KR20150065302A

KR20150065302A - Method deciding 3-dimensional position of landsat imagery by Image Matching

Info

Publication number: KR20150065302A
Application number: KR1020130150460A
Authority: KR
Inventors: 김훈정; 정해진
Original assignee: 주식회사 한국지오매틱스
Priority date: 2013-12-05
Filing date: 2013-12-05
Publication date: 2015-06-15

Abstract

An existing treatment of satellite imagery through ground control point (GCP) and digital elevation model (DEM) by using a reference point and a figure map for a three dimensional modeling of satellite imagery requires a variety of reference materials, and a great deal of time and cost. However, the present invention treats satellite imagery by using rational polynomial coefficient (RPC) including information about the position and the location of the satellite classified by the characteristic and the type of the satellite imagery; performs an image matching by extracting a common spot between two images for producing the satellite imagery into a three dimensional image; and performs a three dimensional modeling of the satellite image by using DEM obtained by a stereo image processing. According to the present invention, by shortening the time and the cost for producing an orthophotograph through reduction of the cost and the period for processing the satellite image, the utilization of satellite images, which has been increasing in security and private sectors, can be more improved.

Description

TECHNICAL FIELD The present invention relates to a three-dimensional positioning method for a satellite image by a video matching method,

The present invention processes a satellite image through a GCP (Ground Control Point) and a DEM (Digital Elevation Model) using a reference point and a digital map for three-dimensional modeling of a satellite image, . However, in the present invention, a satellite image is processed using an RPC (Rational Polynomial Coefficient) coefficient including a satellite attitude and position information according to the characteristics and types of the satellite image, and in order to produce it as a stereoscopic image, And then performs image matting to perform 3D modeling of the satellite image using the DEM obtained through the stereo image processing, thereby producing an orthoimage image.

Recently, high-resolution satellite imagery has emerged and the rapid development of GIS technology has enabled various types of terrain information to be acquired and managed systematically. High-resolution optical satellites such as IKONOS, QuickBird, SPOT and KOMSAT The use of RADARSAT, which is a geographical information based data, is used for city management, various construction management, resource management, and environmental management. It has become necessary to construct information system for various purposes by linking information data with GIS, and integration of various information obtained by using low-resolution resolution satellite image and high resolution image data and integration of multiple sensor data can be utilized Various researches and inventions are in progress to make it very diverse. .

Due to the development of such high-resolution observing satellites, it has rapidly grown to the level of technology capable of replacing aerial photographing as well as local surveying. Digital orthoimage images produced using high-resolution satellites are the spatial information that can represent the real world most accurately and are used to produce various map images and user-centered thematic maps. Even if you have not been able to see the situation in your area of interest.

In the case of satellite image processing technology, development of tools and module technology for image processing centering on developed countries have been developed in a large part, and processing technology has been progressing with the development of payload and sensor technology. The most important aspect of processing technology for utilizing future satellite images is the management and utilization of vast amount of construction information, the automation of processing, and the development and acquisition of accuracy verification technology.

When the technology that can improve the utilization of satellite images is developed as described above, not only the development of technology such as ortho image production but also the improvement of the utilization of the national security dimension by improving the image acquisition and processing technology for the non-access areas Will be.

Conventional image modeling techniques are general modeling and physical modeling. In general modeling, DLT (Direct Linear Transformation) does not need an initial value to perform modeling, and calculation process is simple using modified form of collinear conditional expression, but it is less accurate than physical modeling. Modeling using the other polynomial, like the DLT, does not need an initial value to calculate the model. Depending on the situation, several types such as 1, 2, and so on are used and the calculation process is simple. However, . We used a method of modeling the external facial expressions for each line to be scanned using a rigorous adjustment method, which is a modeling technique using satellite orbital elements, with a polynomial over time, and determining a large number of external facial expressions with a small number of ground reference points. In this case, the first to third order formulas are used for the external facial expression element based on the collinear condition expression. However, if the information provided in the auxiliary data is accurate, it is possible to obtain very accurate results. However, There is a drawback in that it takes a lot of time and cost for image processing.

Recently, the processing of satellite image satellite image is using RFM image processing technique using RPC data. This method compensates the disadvantages of conventional general modeling method and physical modeling method. There is no need, and depending on the situation, various forms such as 1, 2, etc. are used. The calculation process is simple and complicated according to the order, and it is more accurate than the general modeling, but it has a disadvantage of saving the time and cost for the image processing although the accuracy is somewhat lower than the strict method. can do.

