CN102567701A - Method for automatically extracting circular impact craters from ChangE DEM (Dynamic Effect Model) data by Hough transformation - Google Patents

Abstract

The invention provides a method for automatically extracting circular impact craters from ChangE DEM (Dynamic Effect Model) data by Hough transformation, wherein the DEM data is considered as a grid image and characteristic units are extracted by a digital image processing method. The method of invention has the advantages that geomorphologic characteristics of the moon is taken into consideration, extraction algorithm is particularly considered due to different earth geomorphologies, execution algorithm is optimized, accidental errors brought by manual operation are avoided and the identifying speed is improved greatly; the execution results are standard vectors which are used to calculate the surface features conveniently. The invention can be applied to rapidly identify the impact craters in a large area such as Mars, moon and the like.

Description

A kind of method of utilizing Hough transformation on goddess in the moon's dem data, to extract annular impact crater automatically

Technical field

The invention belongs to the digital Terrain Analysis field of GIS.The present invention is a kind of method of utilizing Hough transformation on goddess in the moon's dem data, to extract annular impact crater automatically; Particularly with the method processing feature unit of Digital Image Processing; Utilize Hough transformation, and with reference to moon terrain parameter characteristic, thereby the method for extracting impact crater identification obtained.Present invention is directed at moon impact crater, also can be applicable to the identification of planet impact craters such as Mars.

Background technology

List of references

[1].Daul，C.，Graebling，P.，and?Hirsch，E.[1998].“From?the?Hough?Transform?to?a?New?Approachfor?the?Detection?of?and?Approximation?of?Elliptical?Arcs，”Computer?Vision?and?ImageUnderstanding，vol.72，no.3，pp.215～236.

[2].Duda，R.o.，and?hart，P.E.[1972].“Use?of?the?Hough?Transformation?to?Detect?Lines?andCurves?in?Pictures.”Comm.ACM，vol.15，no.1，pp.11～15.

Say that from research method the quality testing method of determining and calculating can be divided into three major types substantially circlewise: complete autonomous (fully autonomous) algorithm, half autonomous detection algorithm and the combine detection algorithm of detecting.Complete autonomous detection algorithm is called non-supervision detection algorithm (unsupervised detection) again, utilizes the geometric properties of annular atural object exactly, and rounded or ellipticity as its edge goes to detect through the correlation technique of pattern-recognition; So-called half autonomous detection algorithm is called supervision again and detects (supervised detection), utilizes machine learning (machine learning) and neural network to make up pattern classifier exactly and is used for detecting; So-called combine detection algorithm integrates multiple detection method exactly and is used, and comprises from the half autonomous algorithm of advocating peace.

Native system adopts complete autonomous detection algorithm, promptly according to the geometric properties of annular atural object, goes to detect through the associative mode recognition methods.Concrete steps do, at first carry out Image Edge-Detection, obtain the border bianry image, utilize Hough (Hough) conversion then, detect annular atural object, last passing threshold analysis, and the result who analyzes filters arrangement.

List of references

[1].Gonzalez，R.C.[1986].“Image?Enhancement?and?Restoration.”In?Handbook?of?Pattern?Recognition?andImage?Processing，Young，T.Y.，and?Fu，K，S.(eds.)，Academic?Press，New?York，pp.191～213.

[2].Guil，N.，and?Zapata，E.L.[1997].“Lower?Order?Circle?and?Ellipse?Hough?Transform，”pattern?Recog.，Vol.30，no.10，pp.1729～1744.

Based on the automatic identification mountain valley of dem data and the procedure of topographical crest, can analyze atural object fast on the one hand, also can avoid only discerning the influence of the accidental error of bringing on the other hand with artificial naked eyes.Through the development in surplus 30 years and perfect, a lot of algorithms have appearred in the present Extraction of Topographic Patterns based on DEM.These algorithms are said from the scope angle; The branch that local algorithm and total algorithm are arranged; The former classifies to each independent element based on the local characteristics on the face of land, is called partial approach, and the latter obtains the landform Global Information from whole dem data scope; Thereby attempt to obtain terrain feature, be referred to as total algorithm through the topographical features structure of a unanimity; Discern in the algorithm of linear atural object the identification of the local DEM of most rule-based earth.

List of references

[1].Desmet?P?J?J，Govers?G.1996a.Comparison?of?routing?algorithms?for?digital?elevation?modelsand?their?implication?for?predicting?ephemeral?gullies.International?Journal?ofGeographical?Information?science，10(10)：311～331.

Summary of the invention

The present invention is directed to the defective that exists in the prior art, a kind of method from moon DEM rapid extraction impact crater is provided, is a kind of method of quick, simple, pervasive extraction impact crater.

Technical scheme of the present invention is following:

A kind of method of utilizing Hough transformation on goddess in the moon's dem data, to extract annular impact crater automatically, it is characterized in that comprising following steps: (1) edge strengthens (utilizing Gauss's Laplace operator); (2) utilize menology geographical unit characteristic, carry out fast Hough transformation; (3) extract the result and put in order, reject because the false impact crater that specific noise produces; (4) result is saved as vector.

(1) edge strengthens: the essence of rim detection is to adopt certain algorithm to extract the boundary line between object and background in the image.We are defined as the edge, and zone boundary jumpy takes place in gray scale in the image.The situation of change of gradation of image can reflect with the gradient that gradation of image distributes, so we can obtain edge detection operator with topography's differential technology.

