CN103576165A - Intelligent satellite earth observation pattern base acquiring method and system - Google Patents
Intelligent satellite earth observation pattern base acquiring method and system Download PDFInfo
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Abstract
The invention provides an intelligent satellite earth observation pattern base acquiring method and system. The intelligent satellite earth observation pattern base acquiring method includes the steps that each kind of single ground feature scene is subject to satellite imaging analog simulation experiments, ground feature characteristics are analyzed, and observation pattern parameters of each kind of single ground feature scene are selected; satellite imaging analog simulation experiments of multiple ground feature scenes are carried out, coupling relations of observation pattern parameters of the multiple ground feature scenes are analyzed, and the observation pattern parameters of the multiple ground earth scenes are selected; an intelligent satellite earth observation pattern base is built according to the selected observation pattern parameters of each kind of single ground feature scene and the selected observation parameters of the multiple ground earth scenes. Due to the adoption of the intelligent satellite earth observation pattern base acquiring method and system, observation pattern parameters of all kinds of scenes can be selected through imaging analog simulation experiments of single ground feature scenes and imaging analog simulation experiments of multiple scenes to build the complete intelligent satellite earth observation pattern base for targeted actual intelligent satellite earth observation selection. The intelligent satellite earth observation pattern base acquiring method and system have wide application value.
Description
Technical field
The present invention relates to remote sensing and earth observation technical field, relate in particular to a kind of satellite intelligence earth observation pattern base acquisition methods and system.
Background technology
Earth observation is to take the earth as object of observation, rely on the space platforms such as satellite, airship, space shuttle, aircraft and Near Space Flying Vehicles, utilize the multiple detection means such as visible ray, infrared, high spectrum and microwave, the process of product is processed and formed to obtaining information also.The common formation earth observation systems such as corresponding carrying platform, detection means, processing and application apparatus.Earth observation systems, can be divided into space-based, space base and near space three major types according to the difference in carrying platform spatial domain of living in; According to purposes difference, can be divided into military systems, civilian system, business system.
At present, the intelligent selection of the best of breeds such as satellite intelligence multimodal time shutter of earth observation, gain is had to certain progress abroad.Compact high-resolution image spectrometer (the Compact High Resolution Imaging Spectrometer that the PROBA moonlet of European Space Agency's transmitting carries, CHRIS) can within 2.5 minutes, obtain the high spectrum image (55 ° ,-36 °, 0 °, 36 °, 55 °) of 5 angles, and can, according to different observed objects and application demands such as water body, vegetation and land, realize the conversion of 2 kinds of different spaces and spectral resolution imaging pattern.It can obtain 62 wave bands, 34m spatial resolution image at 411-997nm spectral coverage, also can, for the needs of water quality remote sensing, imaging pattern be changed into the Hyperspectral imaging that obtains 18 wave bands, 17m spatial resolution at 411-1019nm spectral coverage.In China, the HY-1 oceanographic satellite has used intelligent network control technology at home first, and useful load configuration Hai Lu takes into account, and has obvious innovation; At the HXMT grinding (hard X-ray Modulation Telescope) astronomical satellite, be first astronomical satellite of China's independent research at present, can realize the Based Intelligent Control to celestial sphere scan task; The Recorder for Space Solar Telescope that State Astronomical Observatory, CAS conducts a research can adopt different observation modes according to solar activity state, and carries out data processing on star adaptively, has certain intelligent observing capacity.
But, above-mentioned intelligent earth observation technology is the elementary step in exploring still, on the Satellite of having launched at present, intelligence observes all comparatively simple with processing, lacks a set of complete satellite intelligence earth observation pattern base acquisition methods and system, to instruct the setting of intelligent satellite load imaging parameters.
Summary of the invention
(1) technical matters that will solve
The invention provides a kind of satellite intelligence earth observation pattern base acquisition methods and system, to solve the technical matters that lacks a set of complete satellite intelligence earth observation pattern base acquisition methods and system in prior art.
(2) technical scheme
For solving the problems of the technologies described above, the invention provides a kind of satellite intelligence earth observation storehouse pattern acquisition methods, comprising:
Each single atural object scene is carried out to the experiment of satellite imagery analog simulation, analyze atural object characteristic, select the observation mode parameter of each single atural object scene;
Carry out the satellite imagery analog simulation experiment of many atural object scene, the observation mode parameter coupled relation of many atural object scene is analyzed, select the observation mode parameter of many atural object scene;
According to the observation mode parameter of selected each single atural object scene and many atural object scene, build satellite intelligence earth observation pattern base.
Further,
Described to each single atural object scene carry out also comprising before the experiment of satellite imagery analog simulation: study the curve of spectrum feature of each single atural object scene imaging, build background knowledge storehouse;
Describedly each single atural object scene is carried out to satellite imagery analog simulation experiment comprise: in conjunction with described background knowledge storehouse, the time shutter of specialized aviation remote sensing camera, gain are controlled, realized the imaging to described each single atural object scene;
Described analysis atural object characteristic, select the observation mode parameter of each single atural object scene to comprise: the imaging results to each single atural object scene is comprehensively analyzed, assessment signal to noise ratio (S/N ratio), the relation of research time shutter and gain, selection makes imaging results reach the observation mode parameter of optimum signal-noise ratio and information entropy, comprises the one or more parameters in the ratio of time shutter, gain and time shutter and gain;
The described satellite imagery analog simulation experiment of carrying out many atural object scene comprises: the time shutter of specialized aviation remote sensing camera, gain are controlled, realized the imaging to described many atural object scene;
The described observation mode parameter coupled relation to many atural object scene is analyzed, select the observation mode parameter of many atural object scene to comprise: the imaging results to many atural object scene is comprehensively analyzed, assessment signal to noise ratio (S/N ratio), the relation of research time shutter and gain, selection makes imaging results reach the observation mode parameter of many atural object scene of optimum signal-noise ratio and information entropy, comprises the one or more parameters in the ratio of time shutter, gain and time shutter and gain.
