JPH06230767A - Information display method - Google Patents

Abstract

PURPOSE:To efficiently perform the analysis of image data and the maintenance of a map by superimposing satellite image data on a vegetation map and a geological map that are map vector data. CONSTITUTION:This method is constituted of an image processing device 102 which performs the display control of raster data and vector data, a display device 103 on which an image or character is displayed, an input device 104 by which mage instruction and data input is performed, a raster data information data base 108 which stores the raster data and managing information and attached information for that, a vector data information data base 109 which stores the vector data and managing information and attached data for that centering about a computer 101. When the analysis of the satellite image data and the maintenance of the map are performed, it is possible to efficiently perform them by superimposing the satellite image data on the vegetation map and the geological map that are the map vector data.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a processing method of an image information processing apparatus which mainly grasps and analyzes an image, and includes a wide range of image data (raster data), vector data and attached information. And an image information processing method and device for displaying an analysis diagram according to the purpose of the analysis target.

[0002]

2. Description of the Related Art For example, in the case of displaying map vector data, which is one of vector data, on satellite image data, which is one of raster data, in order to perform alignment with the satellite image data, the scale, direction, It was necessary to convert the map vector data by affine transformation etc. in consideration of the amount of movement and to superimpose it while maintaining the positional relationship. In this method, the corresponding points of the satellite image data and the map vector data must be designated for each map. Generally, satellite image data has a size of about 60 km to 180 km. On the other hand, the map is about 10 km square (in the case of a map of 1 / 25,000 scale). Therefore, the range of one satellite image data is 36
Maps from map leaves to map leaves 320 will be included.

That is, in order to associate one satellite image with map vector data, the operation of designating corresponding points must be repeated 36 to 320 times. Further, since the corresponding points are instructed for each map map leaf, there is a possibility that a gap may occur at a joint with an adjacent map in the case of overlapping display.

As a known example close to the present invention, Japanese Patent Laid-Open No. 3-1
Although the invention described in Japanese Patent No. 96372 can be mentioned, this relates to a method of automatically selecting corresponding points for alignment, and not a method of superimposing display.

[0005]

In the above-mentioned prior art, it is necessary to calculate the superposition parameter each time depending on the enlargement ratio, the rotation angle, and the movement amount of the vector data to be superposed on the raster data. Therefore, it is necessary to calculate and store parameters for the types of vector data to be superimposed on the raster data. For example, considering superimposing map vector data on satellite image data, it is necessary to calculate and store parameters for the number of maps (maps with different scales, directions, and movement amounts are considered as separate maps). . This increases the amount of calculation and the memory capacity for storing parameters. In addition, the number of instruction operations for calculating the superposition parameter must be performed for the number of maps, which is complicated.

In order to solve the above problems, an object of the present invention is to define a convolution parameter that does not depend on the type of vector data and a vector data conversion method for convolution using the parameter, and to calculate the convolution parameter. Eliminating the pointing operation is an important issue. Furthermore, it is also an important issue to reduce the number of calculations of superimposition parameters and the memory capacity for storage.

[0007]

In order to achieve the above object, the present invention provides superimposing key information (for example, latitude and longitude in the case of satellite image data and map vector data) that does not depend on the type of raster data or vector data. The vector data is converted by using it, and is superimposed and displayed on the raster data. FIG. 2 shows, as an example, superimposed display of image data and map vector data. First of all, the raster coordinates of the image data
Raster coordinates ← → latitude / longitude conversion parameter 204 for associating (generally called line and pixel coordinates) with latitude / longitude is created (202 in FIG. 2).

On the other hand, the map vector data 205 is represented by a set of coordinates of the start point and the end point. For example, the vector data of ab shown in the map vector data 205 is represented by a set having a start point (ax, ay) and an end point (bx, by). First, the coordinates of the start point and the end point are converted into latitude and longitude by vector coordinates → latitude / longitude conversion 206. As a result, for each point a, b, c, d of the map vector data 205, data (indicated by the latitude and longitude vector data 207) a ', b', c ', d whose latitude and longitude are the coordinates of the start point and the end point, respectively. Is converted to ′. This conversion is realized by UTM coordinate → latitude / longitude conversion or the like. Next, the coordinates of the start point and the end point, which have been converted to latitude and longitude, are converted from the latitude and longitude to the raster coordinates of the satellite image data using the raster coordinates ← → latitude and longitude conversion parameter 204 obtained by the satellite image correction processing 202. As a result, each start point and end point are converted into the raster coordinates a ″, b ″, c ″, d ″ of the superimposed display image data 209. After that, by connecting the respective start points and end points, the superimposed display image data 209 of the image data and the map vector data is created. According to this method, the map vector data can be displayed in a superimposed manner without paying attention to the scale, direction, and movement amount.

[0009]

According to the present invention, in analyzing satellite image data (for example, forest vegetation and geology) and maintaining the map, satellite image data and vegetation map, which is map vector data, geological map (scale, map It is possible to efficiently analyze image data and perform map maintenance by superimposing it on any direction and movement amount). Moreover, the resolution of satellite image data is generally about 10 to 80 m, and roads and railways are blurred. By superimposing map vector data on this data, roads and railways can be emphasized and visibility improved. can do.

[0010]

EXAMPLE An example of the present invention will be described below. FIG. 1 shows an example of the configuration of a system for carrying out the present invention.
01 as the center, an image processing device 102 for controlling display of raster data and vector data, a display device 103 for displaying an image or a character, an input device for instructing a screen and inputting data, raster data and its Raster data information database 108 for storing management information and attached information
And a vector data information database 109 for storing vector data, its management information, and auxiliary information. The computer 101 has a search means 105 for searching raster data based on the information from the input device 104, and a search means 7 for searching the raster data searched by the search means 105 for necessary vector data. It further has a conversion unit 106 for converting the vector data searched by the search unit 107 into a coordinate system of raster data.

