightness component and the multi-mode image by using the saliency map weighting and outputting a brightness component fusion result. And finally, merging the fused brightness component with the chroma and saturation components of the original color video frame, and outputting the video frame which is weighted and fused based on the image saliency.
Further, according to the affine transformation relation between the precisely registered map frames and the multi-mode video plane, the positions and texture coordinates of the obstacle points, lines and planes are recalculated in the three-dimensional space and are overlapped in the fused image frames, finally, the fused multi-mode video frames and the corrected obstacle models are uniformly rendered by using graphics engines such as OpenGL, and the virtual and real fused comprehensive vision frames are output.
Because the multi-mode video and the map texture in the comprehensive view are accurately registered, the planar runway images and the three-dimensional obstacle model are accurately indicated. Meanwhile, the map picture is a clear image shot in sunny weather, so that the map picture has rich colors and textures and has higher identification degree. The virtual-real fusion display comprehensive visual picture has better readability through the migration of colors and textures.
An example application is given below:
in the map video registration part, the longitude and latitude of an airplane at the current video frame time point are read through an onboard integrated navigation device, a three-dimensional digital map database is queried, three-dimensional digital map elevation Data (DEM) and an orthographic image (DOM) within the same view angle of the forward-looking multi-mode video camera in the forward-looking direction of the airplane at the current position are retrieved, the current longitude, latitude, altitude information and pitching, rolling and yawing information are converted into a geocentric earth fixed (ECEF) coordinate system, and the synthetic view map picture under the virtual video camera is calculated by combining the relative rotation translation parameters between the multi-mode video sensor and the machine body coordinate system and the internal parameters such as the principal point, focal length and the like of the multi-mode video sensor.
Because of errors of navigation parameters and calibration data, a map picture generated by the virtual camera has a certain registration error with a video frame imaged in real time. The affine transformation relation is approximately considered to be satisfied between the map picture and the real-time video frame, affine transformation parameters corresponding to the map picture and the multi-mode video frame are taken as optimization objects, error energy constructed by taking the normalized total gradient as the optimization parameters is subjected to iterative optimization, and accurate affine transformation parameters are obtained. Because the map picture and the multi-mode video frame are already registered initially, the iterative optimization process can converge faster, and the registration parameters of the sub-pixel level are output.
The pixel position of any pixel point of the multi-mode video frame in the map picture can be positioned by applying the perspective transformation model and the accurate registration model. In order to prevent the phenomenon of data loss such as 'white-out', a map picture after correction is generated by adopting a reverse mapping interpolation method. And (3) applying the geometric transformation to any point position on the multi-mode video, inquiring the pixel position in the map picture, and performing bilinear interpolation with adjacent pixels to obtain a corresponding pixel value of the map picture. And finally, obtaining the precisely registered synthetic vision virtual map picture after reverse mapping.
In the image and graph fusion part, HSV chromaticity, saturation and brightness decomposition are firstly applied to the registered synthetic vision virtual map picture, and a map picture brightness image of a single channel and a multi-mode image of the single channel are extracted for fusion. Traversing the map picture brightness image and the multi-mode image, and obtaining a rough saliency image by using the Laplacian operator. And taking the map picture brightness image as a guide image, guiding and filtering the saliency image corresponding to the map picture brightness, and outputting the smoothed map picture brightness saliency image. And taking the multi-mode video frame as a guide image, guiding and filtering the multi-mode video frame saliency image, and outputting the smoothed multi-mode video frame saliency image. And then, carrying out normalized weight calculation on the corresponding saliency image of the smoothed map picture brightness image and the saliency image of the multi-mode video frame, and acquiring a higher weight value by the pixel with a higher value. And then, the brightness image corresponding to the map picture and the multi-mode video frame image are weighted and averaged according to the pixel-by-pixel weight value, and the fused brightness image is obtained. And merging the fused brightness image with the chromaticity image and the saturation image of the map picture, and outputting the fused multi-mode video frame.
After the image fusion is completed, geometric correction fusion is carried out on the three-dimensional figure of the obstacle. As shown in fig. 2, coordinate values of each vertex of the three-dimensional figure of the virtual obstacle are firstly obtained, projection transformation is carried out by applying internal parameters and external parameters of the camera, and accurate registration affine transformation calculated in one step is applied after the projection transformation, so that the position of a pixel of the three-dimensional figure of the obstacle is correctly displayed. And inquiring the longitude and latitude corresponding to the pixel position in the map picture according to the coordinates of the pixel position. Correcting longitude and latitude values of each fixed point of the three-dimensional obstacle graph according to the inquired longitude and latitude, keeping the height value unchanged, and outputting a corrected three-dimensional obstacle model. And then, the multi-mode video after image fusion and the corrected obstacle model are sent to an OpenGL state machine to perform unified graphics rendering, and a final virtual and real image graphics fusion picture of the comprehensive vision system is output.