Further,
Described signal to noise ratio (S/N ratio) is: for the ratio of key diagram picture effective information and noise:
SNR=LSD
maxLSD
min
Wherein SNR is signal to noise ratio (S/N ratio), LSD
maxfor add make an uproar after the maximal value of all pixel local variances in image, LSD
minfor add make an uproar after the minimum value of all pixel local variances in image;
Described information entropy is: the quantity of information having for key diagram picture:
Wherein, EN is information entropy, p
iprobability while being i for grey scale pixel value in image, the maximum gradation value that n is image.
Further,
Described single atural object scene comprises: the one or more atural object scenes in vegetation, soil, water body, rock and man-made features;
Described many atural object scene comprises: the vegetation-soil of combination of two, vegetation-water body, vegetation-rock, vegetation-man-made features, soil-water body, soil-man-made features, water body-rock, water body-man-made features; Vegetation-soil-the water body of three kinds of combinations, vegetation-soil-rock, vegetation-soil-man-made features, vegetation-water body-rock, vegetation-water body-man-made features, soil-water body-man-made features; One or more many atural object scenes in the vegetation-soil-water body-man-made features of multiple combination.
Further, described method also comprises: according to described satellite intelligence earth observation pattern base, one or more influence factors in judging in conjunction with task priority, environmental baseline, earth object, the association of comprehensive analysis image-forming condition and impact, determine optimal imaging pattern, select optimum exposure time and gain earth observation imaging in satellite intelligence earth observation pattern base.
On the other hand, the present invention also provides a kind of satellite intelligence earth observation pattern base to obtain system, it is characterized in that, comprising: the single atural object image-generating unit, many atural object image-generating unit and the pattern base construction unit that are linked in sequence, wherein:
Single atural object image-generating unit, for each single atural object scene is carried out to the experiment of satellite imagery analog simulation, analyzes atural object characteristic, selects the observation mode parameter of each single atural object scene;
Many atural object image-generating unit, for carrying out the satellite imagery analog simulation experiment of many atural object scene, analyzes the observation mode parameter coupled relation of many atural object scene, selects the observation mode parameter of many atural object scene;
Pattern base construction unit, for according to the observation mode parameter of selected each single atural object scene and many atural object scene, builds satellite intelligence earth observation pattern base.
Further,
Described system also comprises: context vault construction unit, be connected with described single atural object image-generating unit, and for studying the curve of spectrum feature of each single atural object scene imaging, build background knowledge storehouse;
Described single atural object image-generating unit comprises: the first imaging subelement, in conjunction with described background knowledge storehouse, the time shutter of specialized aviation remote sensing camera, gain are controlled, and realize the imaging to described each single atural object scene; The first parameter chooser unit, for the imaging results of each single atural object scene is comprehensively analyzed, assessment signal to noise ratio (S/N ratio), the relation of research time shutter and gain, selection makes imaging results reach the observation mode parameter of optimum signal-noise ratio and information entropy, comprises the one or more parameters in the ratio of time shutter, gain and time shutter and gain;
Described many atural object image-generating unit comprises: the second imaging subelement, for the time shutter of specialized aviation remote sensing camera, gain are controlled, realize the imaging to described many atural object scene; The second parameter chooser unit, for the imaging results of many atural object scene is comprehensively analyzed, assessment signal to noise ratio (S/N ratio), the relation of research time shutter and gain, selection makes imaging results reach the observation mode parameter of many atural object scene of optimum signal-noise ratio and information entropy, comprises the one or more parameters in the ratio of time shutter, gain and time shutter and gain.
Further,
Described the first parameter chooser unit comprises: the first signal to noise ratio (S/N ratio) module; Described the second parameter chooser unit comprises: the second signal to noise ratio (S/N ratio) module; Described the first signal to noise ratio (S/N ratio) module and described the second signal to noise ratio (S/N ratio) module are used for utilizing following formula to be calculated to be picture signal to noise ratio (S/N ratio):
SNR=LSD
maxLSD
min
Wherein SNR is signal to noise ratio (S/N ratio), LSD
maxfor add make an uproar after the maximal value of all pixel local variances in image, LSD
minfor add make an uproar after the minimum value of all pixel local variances in image;
Described the first parameter chooser unit comprises: first information entropy module; Described the second parameter chooser unit comprises: the second information entropy module; Described first information entropy module and described the second information entropy module are used for utilizing following formula to be calculated to be picture information entropy:
Wherein, EN is information entropy, p
iprobability while being i for grey scale pixel value in image, the maximum gradation value that n is image.
Further,
Described single atural object scene comprises: the one or more atural object scenes in vegetation, soil, water body, rock and man-made features;
Described many atural object scene comprises: the vegetation-soil of combination of two, vegetation-water body, vegetation-rock, vegetation-man-made features, soil-water body, soil-man-made features, water body-rock, water body-man-made features; Vegetation-soil-the water body of three kinds of combinations, vegetation-soil-rock, vegetation-soil-man-made features, vegetation-water body-rock, vegetation-water body-man-made features, soil-water body-man-made features; One or more many atural object scenes in the vegetation-soil-water body-man-made features of multiple combination.
Further, described system also comprises:
Image-generating unit, be connected with described pattern base construction unit, be used for according to described satellite intelligence earth observation pattern base, one or more influence factors in judging in conjunction with task priority, environmental baseline, earth object, the association of comprehensive analysis image-forming condition and impact, determine optimal imaging pattern, select optimum exposure time and gain earth observation imaging in satellite intelligence earth observation pattern base.
