CN101149843A - Succession type automatic generation and real time updating method for digital city - Google Patents
Succession type automatic generation and real time updating method for digital city Download PDFInfo
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Abstract
The digital-city inherit-type automatic generating and real-time renewing method of using existing digital cities and repository includes: obtain remote-sensing images in different times to be conducted change monitoring and produce a changed image; identify object in the changed image and match the identified object with the 3-D model in the repository; plant the 3-D model returned from the matching into corresponding position of the said digital city. Advantage: automatically renewed digital city and reduced workload. The renewing data is mainly of contrast changing.
Description
Technical field
The present invention relates to a kind of geographical space analogue technique, the method for automatic generation of in particular a kind of digital city succession type and real-time update.
Background technology
Notion involved in the present invention below at first is described:
1, digital city (Digital city): can realize the overall management of the urban area and decision support, virtual, as to have opening city model for one;
2, three-dimensional model (3D model): the three-dimensional polygon of object represents that logical conventional computer or other video equipment show.Objects displayed is can be the entity of real world, also can be the thing of fabricating, and both may diminish to atom, also can arrive very big size greatly.The thing that any physics nature exists can be represented with three-dimensional model.
3, texture (Texture): in fact a texture is exactly a bitmap.In this sense, when texture one speech is used to computer graphical class hour, it has just had a clear and definite definition.From the semantics angle, texture one speech both had been meant the pattern of color on the object, was meant that again body surface is coarse or smooth.
4, knowledge base (Knowledge Base): structuring in the knowledge engineering, easy to operate, easily utilize, comprehensive organized knowledge cluster, be the needs of finding the solution at a certain (or some) field question, the knowledge sheet that the interknits set of adopting certain (or some) knowledge representation mode in computer memory, to store, organize, manage and use.These knowledge sheets comprise the knowwhy relevant with the field, factual data, and the heuristic knowledge that is obtained by expertise is as definition relevant in certain field, theorem and algorithm and common sense knowledge etc.It is intelligent that knowledge base has KBS Knowledge Based System (or expert system), and not all program with intelligence all has knowledge base, has only KBS Knowledge Based System just to have knowledge base.Present many application programs are all utilized knowledge, and what wherein have has also reached very high level, and still, these application programs may not be KBS Knowledge Based System, and they do not have knowledge base yet.General application program and the difference between the KBS Knowledge Based System are: general application program is impliedly to be coded in the knowledge of problem solving in the program, KBS Knowledge Based System is then expressed the problem solving knowledge explicitly of application, and forms a relatively independent program entity individually.
The characteristics of knowledge base are as follows:
1) knowledge in the knowledge base is configured the organizational form of being convenient to utilize, structure is arranged according to their application feature, background characteristics (background information when obtaining), use characteristic, attributive character etc.The knowledge sheet generally is modular.
2) knowledge of knowledge base is stratified.Lowermost layer is " fact knowledge ", and the middle layer is the knowledge (representing with rule, process etc. usually) that is used for controlling " fact "; Highest level is " strategy ", and it is a controlling object with middle layer knowledge.Strategy also usually is considered to the rule of rule.Therefore the basic structure of knowledge base is hierarchical structure, is determined by the characteristic of its knowledge itself.In knowledge base, all there is relation of interdependence between the knowledge sheet usually.Rule is typical, the most the most frequently used a kind of knowledge sheet.
3) a kind of knowledge that not only belongs to the special shape of a certain level (level in office in other words all exists) can be arranged in the knowledge base---confidence level (or claiming degree of belief, confidence measure etc.).To a certain problem, relevant facts, rule and strategy all can be marked with confidence level.Like this, just formed the augmentation knowledge base.In database, there is not uncertainty measure.Because all belong to " determining type " in the processing of database.
4) also can there be a special part that is commonly referred to as the typical method storehouse in the knowledge base.If the solution route for some problem is to affirm with inevitable, just can directly be stored in it in typical method storehouse as the quite sure problem solution route of a part.The storage of this macroscopic view will constitute another part of knowledge base.When using this part, machine inference will be only limited to certain one deck body portion of selecting for use in the typical method storehouse.
