CN109636840B - Method for detecting building shadow based on ghost image - Google Patents

Method for detecting building shadow based on ghost image Download PDF

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CN109636840B
CN109636840B CN201811566632.9A CN201811566632A CN109636840B CN 109636840 B CN109636840 B CN 109636840B CN 201811566632 A CN201811566632 A CN 201811566632A CN 109636840 B CN109636840 B CN 109636840B
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roof
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周国清
沙洪俊
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Guilin University of Technology
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
    • G06T17/05—Geographic models
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/50—Depth or shape recovery
    • G06T7/507—Depth or shape recovery from shading
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/70—Determining position or orientation of objects or cameras

Abstract

The invention discloses a method for detecting building shadows based on ghost images, which comprises the following steps: 1. secondarily utilizing the traditional orthorectification result (ghost image); 2. searching and correcting a shadow inflection point with relatively small error through photogrammetric knowledge analysis; 3. the coordinate of the shadow inflection point with relatively small error is used for solving the solar altitude angle and the solar azimuth angle in the DBM to detect shadows on a ghost roof (a roof obtained by orthorectification) and the ground in the ghost image, and finally, the complete shadow detection result is displayed through layer overlapping. The method for detecting the building shadow can effectively avoid the problem that the boundary of the shadow zone projected on the roof cannot be detected in the prior method, thereby improving the detection rate on the roof by 33.33 percent. The method is simple to operate, improves the speed of shadow detection, and saves the detection cost.

