CN106157292A - Land resources variation monitorings based on two phase remote sensing images - Google Patents
Land resources variation monitorings based on two phase remote sensing images Download PDFInfo
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Abstract
The present invention is data based on the remote sensing images of two phases, by the Image semantic classification process such as geometrical registration, radiant correction, the difference image of two phases is combined with the ground object structure information in remote sensing images, the algorithm utilizing the present invention completes the variation monitoring to land resources, obtains region of variation the most clearly.Improve the gentle monitoring accuracy of Automated water of land resources change-detection, reduce the impact of subjective factors.Belong to spatial analysis applied technical field, provide preferable land and resource information change-detection means for the associated user such as the public, government.Land resources variation monitoring algorithms based on two phase remote sensing images have employed the method combined by the half-tone information of remote sensing image with texture information, having merged two kinds of characteristic informations and carried out the feature changes in comprehensive detection image, this is the effective way improving the change detecting method being based only on spectral signature.Also substantially increase accuracy and the objectivity of excursion detection, improve the automatization level of land resources change-detection.
Description
Technical field
The present invention is data based on the remote sensing images of two phases, by the Image semantic classification process such as geometrical registration, radiant correction, the difference image of two phases is combined with the ground object structure information in remote sensing images, the algorithm utilizing the present invention completes the variation monitoring to land resources, obtains region of variation the most clearly.Improve the gentle monitoring accuracy of Automated water of land resources change-detection, reduce the impact of subjective factors.Belong to spatial analysis applied technical field, provide preferable land and resource information change-detection means for the associated user such as the public, government.
Background technology
Along with the development of society with technology, all changing Landscape and utilizing form the various movable every day of the mankind, quickly increasing and the development of urbanization of population, accelerate the speed of this change.Therefore, rapidly and efficiently monitor these change informations, analyze feature and the reason of change and affect result, be of great significance for realizing the sustainable development tool of China.
In recent decades, along with the fast development of space technology, sensor technology, computer technology and related science thereof, remote sensing technology has obtained made rapid progress.Rising as one and the subject of extensive application prospect, remote sensing technology is up to the present to provide the only resource dynamically observing data of wide area, there is seriality spatially and temporal sequentiality, it is provided that carry out the multi-temporal image data of atural object perception and monitoring.Therefore, by analyzing the Multitemporal Remote Sensing Images in same geographical position, it is a kind of effective way obtaining land resources change information.
The process utilizing Multitemporal Remote Sensing Images to obtain feature changes information is referred to as change-detection, and it is a kind of data analysing method set up for the feature of remote sensing images, for identifying the state change of an object or phenomenon.Currently, change detection techniques has become as the focus in Remote Sensing Study, is widely used in the numerous areas of national economy and national defense construction.On civilian, it be mainly used in the change information such as Land use cover and change, forest and coupling relationship in resource and environment monitoring, wetland reserves, Urban Expansion, topographic change and obtain；And disaster surveillance and the assessment such as earthquake in natural disaster, flood, mud-rock flow and forest fire.
Although the change-detection research of remote sensing images has been obtained for the biggest development, but at present still in the exploratory stage, automatization level is the highest, it is often necessary to realize by the way of manual intervention.And along with Remote Sensing Information Extraction technology is in the improve of time, spatially and spectrally resolution, remote sensing image data amount has had huge increase, using artificial means too much will be a very heavy task to process these mass datas, the most sometimes be difficult to.Therefore in the urgent need to some automatization's change detection techniques, make it possible to by computer, the remote sensing images of same region difference phase are analyzed and are compared, obtain the information of feature changes.
Land resources variation monitoring algorithms based on two phase remote sensing images have employed the method combined by the half-tone information of remote sensing image with texture information, having merged two kinds of characteristic informations and carried out the feature changes in comprehensive detection image, this is the effective way improving the change detecting method being based only on spectral signature.Also substantially increase accuracy and the objectivity of excursion detection, improve the automatization level of land resources change-detection.
Applying for some, such as the change-detection room for important military region, the geography information of this region is the most not accurate enough, is even difficult to obtain.Meanwhile, the acquisition of remote sensing images becomes increasingly to facilitate so that the change-detection analyzing different phase remote sensing images becomes the Main Means obtaining such geographical diversity information.