An example of superimposed display of satellite image data, which is one of raster data, and map data, which is one of vector data, will be shown below. Here, latitude and longitude are selected as an example of key information for mediating raster data and vector data.

First, a method of obtaining a coefficient for determining conversion between raster image coordinates and latitude / longitude coordinates will be described. The formula for determining this coefficient may be any formula, but here, a polynomial is used as an example.

A polynomial for raster coordinate ← → latitude / longitude conversion is set as follows (see FIG. 3).

[0014]

[Equation 1] Latitude = a ₀ + a ₁ · line + a ₂ · pixel (Equation 1)

[0015]

[Equation 2] Latitude = b ₀ + b ₁ · line + b ₂ · pixel (Equation 2)

[0016]

[Equation 3] Line = c ₀ + c ₁ · Latitude + c ₂ · Age ... (Equation 3)

[0017]

Equation 4] Pixel = d ₀ + d ₁ · latitude + d ₂ · through index (Equation 4) _{where, a 0, a 1, a} 2, b 0, b 1, b 2, c 0, c 1, c
₂ , d ₀ , d ₁ and d ₂ are polynomial coefficients. (Equation 1) is a calculation formula for calculating latitude from lines and pixels, (Formula 2) is a calculation formula for calculating longitude from lines and pixels, and (Formula 3) is a calculation formula for calculating lines from latitude and longitude. , (Equation 4) is a calculation formula for obtaining pixels from latitude and longitude. FIG. 4 shows a flow for obtaining the coefficient of the polynomial.

When a first-order polynomial is used, three or more points on the image are selected to determine the above polynomial coefficient,
The latitude / longitude and the line pixel at that point are examined, and the result is (latitude, longitude) = (λ _i , ψ _i ) (line, pixel) = (l _i , p _i ) i = 1 to N (N is Number of selected points). (See 401 in FIG. 4 and 501 in FIG. 5) The polynomial coefficients of (Equation 1) to (Equation 4) use the least squares method,

[0019]

[Equation 5]

[0020]

[Equation 6]

[0021]

[Equation 7]

[0022]

[Equation 8]

In ε ₁ , ε ₂ , ε ₃ , ε ₄ are set to be minimum (402 in FIG. 4, number 1, number 2, number 3, number 4 in FIG. 5). By storing the coefficient defined here in the database together with the individual image information, it is possible to mutually specify arbitrary position information and arbitrary pixels on the image (see 403 in FIG. 4 and 605 in FIG. 6).

FIG. 6 shows the structure of the satellite image data management table and the image data file. Satellite image data is generally managed for each image capturing unit called a scene. One scene is the coordinates of the shooting position on the earth called Pasuloux, the shooting date, the satellite name (or
It is specified by (sensor name) (602 in FIG. 6). Further, information (size, number of bands) of the image data itself is stored as the number of bands, the number of lines, and the number of pixels (60 in FIG. 6).
3). In addition, the position information of this scene (latitude and longitude of the four corners of the image, 604 in FIG. 6), the raster image coordinates obtained above, and the polynomial conversion coefficients (a ₀ , a ₁ , a ₂ , b of the latitude and longitude coordinates).
₀ , b ₁ , b ₂ , c ₀ , c ₁ , c ₂ , d ₀ , d ₁ , d ₂ ) are stored (605 in FIG. 6).

Next, the procedure for superimposing the satellite image data, which is raster image data, and the map data, which is vector image data, will be described with reference to FIG.

First, the satellite image data to be superimposed and displayed is selected (passlow, shooting date, satellite name (or sensor name) are designated. 701 in FIG. 7). The selected satellite image data is displayed on the display device (103 in FIG. 1) (see FIG. 7).
702).

At this time, the selected latitude / longitude of the satellite image data, the raster image coordinates, and the polynomial conversion coefficients (a ₀ , a ₁ , a ₂ , b ₀ , b ₁ , b ₂ , c of the latitude / longitude coordinates). ₀ , c ₁ ,
(c ₂ , d ₀ , d ₁ , d ₂ ) are extracted from the satellite image management data table (FIG. 6) (703, 70 in FIG. 7).
4). Next, using the latitude and longitude of the four corners of the satellite image data extracted in 703, the map data necessary for superimposition display is searched. Multiple pieces of map data are searched (70 in FIG. 7).
8).

The following processing is repeated for the number of retrieved map leaves for the map (709 in FIG. 7). Coordinates in the map data leaf segment data table, coordinates in the symbol data table,
Convert the coordinates in the character data table from UTM coordinates to latitude / longitude coordinates (701 in FIG. 7) Next, a raster image in which the coordinates (line segment data, symbol data, character data) converted to latitude / longitude are extracted at 704. Coordinates and latitude / longitude coordinate conversion coefficients (a ₀ , a ₁ , a ₂ , b ₀ , b ₁ , b ₂ , c ₀ , c ₁ , c ₂ ,
Using d ₀ , d ₁ , d ₂ ), the latitude / longitude coordinates (line segment data, symbol data, character data) converted in 710 are converted into raster coordinates (711 in FIG. 7). Next, the points converted into the raster coordinates are connected by a straight line, and are superimposed and displayed on the display device.

Hereinafter, a detailed procedure for retrieving map data necessary for superimposition display (708 in FIG. 7) and a procedure for converting latitude / longitude coordinates (line segment data, symbol data, character data) into raster coordinates (FIG. About 711 of 7).

