983 results about "Remote sensing satellite" patented technology

The invention provides a three-dimensional digital earth-space data organizing and rendering method based on a quad-tree index, which belongs to the technical fields of cartography, geography information systems and virtual reality. The method comprises the following steps of: unifying common spatial data formats under multi-scale and multi-projection conversion, multispectral, multi-temporal and high-resolution remote sensing satellite images and aerial images as well as digital thematic maps with different scales into same coordinate system, carrying out operation on the attribute of each element and the parameter regulation of quad-tree tiles, outputting in the form of the quad-tree tiles, carrying out quad-tree cutting on three-dimensional landscape map data, leading spatial data into a relevant database, and carrying out unified management. By using the method, common vector data, raster data, altitude data and three-dimensional map data are organically integrated and issued into a three-dimensional digital earth prototype, thereby shortening the time of data preprocessing, improving the execution efficiency and providing a new integration method for three-dimensional digital earth fundamental geographic data dissemination.

The invention discloses an improved weighting region matching high-altitude video pedestrian recognizing method (KS-WRM (KS-weighting matching region)). The improvement is reflected as follows: 1) confirming a candidate region by utilizing Kalman filtering; 2) fixing a camera or not by adopting different pedestrian detecting strategies; 3) proposing a pedestrian detecting method of an HLS (hue, lightness and saturation) model with multi-characteristic fusion; and 4) dividing pedestrians based on CA obvious region detection of context sensing. According to the invention, pedestrians can be recognized accurately under complex occasions of blur details, complex backgrounds, noise influences and the like. And the improved weighting region matching high-altitude video pedestrian recognizing method (KS-WRM) provided by the invention can be used for pedestrian detection and recognition at places with high visitor flow rate, such as remote sensing satellite images, malls, subway stations, railway stations, airports, as well as intelligent traffic control, intelligent vehicle auxiliary driving, pedestrian flow rate statistics and analysis places.

A method includes: a) producing initial scheduling plans based on requests related to tasks to be performed within a time period by a remote sensing satellite; wherein each initial scheduling plan schedules respective tasks, which do not conflict with each other in time and in using satellite resources; and each task is scheduled in at least one of the initial scheduling plans; b) applying a genetic-algorithm-based processing to the initial scheduling plans to produce a genetic-algorithm-based scheduling plan which is for mission objectives, and complies with constraints related to the satellite resources, to the tasks, and to the time period; and c) applying a simulated-annealing-based processing to the genetic-algorithm-based scheduling plan to produce a simulated-annealing-based scheduling plan that fits the mission objectives, complies with the constraints, and in which a larger number of tasks is scheduled than in the genetic-algorithm-based scheduling plan.

The present invention provides method and system for automatically planning and scheduling a remote sensing satellite mission. A swath coverage of a remote sensing satellite at a specified time interval is determined from a ground station. Thereafter, a set of points-of-interest lying within the swath coverage of the remote sensing satellite at the specified time interval is identified. The method further includes associating a goodness factor to each point-of-interest of the set of points-of-interest based on a satellite mission requirement. An artificial intelligence searching algorithm is utilized to select a sub-set of points-of-interest from the set of points-of-interest based on a satellite resource constraint and a corresponding goodness factor associated with each point-of-interest. Finally, the method schedules the remote sensing satellite to capture at least one image for each point-of-interest of the sub-set of points-of-interest.

The invention provides a configuration for a low-earth-orbit remote sensing satellite, which comprises a base plate, a middle plate, a top plate, a plurality of transverse lateral plates and upright lateral plates, wherein the base plate, the middle plate and the top plate are enclosed into a sealed space by the transverse lateral plates and the upright lateral plates; a central force-bearing cylinder is arranged in the sealed space; corresponding solar cell arrays are arranged on the two sides of the sealed space; a supporting rod is connected between the base plate and the middle plate; four isolating plates are uniformly distributed and are arranged between the middle plate and the top plate; a payload bay is connected above the top plate; and an overskirt is connected to the bottom of the base plate. The configuration for the low-earth-orbit remote sensing satellite has a stable structure, is capable of carrying a large-size and large-mass load, and is high in adaptability for the characteristics of large volume, heavy weight, high precision demand and difficulty in mounting of the present payload.