Description

Method for detecting building shadow based on ghost image
Technical Field
The invention belongs to the field of aerial photogrammetry, relates to a method for detecting building shadows based on ghost images, and particularly relates to an accurate calculation method for solar altitude angles, solar azimuth angles and building roof shadow areas, so that ghost images achieve the effect of true orthographic images.
Background
The image obtained after the traditional orthorectification treatment does not completely consider the geographic information of the shadow of the building, so that the space target of the shadow area deviates from the original position, and the accuracy and the usability of the orthorectification image are greatly influenced by the shadow of the building. Therefore, in order to improve the quality of the corrected image, the detection of the shadow becomes a necessary step in the correction process of the ortho image.
The traditional shadow detection method based on a model mainly establishes a shadow statistical model for parameters such as the geometric shape of a scene, the solar altitude, DSM or a sensor and the like according to the shadow property, and judges one pixel by one pixel. For example, Rau (2002) proposed to detect building shadow regions by projection geometry and use local histogram matching to enhance the grayscale features to improve image interpretability and reduce the image contribution from radiance. Tong (2013) proposes building a three-dimensional (3D) building model from data stored in a geographic information system. And calculating to obtain a theoretical shadow area of the building. And extracting polygons of the ground shadow area of the building. The calculated average value is compared with a preset threshold value to determine the threshold values of different types of shadows so as to detect the shadow area, the process does not need to extract the shadows from the image, and errors are greatly prevented from being introduced in feature extraction.
Nevertheless, the existing model-based shadow detection methods still have the following problems in terms of integrity between walls, on roofs and as a whole of urban buildings: shadows cast on the roof are still not fully detected; it is difficult to accurately detect shadows and building boundaries; the recognition degree of the whole shadow area is not high, and a large ascending space still exists in the detection precision.
Disclosure of Invention
The invention provides a method for detecting building shadows based on ghost images, which aims to solve the problems that the overall recognition degree is not high and the roof shadows cannot be correctly detected in the conventional shadow detection method.
In order to achieve the technical purpose, the technical scheme of the invention comprises the following specific steps:
step 1, converting the original image and the ghost image file into a gray image for processing. A Digital Building Model (DBM) file is loaded.
And 2, analyzing and seeking a building shadow inflection point with relatively small inclination error and projection error from the original aerial image, so that the point has relatively small image point displacement difference.
In actual work, three points of a shadow point with relatively small error, a photographing center and an object point corresponding to the shadow point with relatively small error in an original image cannot be completely idealized to meet the collinearity, so that the shadow point searched in the step 1 needs to be corrected for corresponding image deformation, objective lens distortion, atmospheric refraction and earth curvature and substituted into a collinearity equation to obtain the geographic coordinate of the point in the DBM.
According to the principle of light straight-line propagation, a building corresponding to a shadow point with relatively small error (point E1 in the schematic diagram of FIG. 1 is a shadow point with relatively small error, so that the shadow boundary error corresponding to Bldg1 in a ghost image is minimum, and the shadow area range is regarded as error-free in an ideal state for convenience of explanation) is determined in the DBM model, and height information of the building and geographical coordinates of a roof inflection point of the building corresponding to the point are obtained through MATLAB.
By utilizing the geometrical relationship of the spatial three-dimensional layers, the relative position of the sunlight is determined in the DBM, namely the relative orientation of the boundary of the shadow area of the building caused by the sunlight at the shooting moment is determined: solar altitude, solar azimuth.
And 3, combining the geometric relation, and solving the shadow point projected on the ground by the inflection point of the building according to the solved solar altitude angle and solar azimuth angle. And the shadow points on the ground are connected in sequence, so that the relatively complete shadow area of the building thrown on the ground at the shooting moment can be determined.
And 4, combining the geometric relation, and solving a shadow point projected by the inflection point of the building on the roof of the adjacent sheltered building according to the solved solar altitude angle and solar azimuth angle. And the shadow points on the roof are connected in sequence, so that the relatively complete shadow area of the building falling on the roof of the shielding building at the shooting moment can be determined.
Step 5, extracting the building roof by using an 8-communicated seed growth method to obtain the building roof; determining shadow areas of all buildings in the experimental area in the DBM according to the step 3 and the step 4; finally, the result is displayed in the ghost image, namely the shadow detection result in the ghost image is obtained, and the result is superposed with the roof of the building and the detected shadow on the roof for display.
Drawings
FIG. 1 is a diagram of the relationship between building shadows before and after proactive correction in an embodiment of the present invention.
FIG. 2 is a diagram of the shaded areas detected in a DBM according to an embodiment of the invention.
FIG. 3 is a display diagram of a detected ground shadow in a ghost image according to an embodiment of the present invention.
FIG. 4 is a representation of a shadow area on a ghost roof detected in an embodiment of the present invention in a DBM.
FIG. 5 is a diagram illustrating an overall result of shadow detection according to an embodiment of the present invention.
FIG. 6 is a flow chart of an embodiment of the present invention.
Detailed Description
The following detailed description of embodiments of the invention refers to the accompanying drawings. It is to be understood that the embodiments described are only some of the embodiments of the invention, and not all of them. All other embodiments, which can be made by those skilled in the art without any inventive presupposition based on the embodiments of the present invention, belong to the scope of the present invention.
The implementation case is as follows:
in this embodiment, an aerial image of a certain foreign area is selected for occlusion detection processing. The aerial image was taken by an RC30 aerial camera, where the adjacent images covering the central urban area were dv1119 and dv1120, with a course overlap of 65%. Buildings in the image are complex and various, and a large amount of shielding phenomena are caused.
In specific implementation, the technical scheme of the invention can be implemented in a mode of automatic operation of computer programming.
The specific operation steps of the ghost shadow detection program provided by the present invention can refer to the flowchart 4:
step 1, loading an image file.
And converting the original image and the ghost image file into a gray image for processing. A Digital Building Model (DBM) file is loaded.
In this embodiment, the image dv1119 has been subjected to conventional orthorectification to generate a ghost image. The ghost image of the loading process is orthodv 1119. The storage format of a corresponding Digital Building Model (DBM) vector file is N rows and two columns, wherein each building is separated by pline-x, the first column in the file stores an x coordinate, the second column in the file stores a y coordinate, a ground elevation value and a roof elevation value are respectively stored in the last two rows of each building model, and the height of the building can be calculated through the two elevation values of the roof and the ground. And when the program runs to pline-x, judging that the information of the next building is automatically read. Therefore, in the processing process, the loop statements can be used for reading respectively, the inflection point plane coordinates of each building are stored in a two-dimensional array, and the inflection point plane coordinates are drawn into a three-dimensional model by combining the elevation h of the building.