Summary of the invention
For relevant departments and the specific industry urgency to land resources change-detection demand such as present stage land resources, the present invention proposes and a kind of combines the method for ground object structure information in gradation of image information and image.Based on the remote sensing image data of the same sensor areal of two phases, by the Image semantic classification means such as geometrical registration, radiant correction, obtain two good phase remote sensing images.By using this invention algorithm to realize Image Change Detection, region of variation is preferably extracted formation figure speckle；There is provided, for relevant departments such as land resources, the change-detection result that reliability is higher, assist government decision.
The technology path that the present invention uses is as follows:
Technology implementation route includes five parts altogether, is respectively as follows: geometrical registration, radiant correction, two phase remote sensing images difference, two phase Remote Sensing Image Textures extractions and difference, grey scale difference image and texture difference image information fusion.Concrete condition is as follows:
One, geometrical registration
Image registration is the basis of many graphical analyses, two width or several images of the same area are most preferably mapped on locus by it, these images or the different sensors from same phase, or the unified sensor from different phases, or the different sensors from different phases.
Actual the referring to of remote sensing image registration process finds the process that two width images map the most one to one, say, that be connected by the point that correspond to spatially same position in two width images.
Two, radiant correction
1. sensor calibration
2. atmospheric correction
3. altitude of the sun correction
4. topographical correction
Three, two phase remote sensing images difference
For most of atural objects, the difference of spectral characteristic is to judge its Main Basis changed, and technology based on spectral signature and method are based on this principle and realize the change-detection of atural object, and this kind of method is the most extensive in the application of current change-detection.During the i.e. image difference of image algebraic operation through frequently with the concrete technology of variation monitoring based on spectral signature and the approach of realization.
Image difference, generally refers to gradation of image difference, is a kind of change detecting method based on simple algebraically calculus of differences, can apply to multiple different geographical environment and image type.During image difference on probation, firstly the need of the difference according to object spectrum value corresponding in phase images during difference, generate difference image by calculus of differences, then select suitable thresholding to separate the part that gray value is big in difference image, represent the region changed on ground with this.
Change detecting method based on image difference, the grey scale difference image mainly changed by analyzing reflection object spectrum value realizes change-detection.It is effective in most of the cases analyzing grey scale difference image, but, under certain conditions, it is difficult to the change-detection of atural object just with the grey scale difference image of the spectral signature of atural object.
Four, two phase Remote Sensing Image Textures extract and difference
Remote sensing images are ground target spectrum on image and the concentrated expression of geometric properties, in some cases, change detecting method based on SPECTRAL DIVERSITY can not well distinguish the difference of atural object, at this moment uses method based on space characteristics to there may be more preferable effect.Meanwhile, the man-made target in high-resolution remote sensing image, architectural feature is the main forms of target property, and the easy combining target model of description based on spatial structure characteristic, high layer analysis of being more convenient for.
Therefore, by the spatial structure characteristic of target in com-parison and analysis difference phase remote sensing images, in man-made target change-detection analysis, there is clear advantage, be a direction of variation monitoring development.
Five, grey scale difference image and texture difference image information fusion
The change-detection merged based on difference image is to combine grey scale difference image with texture difference image to be changed the processing method of region detection, main handling process is: after input Multitemporal Remote Sensing Images, first passes through image registration and realizes geometry and the radiant correction of different phase remote sensing images with relative radiometric correction method；Then texture difference image and grey scale difference image are merged according to Bayes principle；The preliminary classification after difference image merges is realized then according to maximum likelihood function；Realize the classification after merging finally by a kind of adaptive parameter estimation, obtain region of variation.
Technology path scheme schematic diagram is as shown in Figure 1.
The flow process of this change detection algorithm is described as follows: after input Multitemporal Remote Sensing Images, first passes through image registration and realizes geometry and the radiant correction of different phase remote sensing images with relative radiometric correction method；Image after correction is carried out grey scale difference and texture blending, difference respectively；Obtain two kinds of result datas are used this algorithm, then obtains changing graphic.
The technical difficult points of land resources variation monitorings based on remote sensing images is: being combined with texture image by the grey scale difference image obtained obtains changing graphic.This algorithm merges texture difference image and grey scale difference image according to Bayes principle；The preliminary classification after difference image merges is realized then according to maximum likelihood function；Realize the classification after merging finally by a kind of adaptive parameter estimation, obtain region of variation..