(3) beneficial effect
Visible, in satellite intelligence earth observation pattern base acquisition methods provided by the invention and system, can test by the single atural object scene in ground and many scene imagings analog simulation, select the observation mode parameter under various scenes, build complete satellite intelligence earth observation pattern base, during for the earth observation of real satellite intelligence, select targetedly, be with a wide range of applications.
The present invention has comprehensively analyzed the imaging effect under various scenes, from signal to noise ratio (S/N ratio) and information entropy angle, carry out image imaging effect analysis, the setting of the parameters such as research time shutter and gain, for the observation mode parameter setting under several scenes has given quantitative parameter recommendation, qualitative results more in the past has increased significantly.
Accompanying drawing explanation
In order to be illustrated more clearly in the embodiment of the present invention or technical scheme of the prior art, to the accompanying drawing of required use in embodiment or description of the Prior Art be briefly described below, apparently, accompanying drawing in the following describes is some embodiments of the present invention, for those of ordinary skills, do not paying under the prerequisite of creative work, can also obtain according to these accompanying drawings other accompanying drawing.
Fig. 1 is the basic procedure schematic diagram of embodiment of the present invention satellite intelligence earth observation pattern base acquisition methods;
Fig. 2 is the schematic flow sheet of a preferred embodiment of the invention satellite intelligence earth observation pattern base acquisition methods;
Five kinds of object spectrum result figure of point measurement when Fig. 3 is embodiment of the present invention background extraction knowledge base;
Fig. 4 is the basic structure schematic diagram that embodiment of the present invention satellite intelligence earth observation pattern base obtains system;
Fig. 5 is that a preferred embodiment of the invention satellite intelligence earth observation pattern base obtains system architecture schematic diagram.
Embodiment
For making object, technical scheme and the advantage of the embodiment of the present invention clearer, below in conjunction with the accompanying drawing in the embodiment of the present invention, technical scheme in the embodiment of the present invention is clearly and completely described, obviously, described embodiment is the present invention's part embodiment, rather than whole embodiment.Embodiment based in the present invention, those of ordinary skills, not making the every other embodiment obtaining under creative work prerequisite, belong to the scope of protection of the invention.
First the embodiment of the present invention provides a kind of satellite intelligence earth observation pattern base acquisition methods, referring to Fig. 1, comprising:
Step 101: each single atural object scene is carried out to the experiment of satellite imagery analog simulation, analyze atural object characteristic, select the observation mode parameter of each single atural object scene.
Step 102: carry out the satellite imagery analog simulation experiment of many atural object scene, the observation mode parameter coupled relation of many atural object scene is analyzed, select the observation mode parameter of many atural object scene.
Step 103: according to the observation mode parameter of selected each single atural object scene and many atural object scene, build satellite intelligence earth observation pattern base.
Visible, in the satellite intelligence earth observation pattern base acquisition methods providing in the embodiment of the present invention, can test by the single atural object scene in ground and many scene imagings analog simulation, select the observation mode parameter under various scenes, build complete satellite intelligence earth observation pattern base, during for the earth observation of real satellite intelligence, select targetedly, be with a wide range of applications.
In one embodiment of the invention, in order to obtain better imaging effect, preferably, before to each, single atural object scene is carried out the experiment of satellite imagery analog simulation, can also comprise: study the curve of spectrum feature of each single atural object scene imaging, build background knowledge storehouse.Wherein, can utilize the method for the single atural object scene of point measurement, obtain reflectance spectrum curve.
In another embodiment of the present invention, preferably, each single atural object scene is carried out to the experiment of satellite imagery analog simulation can be comprised: in conjunction with above-mentioned background knowledge base, the time shutter of specialized aviation remote sensing camera, gain are controlled, realized the imaging to each single atural object scene.
In one embodiment of the invention, need to analyze the atural object characteristic of each single atural object scene, thereby obtain the observation mode parameter of each single atural object scene, preferably, can comprehensively analyze to the imaging results of each single atural object scene assessment signal to noise ratio (S/N ratio), the relation of research time shutter and gain, selection makes imaging results reach optimum signal-noise ratio and information entropy, comprises the observation mode parameter of the ratio etc. of time shutter, gain and time shutter and gain.
In another embodiment of the present invention, preferably, when the satellite imagery analog simulation experiment of carrying out many atural object scene, can control the time shutter of specialized aviation remote sensing camera, gain, realize the imaging to many atural object scene.
In one embodiment of the invention, can also analyze at the observation mode parameter coupled relation to many atural object scene, while selecting the observation mode parameter of many atural object scene, preferably, imaging results to many atural object scene is comprehensively analyzed, assessment signal to noise ratio (S/N ratio), the relation of research time shutter and gain, selection makes imaging results reach optimum signal-noise ratio and information entropy, comprises the observation mode parameter of many atural object scene of the ratio etc. of time shutter, gain and time shutter and gain.
In one embodiment of the invention, can utilize signal to noise ratio (S/N ratio) and information entropy to be used as picture appraisal index.Wherein, signal to noise ratio (S/N ratio) is used for the ratio of key diagram picture effective information and noise:
SNR=LSD
maxLSD
min
Signal to noise ratio (S/N ratio) is larger, and picture quality is better, and too much noise can be covered the information that image provides.At present, for signal noise ratio (snr) of image, calculate and there is no unified definition and algorithm, preferably, the embodiment of the present invention is selected a kind of approximation method, with signal and the ratio of the variance of noise, replace power spectrum to carry out the signal to noise ratio (S/N ratio) of approximate estimation image, use the maximal value LSD that adds the local variance of all pixels in the image after making an uproar
maxwith its minimum value LSD
minratio estimate signal to noise ratio (S/N ratio).