Claims (10)
1. The utility model provides an airborne integrated vision system virtual-real fusion display method which is characterized by comprising the following steps:
1) Acquiring current airborne positioning information, corresponding map elevation data and an orthophoto, and combining flight attitude information to obtain a rough registration map picture consistent with a current frame of the multi-mode video sensor;
2) Taking the rough registration map picture as a floating image f and taking a current multi-mode video frame as a reference image f R Optimizing to obtain a corrected map picture with sub-pixel registration accuracy according to the established error energy function related to affine transformation between the floating image and the reference image;
3) Carrying out HSV color space decomposition on the corrected map picture to obtain decomposed chromaticity, saturation and brightness components, and carrying out image fusion on the brightness components and the multi-mode video;
4) Merging the fused brightness component with the chromaticity and saturation components of the color video frame, and outputting a fusion result;
5) And (3) superposing the established barrier model in the fused image picture in the step (4), and rendering and outputting a virtual-real fused comprehensive view picture.
2. The method for displaying virtual-real fusion of an airborne integrated vision system according to claim 1, wherein the step 1) is specifically: and inquiring and synthesizing a three-dimensional digital map database of the view based on airborne positioning information, obtaining map elevation data near an airport and a map orthographic image of a set range of forward viewing directions of the airplane, and performing perspective projection transformation on a map picture by combining flight attitude information and sensor internal parameters obtained by calibrating a multi-mode video sensor to obtain a rough registration map picture consistent with a current frame of the multi-mode video sensor.
3. The method for displaying the virtual-real fusion of the airborne integrated vision system according to claim 1, wherein in the step 1), the rough registration map picture is drawn according to a pinhole imaging principle in computer vision.
4. The method for displaying virtual-real fusion of an airborne integrated vision system according to claim 1, wherein the step 2) is specifically: adopting a Normalized Total Gradient (NTG) as an error energy function of affine transformation between the floating image and the reference image, and optimizing and solving the error energy function by an iteration method to obtain affine transformation parameters under the condition of minimum error energy function, namely, the geometric transformation relation between the floating image and the reference image; and finally, performing geometric transformation on the floating image to obtain a corrected map picture with sub-pixel registration accuracy.
5. The method for displaying the virtual-real fusion of the airborne integrated vision system according to claim 1, wherein in the step 3), the luminance component and the multi-mode video are subjected to image fusion, specifically, a fusion method based on saliency is adopted, and a laplace operator is applied pixel by pixel in a luminance component image of a color video frame and the multi-mode video frame, so as to obtain an initial saliency image; guiding and filtering the initial saliency image, and outputting a smooth saliency image; and taking the saliency image brightness value as a weighting weight, carrying out pixel-by-pixel weighted average on the brightness component of the color video frame and the multi-mode video frame, and outputting the fused brightness component.
6. The method according to claim 1, wherein the obstacle model in step 5) is obtained by recalculating the positions of the obstacle points, lines, planes and texture coordinates in a three-dimensional space according to the geometric transformation relationship between the floating image and the reference image.
7. The method for displaying virtual-real fusion of an on-board integrated vision system according to claim 1, wherein the on-board positioning information includes longitude, latitude and altitude; the flight attitude information includes pitch, roll, yaw data.
8. An airborne integrated vision system virtual-real fusion display system, which is characterized by comprising:
the coarse registration module is used for acquiring current airborne positioning information, corresponding map elevation data and an orthographic image, and combining flight attitude information to obtain a coarse registration map picture consistent with the current frame of the multi-mode video sensor;
the fine registration module is used for taking the coarse registration map picture as a floating image f and taking a current multi-mode video frame as a reference image f R Optimizing to obtain a corrected map picture with sub-pixel registration accuracy according to the established error energy function related to affine transformation between the floating image and the reference image;
the brightness component fusion module is used for carrying out HSV color space decomposition on the corrected map picture to obtain decomposed chromaticity, saturation and brightness components, and carrying out image fusion on the brightness components and the multi-mode video;
the HSV component merging module is used for merging the fused brightness component with the chromaticity and saturation components of the color video frame and outputting a fusion result;
and the rendering output module is used for superposing the established barrier model in the fused image picture, and rendering and outputting the virtual-real fused comprehensive view picture.
9. The on-board integrated vision system virtual-real fusion display system of claim 8, wherein: the obstacle model is obtained by recalculating the positions and texture coordinates of obstacle points, lines and planes in a three-dimensional space by acquiring a corrected map picture obtained by the fine registration module.
10. An on-board device comprising a processor and a program memory, wherein the program stored in the program memory performs the virtual-real fusion display method of the on-board integrated vision system as claimed in claim 1 when loaded by the processor.
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