FIG. 8 shows the table structure of the map database for the procedure (708 in FIG. 7) for retrieving the map data necessary for the superimposed display. The map data is managed for each scale (801 in FIG. 8), and one map leaf of the map is the range (map leaf range, 803 in FIG. 8) that the map represents and the map data storage destination pointer (map). 8 804). On the other hand, the map data is a line segment data table (80 in FIG. 8).
6), a symbol data table (807 in FIG. 8), and a character data table (808 in FIG. 8). Here, the map leaf area of the map is defined by the latitude and longitude of the four corners of the map, as indicated by 904 in FIG. Satellite image data 1
In order to search the map leaf included in the scene, the latitude and longitude of the four corners of the satellite image data and the map leaf range (latitude and longitude) extracted in 703 of FIG. 7 are used. FIG. 11 shows the method. Satellite image data (Fig. 11
Points 1101) at the four corners A (λ ₁ , ψ ₁ ), B respectively
(Λ ₂ , ψ ₂ ), C (λ ₃ , ψ ₃ ), D (λ ₄ , ψ ₄ ) (λ _i
Is latitude and ψ _i is longitude) At these points A, B, C, D, it is sufficient to retrieve the map leaves within the enclosed range.

However, in general, the satellite image does not match the coordinate system of the map. Therefore, the search is performed within the range indicated by the broken line 1103 in FIG. That is, the point A '(λ ₂ ,
ψ ₁ ), B '(λ ₂ , ψ ₄ ), C' (λ ₃ , ψ ₁ ), D '
Search for a map that includes at least one of the four corner points of the map leaf area within the area surrounded by (λ ₃ , ψ ₄ ). In other words, the latitude and longitude of the four corners in the map leaf area are a (λ ₁ ′,
ψ ₁ ′), b (λ ₂ ′, ψ ₂ ′), c (λ ₃ ′, ψ ₃ ′),
d (λ ₄ ′, ψ ₄ ′), in FIG. 11, λ ₃ ≦ λ ₁ ′ ≦ λ ₂ and ψ ₁ ≦ ψ ₁ ′ ≦ ψ ₄ or λ ₃ ≦ λ ₂ ′ ≦ λ ₂ and ψ ₁ ≦ ψ ₂ ′ ≦ ψ ₄ or λ ₃ ≦ λ ₃ ′ ≦ λ ₂ and ψ ₁ ≦ ψ ₃ ′ ≦ ψ ₄ or λ ₃ ≦ λ ₄ ′ ≦ λ ₂ and ψ ₁ ≦ ψ ₄ ′ ≦ ψ ₄ You can search for the map map leaves that meet.

Procedure for converting the longitude / latitude coordinates (line segment data, symbol data, character data) of the map into raster coordinates (711 in FIG. 7) In the table structure of the map database, the line segment data is the number of constituent points ( 1011) and the coordinates of each point P ₁ , P _{2 to} P _n
(UTM coordinates 1001, 1002, 1003, 1004, 1
005, 1006). The symbol data is also composed of its number (1012) and its reference coordinates (UTM coordinates 1007, 1008). Similarly, the number of character data (1013) and its reference coordinates (UTM coordinates 1
009, 1010). The conversion procedure to raster coordinates is shown below using line segment data as an example (FIG. 12).

First, the line segment S ₁ (starting point P on the UTM
Consider ₁ (X ₁ , Y ₁ ) and end point P ₂ (X ₂ , Y ₂ )). The UTM coordinates of the start point P ₁ and the end point P ₂ are acquired (1 in FIG. 12).
202, where ni is the UTM zone number. ). This U
The TM coordinates are converted to the latitude / longitude value P by converting the coordinates of P ₁ and P ₂ by the UTM → latitude / longitude coordinate conversion processing (1203 in FIG. 12).
₁ (λ ₁ , ψ ₁ ), P ₂ (λ ₂ , ψ ₂ ) (1204 in FIG. 12, where λ _i is latitude and ψ _i is longitude). Next, the raster image coordinates extracted at 704 in FIG. 7 and the conversion coefficients (a ₀ , a ₁ , a ₂ , b ₀ , b ₁ , b ₂ , c ₀ , c) of the latitude / longitude coordinates.
₁ , c ₂ , d ₀ , d ₁ , d ₂ ) (1206 in FIG. 12) is used to convert to raster coordinates (1205 in FIG. 12). The raster coordinates after conversion are P ₁ ′ (l ₁ , p ₁ ), P ₂ ′ (l ₂ ,
p ₂ ) (where l ₁ and l ₂ are line coordinates and p ₁ and p ₂ are pixel coordinates), as indicated by 1205 in FIG.

[0034]

[Equation 9] l ₁ = c ₀ + c ₁ · λ ₁ + c ₂ · ψ ₁ (Equation 9)

[0035]

[Equation 10] p ₁ = d ₀ + d ₁ · λ ₁ + d ₂ · ψ ₁ (Equation 10)

[0036]

[Equation 11] l ₂ = c ₀ + c ₁ · λ ₂ + c ₂ · ψ ₂ (Equation 11)

[0037]

[Equation 12] p ₂ = d ₀ + d ₁ · λ ₂ + d ₂ · ψ ₂ (Equation 12) If these points are connected by a straight line on the raster image, it is possible to display in a superimposed manner (1207 in FIG. 12).

According to the present embodiment, map data (line segment data: roads, railways, coastlines, administrative divisions, etc.), which is vector data, and satellite image data can be superimposed and displayed. As a result, roads and railways that are unclear with satellite image data alone can be emphasized, which has the effect of improving visibility. In addition, administrative divisions, which are not included in the satellite image data, can be displayed in a superimposed manner, and the boundaries between prefectures and municipalities can be made clear. Also, the latest satellite image can be used as a guide for map data correction (for example, when the coastline changes due to landfill).