Accompanying drawing explanation
Fig. 1 is land resources variation monitoring technical scheme route maps based on two phase remote sensing images；
Fig. 2 is remotely sensing image geometric correction schematic flow sheet；
Detailed description of the invention
One, geometrical registration
Image geometry registration is exactly the image to the areal that different time, different-waveband, different sensors system are obtained, set up its mutual corresponding relation, determine corresponding geometric transformation parameter, the method that a width in two width images is carried out geometric transformation, i.e. realizes the registration of two width image pixels of the same name.
Geometry multinomial model is the DEM information that a two-dimensional coordinate conversion process, i.e. trimming process need not image.When the degree of polynomial is 1, equivalent model is in affine transformation, and this is suitable for when landform is smooth, and the deformation between image may be considered translation, rotates and scale.The multinomial model of relatively high order can be selected when data set exists serious geometric error, in theory, polynomial number of times is the highest, is just originally inputted the deserved parameter of geometric error of image closer to simulation, and is placed on by pixel after the correction of correspondence on the correct plan-position of image output.High-order moment usually can region around accurately matching ground control point, but, other geometric error may be introduced in the region away from GCP.Further, since need to carry out a large amount of mathematical operation, when using high-order moment that remote sensing image is carried out geometric correction, required operation time is longer.Usual 2 order polynomial corrections can reach more satisfactory correction result.
A kind of mathematical relationship is found in the correction of geometry multinomial between raw video and reference image, sets up the functional relationship between image coordinate and its ground corresponding image points map reference before converting.
Generally f is binary polynomial of degree n, and polynomial item number (i.e. coefficient number) N and its exponent number n has a fixing relation:
Each control point formed two equations, as different rank correction required by minimum control point number different, typically require multiselect some.The most polynomial coefficient can solve according to the principle of least square, and precision is higher.Geometry polynomial method calculates simple, the method is all blanket to the correction of all kinds sensor, and the method is applied not only to image and corrects the system of ground (or map), the mutual geometrical registration being also commonly used between dissimilar image, to meet the needs that image mosaic, image change detection etc. process.
Two, radiant correction
1. mark and draw knowledget opic classification
2. multiscale space plotted data self-organizing model
The expression characteristic self being had based on multiscale space plotted data, in conjunction with framing tissue, subregional organization, sub-element tissue and the mixing multiple aspect of key element tissue, division from plane and vertical space enterprising row data, at many levels, multi-angle sets up the multi-level representation of space plotted data, set up the multiscale space index of the level correlation rule towards the whole world, it is achieved the self-organizing of multiscale space plotted data.
3. mark and draw the automatic/semi-automatic integration of content
4. geographical information visualization service and map dynamic publishing
Set up R+ tree index by marking and drawing and mark and draw region, realize real-time positioning and the extraction of plotted data；Visualization issue and the entity expression agreement of plotted data is set up based on XML specification；Use Web Service technology, the visualization setting up plotted data and data service system.
Three, two phase remote sensing images grey scale difference
When using image difference, firstly the need of the difference according to object spectrum value corresponding in phase images during difference, generate difference image by calculus of differences, then select suitable thresholding to separate the part that gray value is big in difference image, represent the region changed on ground with this.
Change detecting method based on image difference, the grey scale difference image mainly changed by analyzing reflection object spectrum value realizes change-detection.It is effective in most of the cases analyzing grey scale difference image, but, under certain conditions, it is difficult to the change-detection of atural object just with the grey scale difference image of the spectral signature of atural object.
Four, two phase Remote Sensing Image Textures extract and difference
Remote sensing images are ground target spectrum on image and the concentrated expression of geometric properties, in some cases, change detecting method based on SPECTRAL DIVERSITY can not well distinguish the difference of atural object, at this moment uses method based on space characteristics to there may be more preferable effect.Meanwhile, the man-made target in high-resolution remote sensing image, architectural feature is the main forms of target property, and the easy combining target model of description based on spatial structure characteristic, high layer analysis of being more convenient for.
Therefore, by the spatial structure characteristic of target in com-parison and analysis difference phase remote sensing images, in man-made target change-detection analysis, there is clear advantage.