For convenience, the following formula of definition;

is the gradient of image, and comprises grey scale change information

is the gradient of

; (x y) can be used as edge detection operator to e.In order to simplify calculating, also can (x y) be defined as partial derivative f with e _xWith f _yThe absolute value sum:

e(x，y)＝|f _x(x，y)|+|f _y(x，y)|

With these theories is foundation, has proposed many algorithms, once more columns one by one not.Consider that the input data possibly comprise very big noise; Adopt squelch Laplacian of Gaussian (LoG) operator preferably to this function; Form LoG (Laplacian of Gaussian; LoG) algorithm, the essential characteristic that also is referred to as Laplce's Gauss algorithm .LoG edge detector is:

1. smoothing filter is a Gaussian filter.

2. enhancing step adopts second derivative (two-dimentional Laplace function).

3. the rim detection criterion is the big peak value of second derivative zero cross point and corresponding first order derivative.

4. use the position of linear interpolation method estimated edge on the subpixel resolution level.

The characteristics of this method are that image at first carries out convolution with Gaussian filter; This step not only level and smooth image but also reduced noise; Isolated noise spot and small construction tissue will be by filterings. owing to smoothly can cause the extension at edge; Therefore edge detector only considers that those have the peaked point of partial gradient is marginal point. and this point can realize with the zero cross point of second derivative. and Laplace function is approximate as two-dimentional second derivative; Be because it is a kind of directionless operator. for fear of detecting non-prominent edge, should select first order derivative greater than the zero cross point of a certain threshold value as marginal point.

The output h of LoG operator (x y) obtains through convolution algorithm:

$h(x,y)={\▿}^2[g(x,y)*f(x,y)]$

Have according to the convolution method of derivation

$h(x,y)=\left[{\▿}^{2}g(x,y)\right]*f(x,y)$

Wherein:

${\&dtri;}^{2}g(x,y)=\left(\frac{x^2+y^2-2{\mathrm{\&sigma;}}^2}{{\mathrm{\&sigma;}}^4}\right)e^{\frac{x^2+{\mathrm{<figure-callout\; id="2"\; label="y"\; filenames="HSA00000377664400011.png"\; state="\{\{state\}\}">y</figure-callout>}}^2}{2{\mathrm{\&sigma;}}^2}}$

Filtering (normally level and smooth), strengthen, detect these three edge detecting step and still set up, wherein smoothly accomplish with Gaussian filter to using the LoG rim detection; Enhancing becomes zero cross point to realize edge transition; Rim detection is then carried out through detecting zero cross point.

Can see; The variation contrast of the slope dependent of zero cross point when image intensity is being passed the edge. remaining issues is to be combined those by the detected edge of different scale operator. in said method; The edge is under specific resolution, to obtain. in order from image, to obtain real edge, be necessary the information combination that obtains those through the different scale operator.

(2) fast Hough transformation:

1, the center of circle confirms

Calculate each pixel (i, angle theta j);

$\mathrm{\&theta;}[i,j]={\tan }^{-1}\left(\frac{\&PartialD;f}{\&PartialD;y}\right[i,j]/\frac{\&PartialD;f}{\&PartialD;x}[i,j\left]\right)={\tan }^{-1}\frac{\mathrm{sobe}{l}_{\mathrm{vert}}[i,j]}{\mathrm{sobe}{l}_{\mathrm{horiz}}[i,j]}$

Do the normal direction line segment on border, then, the circle centre position of circle is the intersection point of this circle, i.e. bright spot (hot spots).Then line segment be mapped to (a, b) space:

$\left.\begin{array}{c}a=r\sin \mathrm{\&theta;}\\ b=r\cos \mathrm{\&theta;}\end{array}\right\}r\&Element;(\min r,\max r)$

A(i±a，j±b)←A(i±a，j±b)+E(i，j)

$R\left(r\right)=\underset{P\&Element;\mathrm{circule}\left(r\right)}{\mathrm{\&Sigma;}}E\left(P\right)$

Wherein (minr, maxr) for detecting the minimax radius of annulus, A is that (E is the pixel boundary value for a, b) space.Be described below shown in the figure;

2, radius confirms

Wherein for being P for the center of circle, each belong to interval (minr, pixel maxr) are mapped to the r space:

$R\left(r\right)=\underset{P\&Element;\mathrm{circule}\left(r\right)}{\mathrm{\&Sigma;}}E\left(P\right)$

Under the situation of r space greater than a certain threshold value, then maximal value can be regarded as the radius in this center of circle.

Description of drawings

Fig. 1 edge extracting operator synoptic diagram.

Fig. 2 Hough transformation algorithm synoptic diagram.

Fig. 3 the present invention is based on the algorithm flow chart of Hough transformation.

Claims (4)

1. one kind is utilized Hough transformation automatic method of extracting annular impact crater on goddess in the moon's dem data; It is characterized in that regarding dem data as grating image; Utilize the method for Digital Image Processing merely, and combine lunar surface performance to regulate parameter, reach the purpose of maximum extracted impact crater; It specifically comprises following steps: (1) is carried out the edge through edge detection operator and is strengthened; (2) utilize Hough transformation to extract annular feature; (3) extraction result's arrangement; (4) result is saved as vector.

2. according to right 1 described a kind of method of utilizing Hough transformation on goddess in the moon's dem data, to extract annular impact crater automatically; It is characterized in that: the unevenness of considering moonscape; Employing is to adopt squelch Laplacian ofGaussian (LoG) operator, i.e. Laplce's Gauss algorithm preferably;

3. according to right 1 described a kind of method of utilizing Hough transformation on goddess in the moon's dem data, to extract annular impact crater automatically; It is characterized in that: through the relation in the annular radii and the center of circle; Quote Fast Hough Transform Algorithm, make not to be the growth of geometric series working time owing to the increase of image;

4. according to right 1 described a kind of method of utilizing Hough transformation on goddess in the moon's dem data, to extract annular impact crater automatically, it is characterized in that: use the menology rule on the Hough transformation parameter, reach the maximum accuracy rate of the moon.

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