As a second embodiment, surface data of the map data (for example, land use map, vegetation distribution map, geological map, etc.)
Let's consider that is displayed on the satellite image data. In general, as shown in FIG. 13, for surface data, one surface data is defined as a set of line segment data (1303 in FIG. 13) constituting the data. That is, the surface f ₁ is composed of the line segments l ₁₁ , l _{12 to} l _1j . Next, the line segment data forming the surface f ₁ is defined as a set of point data (1304 in FIG. 13). That is, the line data l ₁₁ is composed of p ₁₁₁ and p _{112 to} p _11k . Finally, the surface data is also a set of point data (Fig. 13).
1305, 1306).

Consider that the planes f ₁ and f ₂ of FIG. 14 are superimposed and displayed on the satellite image. The surface f ₁ has points p ₁₁₁ , p ₁₁₂ , and p
_{It is} composed of ₁₂₁ , p ₁₂₂ and p ₁₂₃ . The surface f ₂ has a point p ₂₁₁ ,
It is composed of p ₂₁₂ and p ₂₂₂ . The UTM coordinates of each point are acquired (1402 in FIG. 14), and then the UTM coordinates →
It is converted into latitude and longitude coordinates (1403 in FIG. 14). (Here, X _ijk and Y _ijk are UTM coordinates of the point P _ijk , and n _ijk is UTM.
Zone No. Indicates. λ _ijk and ψ _ijk are points P
Indicates the latitude and longitude of _ijk . ) Next, the polynomial transformation coefficients (c ₀ , c ₁ , c ₂ , d ₀ , of the raster image coordinates and the latitude / longitude coordinates)
d ₁ , d ₂ ) (1406 in FIG. 14) is used to convert to raster coordinates. Convert the raster coordinates after conversion to P _ijk (l _ijk , p
_ijk ) (where l _ijk is a line coordinate and p _ijk is a pixel coordinate)

[0041]

L _ijk = c ₀ + c ₁ · λ _ijk + c ₂ · ψ _ijk ( _Equation 13)

[0042]

[ _Expression 14] p _ijk = d ₀ + d ₁ · λ _ijk + d ₂ · ψ _ijk ( _Equation 14) These points are connected by a straight line on the raster image. Further, since the data is surface data, the surface data can be superimposed and displayed on the raster image by changing the luminance value of the portion surrounded by the straight line on the raster image.

According to this embodiment, map data (plane data: land use map, vegetation distribution map, geological map, etc.), which is vector data, and satellite image data can be superimposed and displayed. This makes it possible to clarify land use, vegetation distribution, geology, etc. that are not on the satellite image. It is also possible to analyze (classify) the latest satellite image and use it as a guide for correcting the vegetation distribution map, which is vector data, based on the obtained vegetation distribution.

As a third embodiment, let us consider superimposition display of weather map data on geostationary satellite image data. Geostationary satellites constantly observe a certain area on the earth and take image data of them. For this reason, the shooting range is always the same, and as shown by 1505 in FIG. 15, one set of conversion coefficients for raster image coordinates and latitude / longitude coordinates may be stored in the geostationary satellite image data management table. You don't have to have each. Each scene has a shooting date and time and its image data storage destination pointer (1507 in FIG. 15). On the other hand, the structure of the weather map data which is vector data is shown in FIG. The weather map data management file includes the total number of observations (1601 in FIG. 16), the observation date and time, and the weather map data storage destination pointer (1603 in FIG. 16). The weather map data file includes an isobar data table (1605 in FIG. 16) and a front data table (16 in FIG. 16) for each observation date and time.
06), high pressure, low pressure data table (16 in FIG. 16)
07) and a symbol data table (1608 in FIG. 16). The details of each configuration are shown in FIG. In any of the data tables, the coordinate data representing the position is the latitude / longitude coordinate (1701, 1702, 170 in FIG. 17).
3).

Consider that the isobars are displayed in a superimposed manner. Coordinates of points forming a certain isobar (1701 in FIG. 17)
(1802 in FIG. 18, where λ _i is the point P _i
, Ψ _i is the longitude of the point P _i ). These coordinates are converted from latitude / longitude coordinates to raster image coordinates (c ₀ , c ₁ , c ₂ ,
d ₀ , d ₁ , d ₂ ) (1804 in FIG. 18) is used to convert to raster coordinates. The raster coordinates after conversion are P _i ′
(l _i , p _i )

[0046]

L _i = c ₀ + c ₁ · λ _i + c ₂ · ψ _i (Equation 15)

[0047]

## EQU16 ## p _i = d ₀ + d ₁ λ _i + d ₂ ψ _i (Equation 16) (1803 in FIG. 18).

If the obtained points are connected by a straight line on the raster coordinates and displayed on the display device, the isobars can be superimposed (1805 in FIG. 18).

According to this embodiment, it is possible to superimpose and display the weather map data, which is vector data, and the satellite image data (for example, weather satellite). This allows
It is possible to make weather forecasts by comparing the appearance of clouds with the contour lines and pressure distribution.

As a fourth embodiment, let us consider superimposition display of image map data and water pipe diagram data. The image map data management table is, as shown in FIG. 19, a map name (1902 in FIG. 19), image size (band count, line count, pixel count, 1903 in FIG. 19), U at the four corners of the map.
It is composed of TM coordinates (1904 in FIG. 19), UTM coordinates, a conversion coefficient of raster coordinates (1905 in FIG. 19), and a storage destination pointer (1906 in FIG. 19) for image map data. In this embodiment, UTM coordinates are used as key information for raster data (image map data) and vector data (water pipe data). In this case, the conversion coefficient can be obtained as follows according to the first embodiment.