Step 2, combining the DBM with the image by calculating a geodetic coordinate value corresponding to the lower left corner of the image, so as to obtain a roof position obtained by traditional orthorectification in the ghost image; and analyzing and finding by referring to photogrammetry related knowledge: the shadow points which are closer to the geometric line and have smaller image diameters have smaller image point displacement, so that an image point needs to be searched near the geometric line of the original aerial image to reduce the influence of image point displacement difference caused by image inclination. Finally, a shadow point with small image point displacement is determined in the original image, and the obtained shadow point still has a system error, so that the system error correction needs to be carried out on the shadow point.
The systematic errors of the image point coordinates include the deformation of aerial photography, the distortion of objective lens, the atmospheric refractive error and the influence of the curvature of the earth. Therefore, the correct coordinates of the image point are obtained by correcting the distortion of the image pickup film, the distortion of the objective lens, the atmospheric refractive error and the earth curvature of the acquired image point. The concrete correction steps are as follows:
deformation of the photographic film: (x ', y') is the standard frame distance or the standard coordinate of the frame; (x, y) is the actual frame distance or the actual coordinates of the frame.
Figure GDA0002997951400000041
Solving the transformation parameter a by the equation of the formula columni，bi(i ═ 0,1,2,3), and finally, the image point correction coordinates are calculated by the equation.
Distortion of the objective lens: undetermined parameter k can be detected through an aerial survey instrumentn(n is 0,1,2,3), r. And (4) correcting according to the object point coordinates in the formula (2).
x'＝x(1-k1-k2·r2-k3·r4-k4·r6......)
y'＝y(1-k1-k2·r2-k3·r4-k4·r6......) (2)
Atmospheric refractive difference: since the image point at the base point has no atmospheric refractive difference and the distance between the equiangular point and the base point is small enough, the shadow point with relatively small error selected by us can ignore the influence of the factor.
Curvature of the earth: the shadow detection is based on DBM, and shadow points with relatively small errors are selected from a ground plane, so that the influence of terrain relief does not need to be considered.
Step 3, determining the ground shadow point P through the collinear equation (3)shadowI.e. E in principle fig. 11Geographical coordinates (X) of pointsE1,YE1,ZE1)。
Figure GDA0002997951400000042
Wherein xp is1、yp1Is P1The image plane coordinates of (a); x is the number of0、y0F is the internal orientation element of the image; xS、YS、ZSIs an exterior orientation element of the image; a isi、bi、ci(i ═ 1,2,3) is the 9 direction cosines of the 3 outward orientation elements of the image.
According to the straight line propagation principle of light, a building corresponding to a shadow point with relatively small error is determined in the DBM model. Obtaining height information of a building and geographic coordinates of a building roof inflection point corresponding to a shadow point with relatively small error, namely a point E, through MATLAB1The geographic coordinates of (a).
Determining the altitude and square of the sunBit information. The straight-line propagation principle of light determines the geometrical similarity of the shadow area and the building. An edge A of the building shadow area as in FIG. 11E1Namely the corresponding wall A1 A1' determined. The relationship between the building and the ground level is assumed here to be an idealized vertical state. Constructing the shadow boundary corresponding to the building wall and the building roof as Rt delta A1′A1 E1Edge A1′A1T side A1 E1。Rt△A1′A1 E1In the formula, α is the solar altitude to be obtained, and Δ X and Δ Y represent points A1And point E1The difference between the horizontal and vertical coordinates of (a). The shadow length P can be determined according to the geometrical relationship as in FIG. 1shadowThe angle α to the sun is expressed as:
Figure GDA0002997951400000051
α＝arctan(HBldg1/Hshadow) (5)
h in the formula (5)Bldg1The building height for building Bldg1 may be obtained directly in the DBM.
The solar altitude is the angle of a spatial three-dimensional layer, and when the coordinate of one point on a ground plane is calculated by using the solar altitude, the relative position of the solar ray is required to be known, namely the relative azimuth beta of the boundary of the shadow area of the building caused by the solar ray at the shooting moment is determined. The angle can also be determined by simulating the basic geometrical relationship existing between the sunlight and buildings and photos at the moment of shooting photos by means of the DBM model.
The principle of the figure 1 is as follows: the size of the angle β and the sizes of Δ X and Δ Y can be determined by the following equations:
Figure GDA0002997951400000052
finally determining the solar azimuth angle beta as follows according to the geometrical relation of delta X and delta Y:
β＝arctan(ΔY/ΔX) (7)
the length of the shadow formed by the projection of four roof points at the same height on the same horizontal ground is the same. Thus the roof vertex C1′The length of the corresponding cast shadow is equal to A1′The lengths of the corresponding shadow areas are equal and can be regarded as Hshadow. If the shadow point is located on the roof with different heights or on the horizontal plane with different heights, the length of the shadow will change, and the formula (8) needs to be obtained again through the solar altitude angle alpha.
Hshadow(i)＝HBld(i)/tan(α) (8)
In the formula (8), i is a building number. Then F1Geographical coordinates (X) of pointsF1,YF1) The geographic coordinates according to point B1 may be expressed as:
Figure GDA0002997951400000053
in the above formula, Delta XB、△YBRepresents point F1And point B1A difference between the horizontal and vertical coordinates of (a) and (b), Delta XB＝Hshadow×Cos(β)、△YB＝HshadowX Sin (. beta.) due to the point A1、B1Is a shadow point projected at the same height on the same building, so that there is a Δ XBAnd Δ X, Δ YBIs the same as the size of delta Y, namely the delta X isBSubstitution into Δ X, Δ YBEqual effect can be achieved by replacing the triangle Y with the triangle Y. Finally, the shadow area of each building projected on the ground can be determined by calculation according to formula (8) in combination with the program language, as shown in the results of fig. 2 and 3, the numbers 1-7 are 7 adjacent buildings, the black area of fig. 2 is the geometric shadow boundary detected by the method, and fig. 3 is the detection result of the shadow area on the ground in the ghost image.
Step 4, shading shadow areas on the roof of the building: for complete detection of shadow area of building, the detection of shadow area on ground is carried out by sequentially facing the roofThe upper shaded area is detected. The principle is shown in FIG. 1, which is shown as point I in the model of FIG. 11For example.
According to point F1Finding I1When the roof of Bldg2 is used as the ground plane for projecting the apex of the Bldg1 house (in this case, the height of the roof point relative to the ground plane is the difference between the heights of two stories), the lengths of the shadows formed by the four apexes of the house at the same height on the same building on different levels of ground are different. Thus, the lengths of the shadows cast by the house vertices F are different and are denoted as Hshadow1′：
Hshadow1′＝(HBldg1-HBldg2)/tan(α) (10)
Shadow point I on roof1Can be finally expressed as:
Figure GDA0002997951400000061
in formula (11):
Figure GDA0002997951400000062
△XI1、△YI1represents point A2And point I1The difference between the horizontal and vertical coordinates of (a). And determining a roof boundary shadow point N. We are in accordance with the solution I1In order to determine the roof point C of Bldg11′The shadow point falling on the plane of the Bldg2 rooftop can determine the intersection point N, which is the shadow point on the boundary of the rooftop.
After the characteristic shadow points on the roof are determined, the determined shadow points on the roof are sequentially connected to determine a relatively complete shadow zone of the building on the roof, as shown in the result of fig. 4.
And 5, extracting the ghost roof of the building in the ghost image. The specific extraction concept can be seen in another patent number (201610521672.6) by the inventor. The shadow areas of all buildings within the experimental area were determined in the DBM by MATLAB and displayed in ghost images.
According to the above principle, the shadow area projected on the ground of the building and the shadow area projected on the roof of the adjacent obstacle building can be detected in the geographic coordinate system, and in order to completely display the detected shadow areas in the ghost image, the detection result, the ghost roof and the ghost image are displayed in a superimposed manner by boolean and operation, as shown in the result of fig. 5.