In addition, knowledge base also can realize on distributed network.Like this, just need to build distributed knowledge base.The superiority of building distributed knowledge base has 3 points:
(1) can under lower price, construct bigger knowledge base;
(2) problem-solving task of the knowledge base correspondence of different levels or different field is relatively more simple comparatively speaking, thereby can constitute the system of more efficient;
(3) can be suitable for geographic distribution vast in territory.
The structure of knowledge base must make knowledge access and search effectively in the process that is used wherein, and the knowledge in the storehouse can be revised and edit easily, simultaneously, the consistance and the complete performance of knowledge in the storehouse is tested.
5, images match (image matching): be meant that two different sensors are enrolled two width of cloth images that get off from same scenery spatially aims at, determining the process of relative translation between this two width of cloth image, it can be widely used in aspects such as target following, resource analysis, medical diagnosis is important techniques very in the present information process field.
6, image similarity (image semblance): the probability that is meant another width of cloth image of piece image " screw-in " has provided a succinct image similarity algorithm simultaneously.By repeatedly experiment, this image similarity is effective and satisfied for the identification of complex patterns, can be used for the systematic searching of image.Similarity is included in the similarity degree of aspects such as shape, structure, statistics, texture, environment, height size.
7, digital city image library: the storehouse that image constituted by all objects in the digital city is the digital city image library, this storehouse can be divided into according to the type of object architectural drawing as word bank, road image word bank, bridge image word bank, plant image word bank, animal painting word bank, waters image word bank, aerography as word bank, formation map as word bank.
8, digital city model bank: the three-dimensional model by all objects in the digital city constitutes, and its classification is corresponding with the digital city image library.Comprise all characteristic informations on the object dimensional in the model, comprised shape, color, texture or the like.
9, digital elevation model (DEM) also claims digital terrain model (DTM), is a kind of continuous representation method to the space fluctuations.Because DTM is implied with the meaning of landform landscape, so DEM commonly used is with simple expression elevation.Can download the free global altitude figures of 30 meters precision from the Internet.
The digital city is technology such as integrated use GIS, remote sensing, remote measurement, broadband network, multimedia and virtual emulation, infrastructure, the functional mechanism in city is carried out the technological system of automatic information collecting, dynamic monitoring management and aid decision making service; It has the powers such as digitizing, networking, virtual emulation, optimum decision support and visual representing of complication systems such as urban geography, resource, ecologic environment, population, economy, society.The digital city provides important supporting tool for the city sustainable development.
Visual is to realize digital city and mutual window and the instrument of people, does not have visualization technique, and a pile numeral in the computing machine does not have in all senses, and a distinguishing feature of digital city is a virtual reality technology.After having set up the digital city, the user puts on and shows the helmet or from computer screen or from large screen projection, just can see that the city occurs from the earth, uses mouse or keyboard amplifier digital image; Along with improving constantly of resolution, the user can see private accommodation, shop, trees and other natural and man-made tourist site, when the user is interested in commodity, can enter in the shop, appreciate the clothes in the market, and can construct the virtual scene that oneself tries on a dress according to the build of oneself.
Virtual reality technology is human observation of nature, appreciates view, and understanding entity provides sensation on the spot in person.Recent years, the virtual reality technology development is very fast, and virtual reality modeling language (VRML) is a kind of towards Web, OO three-dimensional modeling language, and it is a kind of interpreted language.It not only supports the three dimensional representation of data and process, and can make the user come into audio visual effect virtual world true to nature, thereby realizes the expression of digital earth and realize the research of various earth phenomenons and people's daily use by digital earth.In fact, artificial virtual reality technology is proven technique already in photogrammetric, the development of digital photogrammetry in recent years, and can set up on computers can be for the digital virtual technology that is survey.Certainly, current technology is that same entity is taken pictures, and produces parallax, and the constructing stereo model is normally worked as models treated.Further development is the whole earth to be carried out seamless spliced, roams arbitrarily and amplifies, by the method for three-dimensional data by artificial parallax, constructing virtual solid.
The technology of existing structure digital city as Fig. 1, Fig. 2, shown in Figure 3, is the way of three kinds of structure digital citys commonly used, and is similar with other scheme, and just modeling is different with the instrument of playing up.The common trait of such scheme is: the photo according to collection in worksite arrives, carry out manual three-dimensional modeling, and the manual position of each object in the scene of city of demarcating, then with the manual relevant position that joins in the scene of city of the three-dimensional model of each object.