First, the method of obtaining the coefficients for determining the conversion between the raster image coordinates and the UTM coordinates will be described. The formula for determining this coefficient may be any formula, but here, a polynomial is used as an example.

A polynomial for raster coordinate ← → UTM coordinate conversion is set as follows.

[0053]

[Formula 17] UTM coordinate (X) = e ₀ + e ₁ · line + e ₂ · pixel (Formula 17)

[0054]

[Equation 18] UTM coordinate (Y) = f ₀ + f ₁ · line + f ₂ · pixel (Equation 18)

[0055]

[Formula 19] Line = g ₀ + g ₁ · UTM coordinate (X) + g ₂ · UTM coordinate (Y) (Formula 19)

[0056]

Pixel = h ₀ + h ₁ · UTM coordinate (X) + h ₂ · UTM coordinate (Y) (Equation 20) where e ₀ , e ₁ , e ₂ , f ₀ , f ₁ , f ₂ , g ₀ , g ₁ , g
₂ , h ₀ , h ₁ and h ₂ are polynomial coefficients. (Equation 1) is
Equation (2) is a formula for obtaining UTM coordinates (X) from lines and pixels, and Equation (2) is a formula for obtaining UTM coordinates (Y) from lines and pixels, and Equation (3) is UTM coordinates (X) and UTM coordinates. (Equation 4) is a calculation formula for obtaining a line from (Y), and UTM coordinates (X) and UTM coordinates (Y)
Is a calculation formula for obtaining a pixel from.

When a first-order polynomial is used, three or more points on the image are selected to determine the above polynomial coefficient,
The UTM coordinate and the line pixel at that point are examined, and in the case of this embodiment (the UTM coordinate of the four corners and the line pixel coordinate), the result is (UTM coordinate (X), UTM coordinate (Y)) = (X _i ，
Y _i ) (line, pixel) = (l _i , p _i ) i = 1 to N (N is the number of selected points).

For the polynomial coefficients of (Equation 17) to (Equation 20), the least squares method is used.

[0059]

[Equation 21]

[0060]

[Equation 22]

[0061]

[Equation 23]

[0062]

[Equation 24]

In ε, ε ₁ , ε ₂ , ε ₃ and ε ₄ are set to be minimum. By storing the coefficient determined here in the database together with the individual image information, it is possible to mutually specify arbitrary position information and arbitrary pixels on the image (see 1905 in FIG. 19).

On the other hand, FIG. 20 shows the structure of water pipe diagram data which is vector data. The water pipe diagram data management table has a reduced scale (2001 in FIG. 20) and the number of leaves (20 in FIG. 20).
02) It consists of a map leaf range (2003 of FIG. 20) and a water pipe diagram data storage destination pointer (2004 of FIG. 20). Further, as shown in FIG. 21, the drawing leaf range of the water pipe diagram is managed by UTM coordinates at the four corners of the drawing leaf. The water pipe diagram data file is scaled, the water pipe data table (2006 of FIG. 20) and the symbol data table (20 of FIG. 20) for each drawing leaf.
07) and a character data table (2008 in FIG. 20). The details of each table structure are shown in FIG. In any of the data tables, the coordinate data representing the position is the UTM coordinate (2214, 2207 in FIG. 22,
2208, 2209, 2210).

Next, FIG. 23 shows a procedure for displaying the water pipe data on the image map data in a superimposed manner. Coordinates of points forming a certain water pipe (2214 in FIG. 22, 2 in FIG. 23)
Take out 301). (2303 in FIG. 23, wherein X _i UTM coordinates of the point P _i (X) Y _i is UTM coordinates of the point P _i (Y)
n _i is, UTM zone No.). Converting these coordinates from UTM coordinates to raster image coordinates (g ₀ , g ₁ , g ₂ ,
h ₀ , h ₁ , h ₂ ) (2304 in FIG. 23) is used to convert to raster coordinates. Convert the raster coordinates after conversion to P _i ′ (l _i ,
p _i )

[0066]

L _i = g ₀ + g ₁ · X _i + g ₂ · Y _i (Equation 25)

[0067]

[Equation 26] p _i = h ₀ + h ₁ · X _i + h ₂ · Y _i (Equation 26) (2305 in FIG. 23), if the obtained points are connected by a straight line on the raster coordinates and displayed on the display device, the water pipe can be displayed superimposed on the image map data (2306 in FIG. 23). According to this embodiment, the image map data can be used as a guide for modifying the water pipe data (in the example of FIG. 23, the water pipe is laid in the newly built house (2307, 2308 in FIG. 23). If you do).

As a fifth embodiment, let us consider a superimposed display of aerial photographs (raster data) and power transmission line data (vector data).

A management table of aerial photograph data is shown in FIG. This configuration conforms to the satellite image data management table (FIG. 6). (The aerial photograph data is digitized by an image scanner in advance and stored in the database.) However, the district code for uniquely determining the aerial photograph, shooting course, aerial photograph No.
(2402 in FIG. 24) is different from the case of satellite image data.

In this embodiment, latitude and longitude are used as key information of raster data (aerial photograph data) and vector data (power line data). Therefore, the conversion coefficient can be obtained as in the first embodiment. Here, as a point on the image used for obtaining the conversion coefficient, a triangular point may be selected.