Claims (5)

1. A method for detecting building shadows based on ghost images, comprising the steps of:
step 1, converting an original image and a ghost image file into a gray image for processing, and loading a digital building model DBM file;
step 2, substituting the coordinates of the image points of the shadow points with relatively small errors into a collinear equation to obtain the geographic coordinates of the points in the DBM;
step 3, solving the inflection point of the shadow area projected on the ground by the building according to the combination of the solar altitude and the solar azimuth and connecting the inflection point with the shadow points determined on the ground in sequence, thus determining the relatively complete shadow area projected on the ground by the building at the shooting moment;
step 4, calculating the inflection points of the shadow areas of the building roof projected by the building roof according to the geometric relation of the sun altitude and the sun azimuth, sequentially connecting the inflection points of the shadow areas determined on the roof, determining the shadow areas of the building on the roof at the moment of shooting the original image,
and 5, overlapping and displaying the determined shadow area projected on the ground and the determined shadow area projected on the roof to obtain a final building shadow detection result based on ghost images.
2. The method of detecting building shadows based on ghost images according to claim 1, wherein: in step 2, the specific implementation manner of selecting the shadow points with relatively small errors is as follows:
and analyzing and seeking a building shadow inflection point with relatively small inclination error and projection error from the original aerial image so that the point has a small image point displacement difference.
3. The method for detecting a shadow of a building based on a ghost image according to claim 2, wherein: the selected shadow points with smaller image point displacement difference should be corrected as follows:
and correspondingly correcting the image distortion, the objective lens distortion, the atmospheric refraction and the earth curvature of the shadow point with the smaller image point displacement difference so as to obtain a more accurate geographical position of the shadow point.
4. The method of detecting building shadows based on ghost images according to claim 1, wherein: in step 3, the specific calculation method for the solar altitude and the solar azimuth is as follows:
determining a building corresponding to a shadow point with relatively small error in a DBM (database management system) model according to the straight line propagation principle of light, and acquiring height information of the building and geographical coordinates of a roof inflection point of the building corresponding to the shadow point with relatively small error through MATLAB;
determining the relative position of the sun rays in the DBM by utilizing the geometric relation of the spatial three-dimensional layers, namely determining the relative position of the boundary of the shadow area of the building at the shooting moment: solar altitude, solar azimuth.
5. The method of detecting building shadows based on ghost images according to claim 1, wherein: in step 5, extracting the building roof by using an 8-communication seed growth method to obtain the building roof, determining shadow areas of all buildings in the experimental area according to the DBM in the steps 3 and 4, finally displaying the result in the ghost image to obtain a shadow detection result in the ghost image, and overlapping and displaying the result with the building roof and the detected shadow on the roof.
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