Utilize technique scheme, after in case the city modeling finishes, the digital city has just been determined, and no longer change, if caused the looks in city after several years that very big variation has taken place, actual appearance of city just can not be reflected in former digital city, and the digital city just needs to make fully again, and in fact the digital city of new edition and former digital city are repeated in a lot of local work, but existing technology can't be utilized this characteristic.
The existing digital city all utilizes manual modeling technique to form, if designed a city I at A digital city Ia constantly, designed city I afterwards again at B digital city Ib constantly, then city I understands brand-new design at B digital city Ib constantly, and can not utilize the city I that has existed at A digital city Ia constantly.Because can't differentiating, existing technology do not change part and the existing part that changes between the different cities constantly, that is to say the research and development again of all starting from scratch of prior art all digital citys when making up the digital city, and can not utilize the research and development achievement in existing digital city, this is a kind of waste to existing digit city research and development achievement, cause the R﹠D work of a lot of repeatability, also caused the R﹠D costs of digital city high.
With the Shenzhen is the example explanation, even a digital Shenzhen of doing before 3 years has been arranged, very big variation has taken place in Shenzhen between 3 years, for example increase some buildings newly, transformed some buildings, removed some buildings or the like, so the true appearance in present Shenzhen can not be truly reflected in the digital Shenzhen of doing before 3 years, need do the digital Shenzhen that to reflect the present looks in Shenzhen.According to existing technology, owing to can't accurately know " increased which building newly, transformed which building, removed which building ", or the like the variation that Shenzhen took place, so utilize prior art still need with camera to all objects in the city take pictures one by one, manual modeling one by one, again the model of building up is demarcated and is arranged to the correct position in the scene of digital city one by one by hand, workload is very big, and its building process is without the slightest difference with structure digital Shenzhen before 3 years.This process need expends great amount of manpower (remove to gather photo, go manual modeling, go manual the demarcation and the arrangement model), expending a large amount of financial resources (needs a lot of cameras to use for gathering photo, need a lot of computing machines for manual modeling, manual demarcate and settle model with), expend a large amount of time and (build a model and sometimes just need 1 day, have thousands of object to need modeling in the city, for example the digital city, Shenzhen just can be finished with the minimum time in 3 years of needs of prior art).
And the development in city at present is with rapid changepl. never-ending changes and improvements, and that official thinks to command on the spot in personly is emergent, it is violating the regulations to investigate and prosecute, and the resident thinks to travel home-confinedly, or the like, these only just can be accomplished in the digital city.If need spend long time but do a digital city, as utilize existing technology, digital Shenzhen needed for 3 years, and those people can give city emergency, the consequence of the bringing on a disaster property such as monitoring of breaking rules and regulations before seen in digital Shenzhen all are 3 years.In fact, making rapid progress really of the variation in Shenzhen, every day, the looks in city all can change, so the digital city needs to upgrade to finish at least within one day just can be of practical significance, could make this digital city really can represent and reflect real city, could make the application on this digital city really to play a role, could provide real-time support for city emergency, monitoring violating the regulations, point duty, digital living.And existing technology is not owing to make full use of existing digital city achievement, and upgrading needs repetitive operation, can't accomplish real-time update and practicability.
Therefore, there is defective in prior art, and awaits improving and development.
Summary of the invention
The object of the present invention is to provide a kind of succession type of digital city to generate automatically and real time updating method, change the manual modeling pattern of existing digital city, and disposable use present situation, the process of utilizing succession type to generate automatically realizes reusing of digital city, avoids the waste of digital city resource; And, shorten the cycle of digital city research and development by the reusing of digital city previous achievements, improve the efficient of digital city research and development.
Technical scheme of the present invention comprises:
A kind of succession type of digital city generates and real time updating method automatically, and it is applied to a general-purpose computing system, utilizes existing digital city and knowledge base, and may further comprise the steps:
A, obtain remote-sensing images in different times and carry out variation monitoring, generate a striograph that changes;
B, in the striograph that changes, carry out object identification, the object that identifies and the three-dimensional model in the knowledge base are mated;
C, the three-dimensional model that coupling is returned are implanted the correspondence position in the described digital city, generate the digital city of one time of back in real time.