Information entropy is the quantity of information having for key diagram picture:
Wherein, p
iprobability while being i for grey scale pixel value in image, the maximum gradation value that n is image.The value of EN is larger, shows that the information that image contains is abundanter, and the spatial detail expressive ability of image is just stronger.
In another embodiment of the present invention, formed observation mode storehouse can comprise the observation mode storehouse of single atural object scene and many atural object scene.Wherein, preferably, single atural object scene can comprise: the scenes such as vegetation, soil, water body, rock and man-made features.Many atural object scene can comprise vegetation-soil, vegetation-water body, vegetation-rock, vegetation-man-made features, soil-water body, soil-man-made features, water body-rock, the water body-man-made features of combination of two; Vegetation-soil-the water body of three kinds of combinations, vegetation-soil-rock, vegetation-soil-man-made features, vegetation-water body-rock, vegetation-water body-man-made features, soil-water body-man-made features; A plurality of many atural object scenes such as the vegetation-soil-water body-man-made features of multiple combination.
In one embodiment of the invention, can utilize resulting satellite intelligence earth observation pattern base to carry out earth observation imaging, preferably, can be according to initial conditions such as earth observation imaging task parameter, earth observation imaging circumstances parameter, earth observation imaging type of ground objects parameters, carry out task priority, environmental baseline, earth object judgement, in conjunction with other influences factor, the association of comprehensive analysis image-forming condition and impact, determine optimal imaging pattern, provide best total of points time and gain adjustment.
The specific implementation method of obtaining satellite intelligence earth observation pattern base of take is below example, describes the implementation process of one embodiment of the invention in detail, as shown in Figure 2:
Step 201: study the curve of spectrum feature of each single atural object scene imaging, build background knowledge storehouse.
The present embodiment relates to five kinds of types of ground objects, is respectively vegetation, soil, water body, rock and man-made features.
Green vegetation has obvious reflectance spectrum feature.In visible light wave range, various pigments are principal elements of domination plant spectral response; At near-infrared band, the spectral characteristic of vegetation is mainly subject to the in-built control of plant leaf, and reflectivity is high, and transmitance is high, and absorptivity is low, and near about 0.76 μ m, reflectivity sharply rises, and forms " cliffy summit "; In middle-infrared band, green plants spectral response is mainly by 1.4 μ m, and near the strong absorption band of the water 1.9 μ m and 2.7 μ m is arranged.
Under state of nature, the reflectivity of soil surface does not have obvious peak value and valley.The reflection spectrum characteristic of soil is mainly subject to the impact of the factors such as primary mineral in soil and secondary mineral, soil water content, the soil organism, iron content, the soil texture.
The spectral signature of water mainly forms decision by the material of water itself, is subject to again the impact of various water states simultaneously.The purer natural water in earth's surface to the electro-magnetic wave absorption of 0.4~2.5 mu m waveband apparently higher than most other atural object.In the visible light wave range of spectrum, energy-matter interaction more complicated in water body, spectral reflection characteristic sums up with feature once: spectral reflection characteristic may comprise the contribution from three aspects:: the reflection of suspended material in the reflection of the surface reflection of water, water bottom material and water; Spectral absorption is not only relevant with the character of water body itself with transmissison characteristic, but also is subject to significantly all kinds and big or small material---the impact of organism and inorganics in water; In near infrared and the middle-infrared band of spectrum, water has almost absorbed its whole energy, and pure natural water is similar to one " black matrix " at near-infrared band, therefore, at 1.1~2.5 mu m wavebands, the reflectivity of purer natural water is very low, almost levels off to zero.
Rock reflectance spectrum curve has obvious similar features unlike vegetation, and its tracing pattern and mineralogical composition, mineral content, rate of decay, water status, grain size, smooth surface degree, color and luster etc. have relation.
Man-made features be take concrete floor as main, reflectance spectrum curve rising between 0.4~0.6um, after tend towards stability, to 0.9~1.1um place, decline gradually.
Atural object hyperspectral measurement adopts OCEAN OPTICS spectrometer.Fig. 3 is five kinds of object spectrum results of point measurement.In figure, indicate respectively vegetation spectrum, soil spectrum, water body spectrum, green Rock Spectrum and man-made features spectrum.
Step 202: each single atural object scene is carried out to the experiment of satellite imagery analog simulation, analyze atural object characteristic, select the observation mode parameter of each single atural object scene.
In the embodiment of the present invention, adopted and flown to think P65+ camera.Fly to think the novel C CD photo-sensitive cell of the imageing sensor Shi Feisiyu DALSA semiconductor company cooperative development that P65+ adopts, its valid pixel number reaches 6,000 ten thousand (8984 * 6732), photosensitive unit area reaches 6 * 6um, and light sensitivity is ISO50-800, and dynamic range reaches 12.5EV.The photo-sensitive cell size that flies to think Phase One P65+ reaches 40.4 * 54.9mm, larger 20% than 120 general DIGITAL-MODUL-Rs, has the title of the real silent frame of global First 645 specification photo-sensitive cells, and its major parameter list is in Table 1.
Table 1 flies to think the list of P65+ major parameter
In this step, in conjunction with the background knowledge storehouse of above-mentioned five kinds of atural objects, to flying to think time shutter, the gain of P65+ camera, control, realize the imaging to each single atural object scene, then select most suitable observation mode parameter.