Five, grey scale difference image and texture difference image information fusion
The change-detection merged based on difference image is to combine grey scale difference image with texture difference image to be changed the processing method of region detection, main handling process is: after input Multitemporal Remote Sensing Images, first passes through image registration and realizes geometry and the radiant correction of different phase remote sensing images with relative radiometric correction method；Then texture difference image and grey scale difference image are merged according to Bayes principle；The preliminary classification after difference image merges is realized then according to maximum likelihood function；Realize the classification after merging finally by a kind of adaptive parameter estimation, obtain region of variation.
Claims (1)
1. land resources variation monitoring algorithms based on two phase remote sensing images, its feature includes:
1. spatial knowledge service system constructing technology flow process based on Collaborative Plotting technology: by the Image semantic classification mistake such as geometrical registration, radiant correction
Journey, combines the difference image of two phases with the ground object structure information in remote sensing images, merges texture difference image and gray scale according to Bayes principle
Difference image；The preliminary classification after difference image merges is realized then according to maximum likelihood function；Realize finally by a kind of adaptive parameter estimation
Classification after fusion, obtains region of variation.Preferable land and resource information change-detection means are provided for the associated user such as the public, government.
2. concrete technology path: the present invention extracts from geometrical registration, radiant correction, two phase remote sensing images difference, two phase Remote Sensing Image Textures
Launch successively to be described, wherein with texture difference image information fusion with difference, grey scale difference image: 1. Multitemporal Remote Sensing Images geometrical registration,
Image geometry registration exactly image to the areal that different time, different-waveband, different sensors system are obtained, sets up it mutual right
Should be related to, determine corresponding geometric transformation parameter that the method that the width in two width images is carried out geometric transformation i.e. realizes two width image pixels of the same name
Registration.2. radiant correction, the purpose that image carries out radiant correction is that elimination air, solar incident angle, visual angle and landform etc. are anti-to ground spectrum
Penetrate the image of signal.The ultimate principle of Multitemporal Remote Sensing Images relative detector calibration is the radiation value by adjusting image to be corrected, is that identical atural object exists
Time different, the spectral reflectance value in phase images is equal, namely " wave spectrum is constant ".3. two phase image difference, is a kind of based on simple algebraically difference
The change detecting method of computing, can apply to multiple different geographical environment and image type.When using image difference, it is necessary first to according to difference
Time phase images in the difference of corresponding object spectrum value, generate difference image by calculus of differences.4. two phase Remote Sensing Image Textures extract and difference
Containing many information of atural object in remote sensing images, in addition to the intensity profile of reflection object spectrum reflected value, the space structure that further comprises atural object is special
Levy such as texture, and these changing features are likely to characterize the change of atural object；This algorithm make use of texture difference image to characterize the change of atural object.5. ash
Degree difference image and texture difference image information fusion, merge texture difference image and grey scale difference image according to Bayes principle；Then according to maximum
Likelihood function realizes the preliminary classification after difference image merges；Realize the classification after merging finally by a kind of adaptive parameter estimation, changed
Region.
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| CN109934788A (en) * | 2019-03-22 | 2019-06-25 | 鲁东大学 | A kind of remote sensing images missing data restorative procedure based on standard remote sensing images |
| CN112906659A (en) * | 2021-03-31 | 2021-06-04 | 夏程巧 | Remote sensing image change detection method based on virtual sample |
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| CN113554011A (en) * | 2021-09-22 | 2021-10-26 | 航天宏图信息技术股份有限公司 | Method, device and equipment for detecting change of remote sensing image and storage medium |
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| CN114066732A (en) * | 2021-11-21 | 2022-02-18 | 特斯联科技集团有限公司 | Visible light image geometric radiation splicing processing method of multi-source monitor |
| CN114066732B (en) * | 2021-11-21 | 2022-05-24 | 特斯联科技集团有限公司 | Visible light image geometric radiation splicing processing method of multi-source monitor |
| CN114120141A (en) * | 2021-11-23 | 2022-03-01 | 深圳航天智慧城市系统技术研究院有限公司 | All-weather remote sensing monitoring automatic analysis method and system thereof |
| CN114627087A (en) * | 2022-03-21 | 2022-06-14 | 国网江苏省电力有限公司无锡供电分公司 | Method and system for automatically detecting ground object change of multi-temporal satellite remote sensing image |
| CN114627087B (en) * | 2022-03-21 | 2024-04-12 | 国网江苏省电力有限公司无锡供电分公司 | Automatic detection method and system for ground feature change of multi-temporal satellite remote sensing image |
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