Described method, wherein, described steps A is further comprising the steps of:
A1, find the same place in the remote-sensing images in different times to extract automatically, comprise angle point, the extraction of flex point, road cross spider as the reference mark;
A2, based on the geometrical registration method of affined transformation model, seek the image same place earlier, bring the affined transformation model of foundation into, by repeatedly calculating optimum affine transformation parameter, according to optimum registration parameter input picture is carried out coordinate transform, obtain 2 o'clock phasors that mate substantially in the geographic position;
A3, did on the phasor at 2 o'clock the atural object level other relatively, the striograph Δ P that obtains changing.
Described method, wherein, described steps A 2 also is included in a plurality of same places of rejecting the deviation maximum before each calculating.
Described method, wherein, the forming process of described knowledge base also is provided with an image library, and it comprises step:
D1, from remote sensing image, extract the representational image of various types of individualities, and these representational images are classified, extract its general character, form first order characteristic image;
D2, in this rank, mark off subclass, and in all images of each subclass, extract general character respectively, give a characteristic image respectively for each subclass;
So analogize, up to its divide represented basically should the representational all kinds of individuality till.
Described method, wherein, the taxonomic structure that a model bank is set is consistent with the taxonomic structure of described image library, and an image in the image library is corresponding with a model in the model bank.
Described method, wherein, the static model that the model in the described model bank is to use the instrument of modeling to build up.
Described method, wherein, the model in the described model bank is to use parametric description and the three-dimensional model of real-time rendering when needed.
Described method, wherein, the mapping relations between described image library and the model bank may further comprise the steps:
D3, the object in the remote sensing image is extracted and discerns according to image library;
D4, the subclass of the object that extracts and the respective classes in the image library is carried out similarity relatively, and retrieve in the image library image with this object similarity maximum, and be mapped to corresponding model in the model bank;
D5, the individuality in the remote sensing image is carried out automatic modeling by knowledge base.
Described method, wherein, described step D5 also comprises:
D51, remote sensing image is scanned, obtain the set of the object of each big class, judge the similarity between this object and these characteristic images according to the first order characteristic image in the image library;
D52, from image library, find out the accurate classification under this object.
Described method, wherein, described step D52 comprises:
D521, the characteristic image that the next stage of this subject image and classification under it is classified compare, if the characteristic image similarity of this individual images and a certain class is the highest, judge that then this individual images belongs to such;
D522, this individual images and each characteristic image of such next stage are mated respectively, and calculate its similarity, find the classification under the maximum characteristic image of similarity, as the classification under this subject image;
So analogize, reach the expection requirement up to its similarity.
The succession type of a kind of digital city provided by the present invention generates and real time updating method automatically, pass through remote sensing technology, can realize renewal process automatically to the digital city, its data updated is based on changes in contrast, therefore workload reduces, realized real-time digital city renewal process, can provide reference accurately for practical application.
Description of drawings
Fig. 1 is the digital city generation technique synoptic diagram of prior art;
Fig. 2 is the another kind of digital city generation technique synoptic diagram of prior art;
Fig. 3 is another digital city generation technique synoptic diagram of prior art;
Fig. 4 a be the succession type of digital city of the present invention automatically generate and real time updating method in build the storehouse schematic flow sheet;
Fig. 4 b is the schematic flow sheet of succession type of the present invention digital city automatic manufacturing method;
Fig. 4 c is the schematic flow sheet of succession type of the present invention digital city real-time update;
Fig. 5 is the processing flow chart of the variation striograph of the inventive method;
Fig. 6 a and Fig. 6 b are respectively remote sensing images of the present invention;
Fig. 7 is the taxonomic structure synoptic diagram of the image library of the inventive method;
Fig. 8 is the taxonomic structure synoptic diagram in the recognition rule storehouse of the inventive method;
Fig. 9 is the model bank taxonomic structure synoptic diagram of the inventive method;
Figure 10 is image library of the inventive method and the mapping synoptic diagram between the model bank;
Figure 11 is the treatment scheme principle schematic of the inventive method;
Figure 12 is the concrete treatment scheme synoptic diagram of the inventive method.
Embodiment
Below in conjunction with accompanying drawing, will be described in more detail each preferred embodiment of the present invention.