Wherein, can utilize signal to noise ratio (S/N ratio) and information entropy to be used as picture appraisal index.Signal to noise ratio (S/N ratio) is used for the ratio of key diagram picture effective information and noise:
SNR=LSD
maxLSD
min
Signal to noise ratio (S/N ratio) is larger, and picture quality is better, and too much noise can be covered the information that image provides.At present, for signal noise ratio (snr) of image, calculate and there is no unified definition and algorithm, preferably, the embodiment of the present invention is selected a kind of approximation method, with signal and the ratio of the variance of noise, replace power spectrum to carry out the signal to noise ratio (S/N ratio) of approximate estimation image, use the maximal value LSD that adds the local variance of all pixels in the image after making an uproar
maxwith its minimum value LSD
minratio estimate signal to noise ratio (S/N ratio).
Information entropy is the quantity of information having for key diagram picture:
Wherein, p
iprobability while being i for grey scale pixel value in image, the maximum gradation value that n is image.The value of EN is larger, shows that the information that image contains is abundanter, and the spatial detail expressive ability of image is just stronger.
Observation mode parameter can be time shutter and signal gain, and the time shutter refers to from shutter and is opened to the time that imaging system between shutter close can receive scene illumination.Under identical scene light intensity and identical luminous flux (being also identical f-number), the time shutter is longer, and the luminous energy that photo-sensitive cell can receive is more, and image is also brighter, otherwise image is darker.For imaging on star, because imaging platform has motion at a high speed with respect to photographed scene, the time shutter is long also can bring motion blur to image.In order to obtain clear bright image, not only to carry out motion compensation to shooting process, also need the time shutter to carry out strict control, set up the funtcional relationship of image quality evaluation and time shutter, according to actual photographed condition, adjust in real time time shutter and imaging pattern, thereby reach best imaging effect.
Signal gain refers to the amplifier gain of analog picture signal this section of electric signal before reaching ADC Collect conversion of being exported by sensitive chip.Generally include the gain of fixed gain amplifier and the gain of variable gain amplifier.When shooting environmental is during in low irradiance, utilize the amplification characteristic of amplifier that useful signal is amplified, thus the sensitivity of expansion imaging system.But because amplifier amplifies noise in the lump when amplifying useful signal, so the noise in image is also just more.In order to increase the intensity of signal, suppress system noise simultaneously, need to effectively study according to the feature of system, thereby determine suitable gain coefficient.
Point results of spectral measurements by Fig. 3 can find out, the reflectivity of water body and vegetation is relatively low, therefore the in the situation that of certain signal to noise ratio (S/N ratio) and identical light sensitivity (ISO), obtains the time shutter that the image of vegetation and water body need to be relatively long; The reflectivity of soil, rock and 3 kinds of atural objects of man-made features is basically identical, and therefore obtaining these three kinds of atural object impacts needs basically identical ISO and shutter ratio.
Step 203: carry out the satellite imagery analog simulation experiment of many atural object scene, the observation mode parameter coupled relation of many atural object scene is analyzed, select the observation mode parameter of many atural object scene.
In this step, first determine test block, test block atural object need comprise vegetation, soil, water body, rock and the five kinds of atural objects of man-made features that will observe, and is evenly distributed, and is convenient to combined experiments.Select suitable shooting camera, requirement can fixed aperture situation under, by manual adjustments ISO, automatically select shutter value.
This experiment adopts and flies to think P65+ slr camera, is set to aperture priority gear, and fixed aperture is 6.4.Camera is fixed on elongation type tripod, and the about 2m of ground clearance, takes the atural object scope of about 1m2 size.It is 100,200,400,800,1600 that ISO is set respectively ..., until reach the higher limit of camera shutter.This tests camera shutter maximal value used is 1/2000.Many atural object scene of testing can comprise vegetation-soil, vegetation-water body, vegetation-rock, vegetation-man-made features, soil-water body, soil-man-made features, water body-rock, the water body-man-made features of combination of two; Vegetation-soil-the water body of three kinds of combinations, vegetation-soil-rock, vegetation-soil-man-made features, vegetation-water body-rock, vegetation-water body-man-made features, soil-water body-man-made features; A plurality of many atural object scenes such as the vegetation-soil-water body-man-made features of multiple combination.
Table 2 is satellite imagery analog simulation experimental result.By evaluation indexes such as signal to noise ratio (S/N ratio), information entropys, choose best time shutter and gain coefficient combination.
Table 2
Table 3 is for being many atural object scene observation control system parameter coupled relation analysis result, i.e. multi-mode observed parameter table.By statistical table, can be found out, under shutter value (integral time) regulates limited case, reduce ISO(gain as far as possible), can obtain the image of information entropy maximum.If shutter value (integral time) is fixing, can be according to itself and ISO(gain) between proportionate relationship try to achieve best ISO(and gain) value.
Table 3
Step 204: according to the observation mode parameter of selected each single atural object scene and many atural object scene, build satellite intelligence earth observation pattern base.
In this step, according to the observation mode parameter of the selected single atural object scene of step and many atural object scene before this, build the satellite intelligence earth observation pattern base under various scenes.
Step 205: according to satellite intelligence earth observation pattern base, select optimum exposure time and gain earth observation imaging in satellite intelligence earth observation pattern base.
In this step, according to initial conditions such as earth observation imaging task parameter, earth observation imaging circumstances parameter, earth observation imaging type of ground objects parameters, carry out task priority, environmental baseline, earth object judgement, in conjunction with other influences factor, the association of comprehensive analysis image-forming condition and impact, determine optimal imaging pattern, provide best total of points time and gain adjustment, with earth observation imaging.
So far, completed the overall process of obtaining satellite intelligence earth observation pattern base method and imaging in the embodiment of the present invention.
In addition, it should be noted that, it is a kind of preferred implementation procedure that the present invention obtains satellite intelligence earth observation pattern base method that above-mentioned all flow processs based on Fig. 2 are described, in the present invention, obtain in the actual realization of satellite intelligence earth observation pattern base method, can on the basis of flow process shown in Fig. 1, carry out as required random variation, can be to select the arbitrary steps in Fig. 2 to realize, the sequencing of each step also can be adjusted etc. as required.