On the other hand, FIG. 25 shows the structure of transmission line diagram data, which is vector data. The power transmission line diagram data management table conforms to the water pipe diagram data management table (FIG. 20). Further, the structure of the power transmission line data file also conforms to the structure of the water pipe diagram data (FIG. 20) as indicated by 2505, 2506, 2508 in FIG. The details of each configuration are shown in FIG. In any of the data tables, the coordinate data representing the position is the UTM coordinate (27 in FIG. 27).
14, 2707, 2709, 2710).

Next, FIG. 28 shows a procedure for superimposing the power transmission line data on the aerial photograph data. Coordinates of points forming a certain power transmission line (2714 in FIG. 27, 280 in FIG. 28)
1) is taken out (2803 in FIG. 28, where X _i is point P).
_{i is} the UTM coordinate (X), Y _i is the UTM coordinate of the point P _i , n _i
Is UTM zone No.).

Next, the UTM coordinates are converted into latitude / longitude values P _i (λ _i , ψ _i ) by UTM → latitude / longitude conversion processing (2805 in FIG. 28) (280 in FIG. 28).
6, where λ _i is latitude and ψ _i is longitude). Next, conversion coefficients (c ₀ , c ₁ , c ₂ , d ₀ ,
d ₁ , d ₂ , 2808 in FIG. 28) are used to convert to raster coordinates. Let the raster coordinates after conversion be P _i ′ (l _i , p _i ).

[0074]

L _i = c ₀ + c ₁ · λ _i + c ₂ · ψ _i (Equation 27)

[0075]

(Equation 28) p _i = d ₀ + d ₁ · λ _i + d ₂ · ψ _i (Equation 28) If these points are combined with a straight line on the raster image and displayed on the display device, the power transmission line data can be displayed superimposed on the aerial photograph data (2809 in FIG. 28).

According to this embodiment, the aerial photograph data can be used as a guide for correcting the power transmission line data (in the example of FIG. 28, a newly installed power transmission line (281 of FIG. 28) is used.
0) When adding to transmission line data (vector)).

As a sixth embodiment, let us consider the superimposed display of aerial photographs (raster data) and map data (vector data).

The table of aerial photograph data has the structure shown in FIG. 24, as shown in the fifth embodiment. On the other hand, the map data (vector data) has the configurations shown in FIGS. 8, 9 and 10 as shown in the first embodiment. In this embodiment, latitude and longitude are used as key information of raster data (aerial photograph data) and vector data (map data).

Next, FIG. 29 shows a procedure for superimposing map data on aerial photograph data using these data. The procedure for superimposing display is the same as the procedure for superimposing map data shown in the first embodiment. That is, the coordinates of the points forming one line segment (the line segment forming the road in this embodiment) in certain map data (1014 in FIG. 10 and 2901 in FIG. 29).
(2903 in FIG. 29, where X _i is U at point P _i )
TM coordinates (X), Y _i is UTM coordinates of the point P _i (Y), n _i
Is UTM zone No.).

Next, converts the coordinates of P _i by the UTM coordinates UTM → latitude and longitude conversion process (2805 in FIG. 28) latitude and longitude values P _i (lambda _i, [psi _i) to (2806 in FIG. 29,
Where λ _i is latitude and ψ _i is longitude). Next, conversion coefficients (c ₀ , c ₁ , c ₂ , d ₀ , d ₁ ,
d _2, converted to a raster coordinates using a 2908) in FIG. 29. Let the raster coordinates after conversion be P _i ′ (l _i , p _i ).

[0081]

[Formula 29] l _i = c ₀ + c ₁ · λ _i + c ₂ · ψ _i (Formula 29)

[0082]

[Equation 30] p _i = d ₀ + d ₁ · λ _i + d ₂ · ψ _i (Equation 30) If these points are connected with a straight line on the raster image and displayed on the display device, the map data will be aerial photograph data,
Superimposition display is possible (2909 in FIG. 29).

According to this embodiment, the aerial photograph data can be used as a guide for correcting the map data (in the example of FIG. 29, a newly constructed road and bridge (291 of FIG. 29) is used.
0) is reflected in map data (vector)).

As a seventh embodiment, let us consider the superimposed display of image map data (raster data) and map data (vector data). The image map data table has the structure shown in FIG. 19 as shown in the fourth embodiment.
On the other hand, the map data (vector data) table also has the configurations shown in FIGS. 8, 9 and 10 as shown in the first embodiment. In this embodiment, UTM coordinates are used as key information for raster data (image map data) and vector data (map data).

Next, FIG. 30 shows a procedure for superposing and displaying the map data on the image map data using these data. The procedure of superimposing display is the same as the procedure of superimposing displaying water pipe diagram data shown in the fourth embodiment. That is, the coordinates of the points forming a certain line segment (1014 in FIG. 10).
Take out. (3003 in FIG. 30, where X _i is the UTM coordinate (X) of the point P _i , n _i is the UTM zone No.) This coordinate is converted from the UTM coordinate to the raster image coordinate (g ₀ ,
g ₁ , g ₂ , h ₀ , h ₁ , h ₂ , 3006 in FIG. 30) is used to convert to raster coordinates. Let the raster coordinates after conversion be P _i ′ (l _i , p _i ).

[0086]

L _i = g ₀ + g ₁ · X _i + g ₂ · Y _i (Equation 31)

[0087]

P _i = h ₀ + h ₁ · X _i + h ₂ · Y _i (Equation 32) (3005 in FIG. 30). If these points are connected by a straight line on the raster image and displayed on the display device, the map data (vector data) can be displayed superimposed on the image map data (3007 in FIG. 30).

According to the present embodiment, the image map data can be used as a guide for modifying the map data (vector) (in the example of FIG. 30, a newly installed railway (see FIG. 3) is used.
(0) 3008) is reflected in map data (vector)).