The succession type of digital city of the present invention generates and real time updating method automatically, based on the existing digital city, on the basis in existing digital city, utilize the variation of remote sensing image that the existing digital city is revised, the digital city generates automatically and the purpose of real-time update thereby reach.Suppose that the remote sensing image that the present invention obtains different time T1, T2 carries out variation monitoring, generate a striograph that changes; Wherein T1 is early than T2.If the digital city C1 of T1 time exists, then utilize this C1; If in the digital city that T2 did not build up before the time, then can utilize previous patent " the full-automatic method that generates in a kind of digital city " to generate the digital city C1 of T1 time.
Patent " the full-automatic method that generates in a kind of digital city " may be summarized as follows: it and has utilized remote sensing image, specifically at first to finish the making of digital city at a multi-purpose computer, shown in Fig. 4 a, specifically comprise: by shade monitoring algorithm, monitoring out the length of all shades on the remote sensing image, is that prior art is known about the shade length calculation; The remote sensing image in city is carried out vector quantization, thereby obtain the shape of different cities object; And the position of object and the position of shade mated, thereby obtain the height of object; Computation process about vector quantization also is that prior art is known, therefore, repeats no more; Gather the image and the corresponding model thereof of various buildings, vehicle etc. in the city, put into knowledge base, analyze the city data in the remote sensing image, with the individual segregation in the city, for example vehicle, building etc., and from remote sensing image, extract individual's characteristic image, automatically add image library, according to the personal feature image, judge through the identification of human eye to add and gathers this individual three-dimensional information on the spot, then modeling and add model bank; Characteristic according to the image of different objects in the image library is discerned different objects in remote sensing image, thereby obtains the type and the footstock shape thereof of different cities object; Secondary characteristics image according to each type objects in the image library in this process mates this type objects in the remote sensing image, belongs to which subclass thereby discern each object; So analogize, know that the effect of identification has reached requirement, thereby obtain the particular type of all city objects in the image; According to dissimilar, base shape, the shape of footstock, the height combination model storehouse of city object, generate the three-dimensional model of city object automatically; Obtain the landforms of digital city and the height fluctuating of landform thereof according to DEM and remote sensing image; With the three-dimensional model of these above-mentioned city objects, inlay in the remote sensing image with elevation according to the position of their two-dimensional coordinates, just generated the digital city automatically to this step.
The succession type of digital city of the present invention generates and real time updating method automatically, shown in Fig. 4 b and Fig. 4 c, it is the overall plan design of the inventive method, on the producing method of the digital city of prior art, its variation part of judgement by remote sensing images, and in conjunction with existing city knowledge base, the modeling of revising is handled, and finally produces real-time digital city.
Concrete computation process is: city I a constantly digital city Ia and city I be carved into that b takes place constantly during from a be changed to Δ Iab, generate city I automatically at b digital city Ib=Ia+ Δ Iab constantly, wherein a constantly should be early than b constantly.So the variation that the inventive method utilizes existing digital city and city to take place generates new digital city automatically, made full use of the existing digital urban resource, and the variation in city in the reality and digital city combined, make the digital city can and real city upgrade synchronously.
With Shenzhen is the example explanation, and as Figure 11 and shown in Figure 12, the S of Shenzhen promptly was digital Shenzhen S2000 in 2000 at X1.Arrived X2 promptly 2006, very big variation has also taken place in appearance of city, so need be digital Shenzhen S2006 again.Technical solution of the present invention is exactly to take the remote sensing images P of Shenzhen (X1)=P2000 in 2000 and the remote sensing images P of Shenzhen (X2)=P2006 in 2006 to compare, and finds the striograph Δ P=P2006-P2000 of variation.According to the part Δ P of this variation, utilize existing city knowledge base to generate Δ S, then so just can obtain S (X2)=S2006=S2000+ Δ S.
Mainly contained for two steps in the scheme of the inventive method:
The first step: take city S remote sensing images P2000 in 2000 and city S remote sensing images P2006 in 2006 to compare, find the striograph part Δ P=P2006-P2000 of variation, also comprise following process in this step:
Phase one: find two figure same places to extract automatically, comprise angle point, extractions such as flex point, road cross spider as the reference mark.At atural object not simultaneously, on the more difficult correspondence in the reference mark of two figure, possible impact point number differs greatly.
Subordinate phase: computational geometry registration affine transformation parameter, bring polynomial expression into according to same place, and reject the too big same place of part deviation.Through repeatedly calculating, obtain optimized parameter, and image is done affined transformation, the basic 2 o'clock corresponding phasors of this stage output atural object geographic coordinate according to this parameter.