In one embodiment of the invention, also proposed a kind of satellite intelligence earth observation pattern base and obtained system, referring to Fig. 4, having comprised:
Single atural object image-generating unit 401, for each single atural object scene is carried out to the experiment of satellite imagery analog simulation, analyzes atural object characteristic, selects the observation mode parameter of each single atural object scene;
Many atural object image-generating unit 402, for carrying out the satellite imagery analog simulation experiment of many atural object scene, analyzes the observation mode parameter coupled relation of many atural object scene, selects the observation mode parameter of many atural object scene;
Pattern base construction unit 403, for according to the observation mode parameter of selected each single atural object scene and many atural object scene, builds satellite intelligence earth observation pattern base.
In one embodiment of the invention, in order to obtain better imaging effect, preferably, system can also comprise: context vault construction unit 501, as Fig. 5, be connected with single atural object image-generating unit 401, for studying the curve of spectrum feature of each single atural object scene imaging, build background knowledge storehouse.Wherein, can utilize the method for the single atural object scene of point measurement, obtain reflectance spectrum curve.
In another embodiment of the present invention, preferably, single atural object image-generating unit 401 can comprise: the first imaging subelement 502, in conjunction with background knowledge storehouse, the time shutter of specialized aviation remote sensing camera, gain are controlled, realized the imaging to described each single atural object scene; The first parameter chooser unit 503, for the imaging results of each single atural object scene is comprehensively analyzed, assessment signal to noise ratio (S/N ratio), the relation of research time shutter and gain, selection makes imaging results reach the observation mode parameter of optimum signal-noise ratio and information entropy, comprises the one or more parameters in the ratio of time shutter, gain and time shutter and gain.
In another embodiment of the present invention, many atural object image-generating unit 402 can comprise: the second imaging subelement 504, for the time shutter of specialized aviation remote sensing camera, gain are controlled, realize the imaging to described many atural object scene; The second parameter chooser unit 505, for the imaging results of many atural object scene is comprehensively analyzed, assessment signal to noise ratio (S/N ratio), the relation of research time shutter and gain, selection makes imaging results reach the observation mode parameter of many atural object scene of optimum signal-noise ratio and information entropy, comprises the one or more parameters in the ratio of time shutter, gain and time shutter and gain.
In one embodiment of the invention, can utilize signal to noise ratio (S/N ratio) and information entropy to be used as picture appraisal index.Wherein, the first parameter chooser unit 503 can comprise: the first signal to noise ratio (S/N ratio) module; The second parameter chooser unit 505 can comprise: the second signal to noise ratio (S/N ratio) module; The first signal to noise ratio (S/N ratio) module and described the second signal to noise ratio (S/N ratio) module are used for utilizing following formula to be calculated to be picture signal to noise ratio (S/N ratio):
SNR=LSD
maxLSD
min
Wherein SNR is signal to noise ratio (S/N ratio), LSD
maxfor add make an uproar after the maximal value of all pixel local variances in image, LSD
minfor add make an uproar after the minimum value of all pixel local variances in image.Signal to noise ratio (S/N ratio) is larger, and picture quality is better, and too much noise can be covered the information that image provides.At present, for signal noise ratio (snr) of image, calculate and there is no unified definition and algorithm, preferably, the embodiment of the present invention is selected a kind of approximation method, with signal and the ratio of the variance of noise, replace power spectrum to carry out the signal to noise ratio (S/N ratio) of approximate estimation image, use the maximal value LSD that adds the local variance of all pixels in the image after making an uproar
maxwith its minimum value LSD
minratio estimate signal to noise ratio (S/N ratio).
In one embodiment of the invention, preferably, the first parameter chooser unit 503 can comprise: first information entropy module; The second parameter chooser unit 505 can comprise: the second information entropy module; First information entropy module and described the second information entropy module are used for utilizing following formula to be calculated to be picture information entropy:
Wherein, EN is information entropy, p
iprobability while being i for grey scale pixel value in image, the maximum gradation value that n is image.The value of EN is larger, shows that the information that image contains is abundanter, and the spatial detail expressive ability of image is just stronger.
In another embodiment of the present invention, formed observation mode storehouse can comprise the observation mode storehouse of single atural object scene and many atural object scene.Wherein, preferably, single atural object scene can comprise: the scenes such as vegetation, soil, water body, rock and man-made features.Many atural object scene can comprise vegetation-soil, vegetation-water body, vegetation-rock, vegetation-man-made features, soil-water body, soil-man-made features, water body-rock, the water body-man-made features of combination of two; Vegetation-soil-the water body of three kinds of combinations, vegetation-soil-rock, vegetation-soil-man-made features, vegetation-water body-rock, vegetation-water body-man-made features, soil-water body-man-made features; A plurality of many atural object scenes such as the vegetation-soil-water body-man-made features of multiple combination.
In one embodiment of the invention, can utilize resulting satellite intelligence earth observation pattern base to carry out earth observation imaging, preferably, system can also comprise: image-generating unit 506, be connected with pattern base construction unit 403, be used for according to satellite intelligence earth observation pattern base, one or more influence factors in judging in conjunction with task priority, environmental baseline, earth object, the association of comprehensive analysis image-forming condition and impact, determine optimal imaging pattern, select optimum exposure time and gain earth observation imaging in satellite intelligence earth observation pattern base.
It should be noted that, the satellite intelligence earth observation pattern base described in the middle any one shown in above-mentioned Fig. 5 obtains the structure of each embodiment of system can carry out combination in any use.