As an eighth embodiment, let us consider a superimposed display of geostationary satellite image data (raster data) and sea surface temperature distribution data (vector data). The table of geostationary satellite image data has the configuration shown in FIG. 15 as shown in the third embodiment. On the other hand, the table of sea surface temperature distribution data is shown in Fig. 3.
It has the configuration shown in FIG. The sea surface temperature distribution data management table includes the total number of observations (3101 in FIG. 31), observation date and time,
Pointer for storing sea surface temperature distribution data (310 in FIG. 31)
2). Further, the sea surface temperature distribution data file includes an isotherm data table (3105 in FIG. 31), a tide data table (3106 in FIG. 31), a warm water mass, a cold water mass data table (3107 in FIG. 31), and a symbol data table (Fig. 31 3108). Details of each data table are shown in FIG. In any of the data tables, the coordinate data representing the position is latitude and longitude (3201, 3202, 3203 in FIG. 32).

In this embodiment, latitude and longitude are used as the key information of raster data (geostation satellite image data) and vector data (sea surface temperature distribution data).

Next, FIG. 33 shows a procedure for superimposing and displaying the sea surface temperature data on the geostationary satellite image data. The procedure for superimposing display is the same as the procedure for superimposing displaying weather map data shown in the third embodiment. That is, first, the coordinates (3201 in FIG. 32) of a point forming a certain isotherm are extracted (33 in FIG. 33).
01, 3302). The conversion coefficient (c ₀ , c ₁ , c ₂ , d ₀ , d ₁ ,
d _2, using 3304) of FIG. 33, converts the raster coordinates. Let the raster coordinates after conversion be P _i ′ (l _i , p _i ).

[0092]

[Expression 33] l _i = c ₀ + c ₁ · λ _i + c ₂ · ψ _i (Expression 33)

[0093]

[Equation 34] p _i = d ₀ + d ₁ · λ _i + d ₂ · ψ _i (Equation 34) (3303 in FIG. 33) If these points are connected by a straight line on the raster coordinates and displayed on the display device, the isotherm data of the sea surface temperature can be displayed superimposed on the geostationary satellite image data (3305 in FIG. 33).

According to the present embodiment, by displaying the geostationary satellite image data and the sea surface temperature distribution data in an overlapping manner, it is possible to estimate the fishing ground of various fish.

As a ninth embodiment, let us consider a superimposed display of satellite image data (raster data) and airway map data (vector data). The satellite image data table is
As shown in the first embodiment, it has the configuration shown in FIG. On the other hand, the table of the air route map data has the structure shown in FIG. The airway map data management table is at a reduced scale (Fig. 3
4 3401), the number of map leaves (3402 in FIG. 34), the map range (3403 in FIG. 34), and the airway map data storage destination pointer (3403 in FIG. 34). Also, the air route data file is the air route data table (34 in FIG. 34).
05) and a symbol data table (3406 in FIG. 34). As shown in FIG. 35, the map leaf range of the air route map is managed by the latitude and longitude of the four corners of the map leaf. Further, details of the air route data table symbol data table are shown in FIG. In each data table, the coordinate data representing the position is latitude and longitude (3508, 3506, 350 in FIG. 32).
7). In this embodiment, raster data (satellite image data)
The latitude and longitude are used as key information for vector data (airway map data).

Next, FIG. 37 shows a procedure for superimposing and displaying the air route map data on the satellite image data. The procedure for superimposing display is the same as the procedure for superimposing displaying weather map data shown in the third embodiment. That is, first, the coordinates (3608 in FIG. 36) of the points forming one air route are taken out (3 in FIG. 37).
701, 3703). The conversion coefficient (c ₀ , c ₁ , c ₂ , d ₀ , d ₁ ,
d _2, converted to a raster coordinates using a 3705) in FIG. 37. Let the raster coordinates after conversion be P _i ′ (l _i , p _i ).

[0097]

L _i = c ₀ + c ₁ · λ _i + c ₂ · ψ _i (Equation 33)

[0098]

[Equation 36] p _i = d ₀ + d ₁ · λ _i + d ₂ · ψ _i (Equation 34) (3704 in FIG. 37). If these points are connected by a straight line on the raster coordinates and displayed on the display device, the air route data can be displayed superimposed on the satellite image data (37 in FIG. 37).
06).

According to this embodiment, it is possible to know the cloud condition of the air route corresponding to the route by superimposing the satellite image data and the air route data.

[0100]

As described above, according to the present invention, the operation of designating corresponding points for superimposing is unnecessary, and the operator's load is lightened. In analysis of satellite image data (for example, forest vegetation, geology) and map maintenance, satellite image data and map vector data such as vegetation map and geological map (scale, map orientation, movement amount do not matter) By superimposing, it is possible to efficiently analyze image data and perform map maintenance.Generally, the resolution of satellite image data is about 10 to 80 m, and roads and railways are blurred. By superimposing map vector data on this data, roads and railways can be emphasized, and visibility is improved.

[Brief description of drawings]

FIG. 1 is a system configuration diagram showing an embodiment of the present invention.

FIG. 2 is a diagram showing a procedure of superimposing display of image data and vector data according to the present invention.

FIG. 3 is a diagram showing conversion between raster coordinates and latitude / longitude coordinates according to the present invention.

FIG. 4 is a flowchart for obtaining a conversion coefficient between raster coordinates and latitude / longitude coordinates according to the present invention.

FIG. 5 is a diagram showing how to obtain a conversion coefficient between raster coordinates and latitude / longitude coordinates according to the present invention.

FIG. 6 is a table configuration diagram of satellite image data, which is an example of a raster image information database according to the present invention.