Phase III: other compares to doing the atural object level on two width of cloth figure, the striograph Δ P that obtains changing.This step is the key of variation monitoring effect, also is the difficult point place, because the shooting angle difference, shade launching position difference just may cause pseudo-impact point.Often the situation of Chu Xianing is, the image that the land used of variation changes, but the image that changes may not be the land used that changes, therefore the present invention is not two simple pixel level comparisons but rises to the contrast of atural object level, identification atural object is that unit compares with atural object, such as meadow, building etc.
Second step: according to the striograph part Δ P of the variation of remotely-sensed data, (this knowledge base has been set up when generating the digital city first to utilize the knowledge base of city S simultaneously, and pass in time and can manually revise) generate the digital city part Δ S that changes, so the present invention just can obtain the present digital city S2006=S2000+ Δ S of city S.This step also comprises concrete process:
Phase one: the object M among the striograph part Δ P that changes in the remotely-sensed data that the first step is obtained, mate with three-dimensional model in the knowledge base, carry out individual identification.If the matching degree of object and some three-dimensional building models is judged, judge that coupling meets the requirements, and then returns this three-dimensional model.
Subordinate phase: the position (longitude and latitude) at the three-dimensional model implanted object M place that will return the phase one, according to disparity map Δ P, implant on the digital city S (X1) formerly, pull out, operation such as correction, the digital city of synthetic X2.
The processing procedure of following more specific description the inventive method.
The first step: the variation in monitoring city: the remote sensing image with different year carries out the striograph that variation monitoring generates an amplitude variationization earlier, on the block of detected variation, carry out object identification then, to the object that identifies in conjunction with knowledge base, give its specific object, for example, if this object is a building, its attribute has height, shape, texture so.
Its treatment scheme as shown in Figure 5, remote sensing image Fig. 1 and remote sensing image Fig. 2 are the remote sensing images of different year, by change-detection of the present invention, promptly obtain disparity map, also the striograph Δ P that promptly changes discerns its object features and position etc. then, and by its knowledge base recognition object attribute.Actual detection effect example is shown in Fig. 6 a and Fig. 6 b, even the satellite of homology or the data of taking photo by plane are arranged, the shooting time of its different year may be different, sun altitude difference during shooting, the not equal situation of weather all can be brought error to change-detection, therefore will carry out registration and corresponding the processing to image before variation monitoring.
The object that monitors is discerned, need utilize rule base, image library, rule in the recognition rule storehouse is divided according to the coupling of different aspect, as shown in Figure 8, as detection rule of detection rule, environment similarity of living in and the difference of detection rule, texture similarity and the difference of detection rule, gray scale similarity and the difference of detection rule, color similarity degree and the difference of: the detection rule of detection rule, structural similarity and the difference of shape similarity and difference, statistics similarity and difference or the like.
Image sampling in the image library is from remote sensing image, its taxonomic structure signal as shown in Figure 7, be specially: the representational image that from remote sensing image, extracts various types of individualities, and these representational images are classified, extract general character, become first order characteristic image, and then mark off subclass in this rank, and in all images of subclass, extract general character, give a characteristic image for this subclass, so analogize, up to its divide represented basically should the representational all kinds of individuality till.The variation object that monitoring is come out carries out similarity relatively with the subclass of the respective classes in the image library, and retrieves in the image library image with this object similarity maximum, and is mapped in the model bank model accordingly.
As follows by knowledge base: as according to the first order characteristic image in the image library remote sensing image to be scanned, obtain the set of the object of each big class to the process that the individuality in the remote sensing image carries out automatic modeling.First order classification has the characteristic image of building, the characteristic image of bridge, the characteristic image on square, the characteristic image of flowers, plants and trees, characteristic image of water or the like.
Judge the similarity between this object and these characteristic images.Similarity comprises: the similarity of the similarity of the similarity of shape, the similarity of structure, statistics, the similarity of color, gray scale, the similarity of texture, similarity of environment of living in or the like.As seen similarity has a lot of components, the present invention can decide by the initial analysis to individuality and adopt which similarity, and in judging this individuality and image library, give different weights for dissimilar similarities during the similarity of image, the method for employing weighting when differentiating final similarity then.