Visible, the embodiment of the present invention has following beneficial effect:
In the satellite intelligence earth observation pattern base acquisition methods and system providing in the embodiment of the present invention, can test by the single atural object scene in ground and many scene imagings analog simulation, select the observation mode parameter under various scenes, build complete satellite intelligence earth observation pattern base, during for the earth observation of real satellite intelligence, select targetedly, be with a wide range of applications.
The embodiment of the present invention has comprehensively been analyzed the imaging effect under various scenes, from signal to noise ratio (S/N ratio) and information entropy angle, carry out image imaging effect analysis, the setting of the parameters such as research time shutter and gain, for the observation mode parameter setting under several scenes has given quantitative parameter recommendation, qualitative results more in the past has increased significantly.
Finally it should be noted that: above embodiment only, in order to technical scheme of the present invention to be described, is not intended to limit; Although the present invention is had been described in detail with reference to previous embodiment, those of ordinary skill in the art is to be understood that: its technical scheme that still can record aforementioned each embodiment is modified, or part technical characterictic is wherein equal to replacement; And these modifications or replacement do not make the essence of appropriate technical solution depart from the spirit and scope of various embodiments of the present invention technical scheme.
Claims (10)
1. a satellite intelligence earth observation storehouse pattern acquisition methods, is characterized in that, comprising:
Each single atural object scene is carried out to the experiment of satellite imagery analog simulation, analyze atural object characteristic, select the observation mode parameter of each single atural object scene;
Carry out the satellite imagery analog simulation experiment of many atural object scene, the observation mode parameter coupled relation of many atural object scene is analyzed, select the observation mode parameter of many atural object scene;
According to the observation mode parameter of selected each single atural object scene and many atural object scene, build satellite intelligence earth observation pattern base.
2. satellite according to claim 1 intelligence earth observation pattern base acquisition methods, is characterized in that:
Described to each single atural object scene carry out also comprising before the experiment of satellite imagery analog simulation: study the curve of spectrum feature of each single atural object scene imaging, build background knowledge storehouse;
Describedly each single atural object scene is carried out to satellite imagery analog simulation experiment comprise: in conjunction with described background knowledge storehouse, the time shutter of specialized aviation remote sensing camera, gain are controlled, realized the imaging to described each single atural object scene;
Described analysis atural object characteristic, select the observation mode parameter of each single atural object scene to comprise: the imaging results to each single atural object scene is comprehensively analyzed, assessment signal to noise ratio (S/N ratio), the relation of research time shutter and gain, selection makes imaging results reach the observation mode parameter of optimum signal-noise ratio and information entropy, comprises the one or more parameters in the ratio of time shutter, gain and time shutter and gain;
The described satellite imagery analog simulation experiment of carrying out many atural object scene comprises: the time shutter of specialized aviation remote sensing camera, gain are controlled, realized the imaging to described many atural object scene;
The described observation mode parameter coupled relation to many atural object scene is analyzed, select the observation mode parameter of many atural object scene to comprise: the imaging results to many atural object scene is comprehensively analyzed, assessment signal to noise ratio (S/N ratio), the relation of research time shutter and gain, selection makes imaging results reach the observation mode parameter of many atural object scene of optimum signal-noise ratio and information entropy, comprises the one or more parameters in the ratio of time shutter, gain and time shutter and gain.
3. satellite according to claim 2 intelligence earth observation pattern base acquisition methods, is characterized in that:
Described signal to noise ratio (S/N ratio) is: for the ratio of key diagram picture effective information and noise:
SNR=LSD
maxLSD
min
Wherein SNR is signal to noise ratio (S/N ratio), LSD
maxfor add make an uproar after the maximal value of all pixel local variances in image, LSD
minfor add make an uproar after the minimum value of all pixel local variances in image;
Described information entropy is: the quantity of information having for key diagram picture:
Wherein, EN is information entropy, p
iprobability while being i for grey scale pixel value in image, the maximum gradation value that n is image.
4. satellite according to claim 1 intelligence earth observation pattern base acquisition methods, is characterized in that:
Described single atural object scene comprises: the one or more atural object scenes in vegetation, soil, water body, rock and man-made features;
Described many atural object scene comprises: the vegetation-soil of combination of two, vegetation-water body, vegetation-rock, vegetation-man-made features, soil-water body, soil-man-made features, water body-rock, water body-man-made features; Vegetation-soil-the water body of three kinds of combinations, vegetation-soil-rock, vegetation-soil-man-made features, vegetation-water body-rock, vegetation-water body-man-made features, soil-water body-man-made features; One or more many atural object scenes in the vegetation-soil-water body-man-made features of multiple combination.
5. according to the satellite intelligence earth observation pattern base acquisition methods described in any one in claim 1 to 4, it is characterized in that, described method also comprises: according to described satellite intelligence earth observation pattern base, one or more influence factors in judging in conjunction with task priority, environmental baseline, earth object, the association of comprehensive analysis image-forming condition and impact, determine optimal imaging pattern, select optimum exposure time and gain earth observation imaging in satellite intelligence earth observation pattern base.
6. satellite intelligence earth observation pattern base obtains a system, it is characterized in that, comprising: the single atural object image-generating unit, many atural object image-generating unit and the pattern base construction unit that are linked in sequence, wherein:
Single atural object image-generating unit, for each single atural object scene is carried out to the experiment of satellite imagery analog simulation, analyzes atural object characteristic, selects the observation mode parameter of each single atural object scene;
Many atural object image-generating unit, for carrying out the satellite imagery analog simulation experiment of many atural object scene, analyzes the observation mode parameter coupled relation of many atural object scene, selects the observation mode parameter of many atural object scene;
Pattern base construction unit, for according to the observation mode parameter of selected each single atural object scene and many atural object scene, builds satellite intelligence earth observation pattern base.