FIG. 7 is a flowchart showing a procedure for superimposing display of satellite image data and map vector data according to the present invention.

FIG. 8 is a table configuration diagram of map data which is an example of a vector image information database according to the present invention.

FIG. 9 is a detailed table configuration diagram of map data, which is an example of a vector image information database according to the present invention.

FIG. 10 is a detailed table configuration diagram of map data, which is an example of a vector image information database according to the present invention.

FIG. 11 is a diagram showing a map vector data search method according to the present invention.

FIG. 12 is a diagram showing details of a procedure of superimposing display of image data and vector data (line segment data) according to the present invention.

FIG. 13 is a table configuration diagram of surface data in the map data which is an example of the vector image information database according to the present invention.

FIG. 14 is a diagram showing details of the procedure for superimposing display of image data and vector data (plane data) according to the present invention.

FIG. 15 is a table configuration diagram of geostationary satellite image data, which is an example of a raster image information database according to the present invention.

FIG. 16 is a table configuration diagram of weather map data, which is an example of a vector image information database according to the present invention.

FIG. 17 is a detailed table configuration diagram of weather map data, which is an example of a vector image information database according to the present invention.

FIG. 18 is a diagram showing details of a procedure of superimposing display of image data and vector data (isobaric line data) according to the present invention.

FIG. 19 is a table configuration diagram of image map data which is an example of a raster image information database according to the present invention.

FIG. 20 is a table configuration diagram of water pipe diagram data, which is an example of a vector image information database according to the present invention.

FIG. 21 is a detailed table configuration diagram of water pipe diagram data, which is an example of a vector image information database according to the present invention.

FIG. 22 is a detailed table configuration diagram of water pipe diagram data, which is an example of a vector image information database according to the present invention.

FIG. 23 is a diagram showing details of a procedure for superimposing display of raster data (image map data) and vector data (water supply conduit diagram data) according to the present invention.

FIG. 24 is a table configuration diagram of aerial photograph data, which is an example of a raster image information database according to the present invention.

FIG. 25 is a table configuration diagram of power transmission line diagram data, which is an example of a vector image information database according to the present invention.

FIG. 26 is a detailed table configuration diagram of power transmission line diagram data, which is an example of a vector image information database according to the present invention.

FIG. 27 is a detailed table configuration diagram of power transmission line diagram data, which is an example of a vector image information database according to the present invention.

[Fig. 28] Fig. 28 is a diagram illustrating details of a procedure of superimposing display of raster data (aerial photograph data) and vector data (power transmission line chart data) according to the present invention.

FIG. 29 is a diagram showing details of the procedure for superimposing display of raster data (aerial photograph data) and vector data (map vector data) according to the present invention.

[Fig. 30] Fig. 30 is a diagram showing details of the procedure for superimposing display of raster data (image map data) and vector data (map vector data) according to the present invention.

FIG. 31 is a table configuration diagram of sea surface temperature distribution data, which is an example of a vector image information database according to the present invention.

FIG. 32 is a detailed table configuration diagram of sea surface temperature distribution data, which is an example of a vector image information database according to the present invention.

[Fig. 33] Fig. 33 is a diagram showing the details of the procedure for superimposing display of raster data (stationary satellite image data) and vector data (sea surface temperature distribution data) according to the present invention.

FIG. 34 is a table configuration diagram of airway map data which is an example of a vector image information database according to the present invention.

FIG. 35 is a detailed table configuration diagram of airway map data, which is an example of a vector image information database according to the present invention.

FIG. 36 is a detailed table configuration diagram of airway map data, which is an example of a vector image information database according to the present invention.

FIG. 37 is a diagram showing details of the procedure for superimposing display of raster data (satellite image data) and vector data (airway map data) according to the present invention.

[Explanation of symbols]

101 ... Calculator, 102 ... Image processing device, 103 ... Display device, 104 ... Input device, 105 ... Raster data search means, 106 ... Vector coordinate → raster coordinate conversion means, 10
7 ... Vector data search means, 108 ... Raster data information database, 109 ... Vector data information database.

 ─────────────────────────────────────────────────── ─── Continuation of the front page (72) Inventor Keizo Sato 5-2-1 Omika-cho, Hitachi-shi, Ibaraki Hitachi Information Control System Co., Ltd.

Claims (6)

[Claims] 1. An information processing display device comprising information consisting of raster data and information consisting of vector data, wherein an enlargement ratio of each of the raster data and the vector data,
An information display method characterized in that key information of raster data and vector data is used as an intermediary, regardless of the rotation angle, and the positional relationship between the two is maintained and superimposed display is performed. 2. The display method according to claim 1, wherein when the raster data is image data and the vector data is map data, the image data, the scale of the map data, and the image data
A method for displaying image information, characterized in that key information of map data is used as an intermediary to maintain a positional relationship between the two and superimpose them. 3. The display method according to claim 1, wherein the key information of the raster data and the vector data is used as an intermediary, regardless of the amount of movement of the raster data and the vector data, the positional relationship between the two is maintained, and superimposed display is performed. How to display information. 4. In the display method according to claim 3, when the raster data is image data and the vector data is map data, the key information of the image data and the map data is used as an intermediary regardless of the movement amount of the image data and the map data. An image display method characterized by maintaining the positional relationship between the two and displaying them in a superimposed manner. 5. The image information display method according to claim 1, wherein when the vector data is line segment data, the vector data is superimposed and displayed while maintaining a positional relationship with the raster data. 6. The image information display method according to claim 1, wherein when the vector data is surface data, the vector data is superimposed and displayed while maintaining a positional relationship with the raster data.