The taxonomic structure in the recognition rule storehouse of the inventive method as shown in Figure 8, after the object image of from remote sensing image, monitoring out variation, from image library, find out the accurate classification (as: building/high building/office building) under this object, its method is: at first the characteristic image that the next stage of this subject image and classification under it is classified relatively, if the characteristic image similarity of this individual images and a certain class (being assumed to be X) is the highest, can judge that so just this individual images belongs to the X class, each characteristic image of next stage with this individual images and X class mates respectively again, and calculate its similarity, find the affiliated classification (being assumed to be Y) of the maximum characteristic image of similarity, as the classification under this subject image; Can continue then to compare with the next stage characteristic image of Y, so analogize, reach the requirement of expection up to its similarity, as stipulating as required in the inventive method: similarity reaches 80% and gets final product for building.The characteristic image of the subclass of its final coupling and similarity maximum is with the twin image of this individual images so, and its actual image effect of drawing out will be closely similar with the object image of reality.
Second step: the part that will change is reconstructed in the digital city, comprises following each stage:
Phase one: according to variation monitoring to subject image make up corresponding object model, the taxonomic structure basically identical of the taxonomic structure of model bank and image library, as shown in Figure 9, an image in the image library is corresponding with a model in the model bank basically, but the static model that the model in the model bank can be to use the instrument of modeling to build up also can be to use the three-dimensional model of the real-time rendering when needed of parametric description.Dynamic model is than the easier correction of static model, and it is more real-time than using dynamic model to use static model, but that the authenticity of expressing is not passed through revised dynamic model is good.So the inventive method can be used static model earlier when generating the digital city automatically, replace previous static model with revised dynamic model gradually again.
Just because of model bank and image library are corresponding,, it can be mapped to model bank and have constructed the model of this object, as shown in figure 10 as long as utilize image library to identify the attribute of object in the phase one.
Subordinate phase: automatically the object model of variation monitoring correspondence is put in the heritable digital city.The process that object model in the remote sensing image is implanted in the heritable digital city again is as follows: when monitoring out the object of variation from remote sensing image, the inventive method has just been write down the two-dimensional coordinate (longitude and latitude) of this object in program, and the orientation on the different limit of this object.According to coordinate and the orientation of this subject image in remote sensing image, the inventive method just can be implanted its model true to nature that automatically generates by previous step in the heritable digital city towards, angle, position with correct.
The mode of putting into is divided into three kinds according to the difference of variation pattern, is the example explanation with the building: if by the contrast remote sensing image, find that the somewhere has more a building, this building will newly be promoted in the heritable digital city so; If by the contrast remote sensing image, the building of finding the somewhere has become the square or this building has uprised, this original building will remove from heritable digital city so, and square or the building that uprised are implanted; If by the contrast remote sensing image, a building has been lacked in the discovery somewhere, and this building will be removed from heritable digital city so.Real-time renewal can be finished in succession type of the present invention thus digital city.
Therefore, in the drawing process of the digital city in Shenzhen,, need the time in 3 years approximately, expensive about 3,000 ten thousand if generated S2006 according to the remote sensing images P2006 of Shenzhen modeling in 2006 again in 2006.And adopt the inventive method to generate S2006 according to the variation succession type ground of Shenzhen's remote sensing images between 2006 and 2000, only need the halfhour time, so can be done in real time the processing of digital city fully, the correct acquisition that only needs to guarantee remote sensing images gets final product.And the digital city S2006 that succession type generates has kept the tractability of digital city S2000.
Utilize the inventive method can be the city emergency commading system service, merge various remotely-sensed datas and generate the digital city automatically real-time, based on information such as the layout in real-time digital city, landform, roads, just can be in conjunction with meteorological measuring (wind-warm syndrome data) simcity wind field, the development trend of accidents such as dynamic similation air pollution diffusion, Real-time and Dynamic is shown to the city cammander realistically, and decision support is provided.
Utilize the inventive method can be city architecture against regulations Monitoring Service, merge various remotely-sensed datas and generate the digital city automatically real-time, just the different architectures against regulations can be found exactly with layout data and the person that is shown to the urban planning administration by the building in the comparative figures city.