Previously, for the 3D modeling of the satellite images, a lot of cost and reference data were required to process the satellite image through the GCP and DEM extracted using the reference point and the digital map. However, in the present invention, the image is processed by the RFM method using the RPC coefficient including the satellite attitude and position information according to the characteristics and types of the satellite image, and in order to produce it as a stereoscopic image, Dimensional modeling of the satellite image using the DEM obtained by extracting the same points among the stereo images using the extracted points.

In order to solve this problem, the present invention processes a satellite image through an RFM method using RPC data, extracts the same points from the processed left and right stereoscopic images, and performs three-dimensional modeling of the satellite image by using image matching I want to.

In order to achieve the above object, the present invention adopts an RFM modeling method using improved RPC data rather than the existing modeling technique, extracts DEMs of overlapping regions through image matching using the same point extraction technique of two images A method of performing three-dimensional modeling, the method comprising: (a) acquiring a stereo satellite image and RPC data through satellite imaging; (b) Image modeling by RFM method using RPC data for image modeling; (c) extracting an identical point between stereoscopic images; (d) performing image matching of two images based on the same point extraction result; (e) extracting a DEM (Digital Elevation Model) from the Stereo image subjected to image matching; (f) A method for three-dimensional positioning through orthoimage production using the modeled satellite image and DEM data.

According to the present invention, it is possible to further increase the usability of the satellite image, which is being utilized in the military and civilian fields, because the cost and time for orthoimage production due to the reduction of the processing time and cost of the satellite image are shortened .

According to the present invention, it is possible to perform three-dimensional modeling without reference data constructed in advance. In particular, when the image matching technique proposed in the present invention is used, it is possible to improve the accuracy of the DEM, And the productivity is higher than that of the conventional method, thereby realizing high quality and low cost.

FIG. 1 shows an image processing process that requires GCP and DEM as a step of performing 3D modeling of a satellite image.
2 is a flowchart illustrating an overall image processing process proposed in the present invention.
FIG. 3 is a flow chart showing the sequence of image matching proposed in the present invention.
4 is a conceptual diagram of a patch and a search area in correlation matching.
5 is a conceptual diagram showing the position of the maximum correlation coefficient in the calculation of the peripheral pixel accuracy.
6 shows a hierarchical structure of an image.
FIG. 7 is a conceptual diagram of a stereoscopic image photographing for assisting an understanding of a stereoscopic image.

Hereinafter, the present invention will be described in more detail with reference to the drawings.

While the present invention has been described in connection with certain embodiments, it is obvious that the invention is not limited to the disclosed embodiments, but, on the contrary, is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the invention. It is to be understood, however, that the invention is not intended to be limited to the particular forms disclosed, but on the contrary, is intended to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the invention.

In the drawings, the same reference numerals are used for the same reference numerals, and in particular, the numerals of the tens and the digits of the digits, the digits of the tens, the digits of the digits and the alphabets are the same, Members referred to by reference numerals can be identified as members corresponding to these standards.

In the drawings, the components are expressed by exaggeratingly larger (or thicker) or smaller (or thinner) in size or thickness in consideration of the convenience of understanding, etc. However, It should not be.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The singular expressions include plural expressions unless the context clearly dictates otherwise. In the present application, the term " comprising " or " consisting of ", or the like, refers to the presence of a feature, a number, a step, an operation, an element, a component, But do not preclude the presence or addition of one or more other features, integers, steps, operations, components, parts, or combinations thereof.

Unless defined otherwise, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Terms such as those defined in commonly used dictionaries are to be interpreted as having a meaning consistent with the contextual meaning of the related art and are to be interpreted as either ideal or overly formal in the sense of the present application Do not.

Image Matching in (d) is a step of finding a matching point in a stereoscopic image (i) applying an image-based correlation matching technique; (Ii) applying a matching point approximation equation of surrounding pixel accuracy to improve the precision of the generated matching point; (Iii) applying a hierarchical structure in order to solve a problem that occurs when a correlation matching technique of (i) is applied to a region lacking a characteristic change, a linear boundary region, or a matching pattern error occurrence region; (Iv) correcting the matching error using the parallax information each time the matching of each layer is completed, in order to prevent a matching error of the upper layer from propagating to the lower layer. The accuracy of the satellite image can be improved by extracting the DEM data with improved accuracy by performing the 3D positioning using the extracted DEM data.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be described in detail with reference to the accompanying drawings.