7. satellite intelligence earth observation pattern base according to claim 6 obtains system, it is characterized in that:
Described system also comprises: context vault construction unit, be connected with described single atural object image-generating unit, and for studying the curve of spectrum feature of each single atural object scene imaging, build background knowledge storehouse;
Described single atural object image-generating unit comprises: the first imaging subelement, in conjunction with described background knowledge storehouse, the time shutter of specialized aviation remote sensing camera, gain are controlled, and realize the imaging to described each single atural object scene; The first parameter chooser unit, for the imaging results of each single atural object scene is comprehensively analyzed, assessment signal to noise ratio (S/N ratio), the relation of research time shutter and gain, selection makes imaging results reach the observation mode parameter of optimum signal-noise ratio and information entropy, comprises the one or more parameters in the ratio of time shutter, gain and time shutter and gain;
Described many atural object image-generating unit comprises: the second imaging subelement, for the time shutter of specialized aviation remote sensing camera, gain are controlled to the imaging realizing described many atural object scene; The second parameter chooser unit, for the imaging results of many atural object scene is comprehensively analyzed, assessment signal to noise ratio (S/N ratio), the relation of research time shutter and gain, selection makes imaging results reach the observation mode parameter of many atural object scene of optimum signal-noise ratio and information entropy, comprises the one or more parameters in the ratio of time shutter, gain and time shutter and gain.
8. satellite intelligence earth observation pattern base according to claim 7 obtains system, it is characterized in that:
Described the first parameter chooser unit comprises: the first signal to noise ratio (S/N ratio) module; Described the second parameter chooser unit comprises: the second signal to noise ratio (S/N ratio) module; Described the first signal to noise ratio (S/N ratio) module and described the second signal to noise ratio (S/N ratio) module are used for utilizing following formula to be calculated to be picture signal to noise ratio (S/N ratio):
SNR=LSD
maxLSD
min
Wherein SNR is signal to noise ratio (S/N ratio), LSD
maxfor add make an uproar after the maximal value of all pixel local variances in image, LSD
minfor add make an uproar after the minimum value of all pixel local variances in image;
Described the first parameter chooser unit comprises: first information entropy module; Described the second parameter chooser unit comprises: the second information entropy module; Described first information entropy module and described the second information entropy module are used for utilizing following formula to be calculated to be picture information entropy:
Wherein, EN is information entropy, p
iprobability while being i for grey scale pixel value in image, the maximum gradation value that n is image.
9. satellite intelligence earth observation pattern base according to claim 6 obtains system, it is characterized in that:
Described single atural object scene comprises: the one or more atural object scenes in vegetation, soil, water body, rock and man-made features;
Described many atural object scene comprises: the vegetation-soil of combination of two, vegetation-water body, vegetation-rock, vegetation-man-made features, soil-water body, soil-man-made features, water body-rock, water body-man-made features; Vegetation-soil-the water body of three kinds of combinations, vegetation-soil-rock, vegetation-soil-man-made features, vegetation-water body-rock, vegetation-water body-man-made features, soil-water body-man-made features; One or more many atural object scenes in the vegetation-soil-water body-man-made features of multiple combination.
10. according to the satellite intelligence earth observation pattern base described in any one in claim 6 to 9, obtain system, it is characterized in that, described system also comprises:
Image-generating unit, be connected with described pattern base construction unit, be used for according to described satellite intelligence earth observation pattern base, one or more influence factors in judging in conjunction with task priority, environmental baseline, earth object, the association of comprehensive analysis image-forming condition and impact, determine optimal imaging pattern, select optimum exposure time and gain earth observation imaging in satellite intelligence earth observation pattern base.
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Cited By (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104270575A (en) * | 2014-10-22 | 2015-01-07 | 中国科学院光电研究院 | Exposure time adaptive-regulation method and device for imaging spectrometer |
CN106960436A (en) * | 2017-03-20 | 2017-07-18 | 哈尔滨工业大学 | A kind of remote sensing image process performance appraisal procedure |
CN108073783A (en) * | 2017-12-06 | 2018-05-25 | 中国科学院上海技术物理研究所 | A kind of self-adapting intelligent optics load implementation method based on measurement data |
CN109509209A (en) * | 2018-11-15 | 2019-03-22 | 上海卫星工程研究所 | Utilize the analysis method of the hyperspectral technique detection aerial moving-target of air-sea environment |
CN110287939A (en) * | 2018-12-29 | 2019-09-27 | 中国科学院软件研究所 | Space-based intelligent image processing method |
CN110736706A (en) * | 2019-10-09 | 2020-01-31 | 北京航空航天大学 | Gobi simulation scene manufacturing method oriented to hyperspectral remote sensing indoor imaging simulation |
CN111213089A (en) * | 2017-09-14 | 2020-05-29 | 杜尔牙科公司 | Method of determining the quality of an imaging plate and imaging plate scanner for use in the method |
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-
2013
- 2013-11-08 CN CN201310553557.3A patent/CN103576165B/en active Active
Non-Patent Citations (3)
Title |
---|
刘团结: "航空多光谱数字相机***关键技术及应用研究", 《中国博士学位论文全文数据库》, no. 1, 31 January 2004 (2004-01-31), pages 42 * |
卿恒新: "复杂地形下典型地物目标热遥感成像仿真研究", 《中国优秀硕士学位论文全文数据库(电子期刊)》, no. 2, 28 February 2009 (2009-02-28), pages 54 - 66 * |
林文芳: "基于SPOT5特征波段的太白地区土地覆盖遥感分类方法研究", 《中国优秀硕士学位论文全文数据库(电子期刊)》, no. 7, 31 July 2013 (2013-07-31), pages 10 - 29 * |
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