Utilize the inventive method can also be used for a lot of other aspects, for example the resident can not go out the door and enjoy the service of aspects such as dummy market, Virtual Hospital, virtual theatre and virtual tourism; City emergency disaster relief commanding does not go out command post just can see best rescue route and field condition; The police need not go out the position that the police office just can navigate to the offender at once, monitors offender's every act and every move, and can determine the best route of arresting immediately; Planning department just can be seen all lands used and house without on-the-spot investigation, thereby makes the most rational decision-making; Vehicle supervision department need not stand in the traffic that just can see all roads on the road, thereby makes the most rational scheduling.
The digital city that the inventive method succession type digital city generation method can be applied to use any scheme to generate, and the object image that variation monitoring obtains changing also has other modes to substitute, and for example takes photo by plane; The three-dimensional model that generates object after the subject image that obtains changing also has other mode to substitute, for example more animation imagery of subject image in the digital city.Above-mentioned concrete image processing process comprises that it is known in the image technology for automatically treating of prior art that the knowledge base of remote sensing images is used, and therefore, repeats no more.
Should be understood that above-mentioned description at preferred embodiment of the present invention is comparatively detailed, can not therefore be interpreted as the restriction to scope of patent protection of the present invention, scope of patent protection of the present invention should be as the criterion with claims.
Claims (10)
1. the succession type of a digital city generates and real time updating method automatically, and it is applied to a general-purpose computing system, utilizes existing digital city and knowledge base, and may further comprise the steps:
A, obtain remote-sensing images in different times and carry out variation monitoring, generate a striograph that changes;
B, in the striograph that changes, carry out object identification, the object that identifies and the three-dimensional model in the knowledge base are mated;
C, the three-dimensional model that coupling is returned are implanted the correspondence position in the described digital city, generate the digital city of one time of back in real time.
2. method according to claim 1 is characterized in that, described steps A is further comprising the steps of:
A1, find the same place in the remote-sensing images in different times to extract automatically, comprise angle point, the extraction of flex point, road cross spider as the reference mark;
A2, based on the geometrical registration method of affined transformation model, seek the image same place earlier, bring the affined transformation model of foundation into, by repeatedly calculating optimum affine transformation parameter, according to optimum registration parameter input picture is carried out coordinate transform, obtain 2 o'clock phasors that mate substantially in the geographic position;
A3, did on the phasor at 2 o'clock the atural object level other relatively, the striograph Δ P that obtains changing.
3. method according to claim 2 is characterized in that, described steps A 2 also is included in a plurality of same places of rejecting the deviation maximum before each calculating.
4. method according to claim 1 is characterized in that the forming process of described knowledge base also is provided with an image library, and it comprises step:
D1, from remote sensing image, extract the representational image of various types of individualities, and will
These representational images are classified, and extract its general character, form first order characteristic image;
D2, in this rank, mark off subclass, and in all images of each subclass, extract general character respectively, give a characteristic image respectively for each subclass;
So analogize, up to its divide represented basically should the representational all kinds of individuality till.
5. method according to claim 4 is characterized in that, the taxonomic structure that a model bank is set is consistent with the taxonomic structure of described image library, and an image in the image library is corresponding with a model in the model bank.
6. method according to claim 5 is characterized in that, the static model that the model in the described model bank is to use the instrument of modeling to build up.
7. method according to claim 5 is characterized in that, the model in the described model bank is to use parametric description and the three-dimensional model of real-time rendering when needed.
8. method according to claim 5 is characterized in that, the mapping relations between described image library and the model bank may further comprise the steps:
D3, the object in the remote sensing image is extracted and discerns according to image library;
D4, the subclass of the object that extracts and the respective classes in the image library is carried out similarity relatively, and retrieve in the image library image with this object similarity maximum, and be mapped to corresponding model in the model bank;
D5, the individuality in the remote sensing image is carried out automatic modeling by knowledge base.
9. method according to claim 8 is characterized in that, described step D5 also comprises:
D51, remote sensing image is scanned, obtain the set of the object of each big class, judge the similarity between this object and these characteristic images according to the first order characteristic image in the image library;
D52, from image library, find out the accurate classification under this object.
10. method according to claim 9 is characterized in that, described step D52 comprises: D521, the characteristic image that the next stage of this subject image and classification under it is classified compare,
If the characteristic image similarity of this individual images and a certain class is the highest, then judge this individuality
Image belongs to such;
D522, this individual images and each characteristic image of such next stage are mated respectively, and calculate its similarity, find the classification under the maximum characteristic image of similarity, as the classification under this subject image;
So analogize, reach the expection requirement up to its similarity.
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