2 is a flowchart of three-dimensional modeling using an image matching technique according to the present invention. Referring to FIG. 2, first, a satellite image and RPC data are acquired. In this case, when acquiring a satellite image, a stereoscopic image must be acquired so that stereoscopic vision can be performed. Stereo images are satellite images of the same area or object taken at different positions, and the height value can be calculated by using the satellite images.

Using the acquired satellite image and RPC data, geometric modeling of the image is performed using the RFM technique. RFM is a mathematical sensor modeling defined as one of four real-time geometry models with universal real-time image geometry model as an image conversion standard in OGC. RFM is a polynomial proportional model in which the denominator and the numerator are polynomials of higher order functions. The left and right satellite images acquired using this model are processed.

By using the satellite image and RPC data acquired from the above, the left and right satellite images obtained by geometric modeling by RFM processing method are obtained.

The image matching of the modeled satellite image is performed as shown in FIG.

(I) The correlation matching method is a step of applying the real-time correlation matching method. The correlation matching method calculates the correlation coefficient with the reference point of the left image at all positions included in the search area calculated as the reference point, To find the position that it has. As shown in FIG. 4, a patch f of pxp size is set around a pixel of the reference image (left image). For all the points in the search region, a patch g of the same size as the reference image patch is set to calculate the correlation coefficient r, and the point having the greatest correlation coefficient value is selected as the matching point. The correlation coefficient r is calculated by the following equation.

(Ii) a step of applying a matching point approximation formula of the neighboring pixel accuracy to improve the accuracy of the generated matching point, and as described in the previous step, by selecting a point having the largest correlation coefficient value in the search area, The matching point can be calculated. Here, by fitting the correlation coefficient to the surrounding pixels of the matching point having the maximum correlation coefficient as a quadratic function, it is possible to calculate the matching point of the peripheral pixel unit more precisely.

(Iii) a step of applying a hierarchical structure to solve a matching error in a region with insufficient characteristic change, a linear boundary region, and a repeated pattern occurrence region, which occurs when the correlation matching technique of (i) is applied, For example, in the case of an image structure having four layers as shown in FIG. 6, the lowest image is a raw image, and the width and width of the image are reduced to 1/2 every time one layer is ascended. In stereo matching of hierarchical structure, matching is performed from the upper layer and the result is applied to the lower layer. The position of the matching point in the lower layer is predicted using the upper layer matching point. When the image reduction ratio between the layers is 1: 2 as shown in FIG. 6, when the matching point (x_m, y_m) of the right image with respect to the pixel (x, y) (2p_x, 2p_y) for the reference image points (2x, 2y), (2x + 1,2y), (2x, 2y + 1) and do. The equation is expressed as follows.

(Iv) correcting the matching error using the parallax information each time the matching of each layer is completed, in order to prevent a matching error of the upper layer from propagating to the lower layer. Way

As described above, by using the RFM method using the RPC data, which is easy to perform the geometric modeling and has a certain accuracy, it is possible to perform geometric correction of the satellite image while reducing time and cost for modeling, We use a step - by - step image matching technique to improve the accuracy of DEM data acquisition for modeling.

Although the techniques that have been proposed in the basic image processing proposed in the present invention have been proposed through many studies, the present invention proposes additional techniques that can effectively use the techniques and improve the accuracy in the image matching step, And suggests ways to improve accuracy.

The background of the present invention can be said to be the presentation of an optimal solution for each step for three-dimensional positioning.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed exemplary embodiments. Should be interpreted as belonging to the scope.

Claims

(a) acquiring a stereo satellite image and RPC data through satellite image capturing
(b) Image modeling by RFM method using RPC data for image modeling
(c) extracting the same point between stereoscopic images
(d) Image Matching of two images based on the same point extraction result
(e) Extracting a DEM (Digital Elevation Model) from the Stereo image subjected to Image Matching
(f) positioning the 3D image using three-dimensional image processing using the modeled satellite image and DEM data.

The method according to claim 1,
Image Matching in (d) is a step of finding a matching point in a stereoscopic image,
(I) Applying the real-time correlation-matching technique
(Ii) applying a matching point approximation equation of surrounding pixel accuracy to improve the precision of the generated matching point;
(Iii) Applying a hierarchical structure to solve the problem of matching error in (a), (b), (c), (c)
(Iv) correcting the matching error using the parallax information each time the matching of each layer is completed, in order to prevent a matching error of the upper layer from propagating to the lower layer. Way