The invention discloses a method for calibrating in-orbit exterior orientation parameters of push-broom optical cameras of remote sensing satellite linear arrays. The method includes steps of (1), acquiring information of high-precision control points; (2), acquiring interior orientation elements of the cameras at the control points, acquiring auxiliary data of orbits and the like and building rigorous imaging geometric models of various control points; (3), computing positioning errors of the various control points, eliminating coarse and poor control points and acquiring information of preliminarily calibrated control points; (4), building geometric calibration mathematical models of exterior orientation elements of the cameras, and computing theoretical pointing vectors and actual pointing vectors of the various control points; (5), creating three-axis rotation error equations among the theoretical pointing vectors and the actual pointing vectors and linearly processing the equations; (6), solving parameters of the error equations by a least square process to acquire calibration exterior parameters. The method has the advantage that after errors of a system are compensated by the aid of the calibration exterior parameters, the cameras are stable in non-control positioning precision.

The invention provides a satellite-ground cooperative in-orbit real-time geometric positioning method and system for optical satellites. The method comprises the following steps: an optical satellite imaging and positioning model suitable for an onboard real-time processing unit is constructed, initial values of onboard positioning model parameters are acquired by calibration parameters or design parameters for camera interior and platform installation relation by a ground laboratory, after the satellite is in orbit, ground calibration field image data is acquired and downloaded, calibration matching and calibration parameter calculation are completed in a ground processing system by using the downloaded calibration field images; calibration results are verified and model parameter annotation is updated. The method and the system aim at limitation of onboard processing environment, and combine the ground processing system, so that a satellite-ground cooperative processing mode is formed, in-orbit high-precision real-time geometric positioning of optical remote sensing satellite is realized, application usefulness and timeliness of earth observation systems are improved, and necessary bases are provided for intelligent and high-efficient remote sensing data onboard real-time processing technology.

The invention provides a remote sensing monitoring method for water quality parameters of a shallow aquatic plant lake. The method comprises the following steps: acquiring time series satellite remotesensing image data of a lake area, and extracting a water body by use of a normalized differential water body index MNDWI; calculating a normalized differential vegetation index NDVI and a normalizeddifferential aquatic plant index NDAPI of the water body to quickly extract an aquatic plant covering zone and aquatic plant growth conditions; building a vegetation index time spectrum cube image ofthe aquatic plant covering zone to realize fine partition of aquatic plant species; using the water quality indication effect of the aquatic plant species and the aquatic plant growth conditions forpartitional and seasonal inversion of the water quality parameters of the aquatic plant covering zone; and forming a spatial distribution map of the water quality parameters. According to the method proposed by the invention, the aquatic plant species on a remote-sensing satellite image can be accurately identified according to unique phenological characteristics of ground features and remote sensing vegetation index time spectrum analysis technology, the water quality parameters of the shallow aquatic plant lake can be simply and quickly inverted.

The invention discloses a land surface soil moisture downscaling method based on multisource remote sensing satellite merged data and is particularly applicable to cloudy and rainy areas. The method comprises the following steps: collecting and arranging a passive microwave soil moisture data set, an LST (land surface temperature) and NDVI (normalized difference vegetation index) data set and DEM(digital elevation model) data; performing spatial interpolation on LST images with serious pixel deletion affected by cloud and rain by adopting an NDVI and DEM data set as auxiliary data to obtain aday-by-day LST data set almost totally covering a research area; constructing a mathematic relation model for microwave soil moisture with optical remote sensing LST and NDVI by a geographical weighted regression model, and obtaining a land surface soil moisture data set with high spatial resolution with the mathematic relation model. Through the adoption of the method, reliability of a descalingresult and universality of descaling in the wide-range research area are improved effectively, and precision and efficiency of wide-range space mapping and monitoring for soil moisture content in thecloudy and rainy areas are improved.

The present invention provides an automatic cloud detection method and system for a multi-spectral remote sensing satellite image. The method comprises: preparing data; roughly extracting clouds; extracting texture information on an image intensity information channel by combining histogram equalization and bilateral filtering; segmenting a texture information map by using a two-dimensional Otsu threshold; removing an error from a rough detection result by using a binary detail map after segmentation; using intensity information of a raw image as a guide map; and based on the rough detection result with the error being removed, performing accurate extraction on the clouds through edge seed expansion. The technical scheme actually realizes automatic, fast, and accurate detection of cloud.

Provided is an earthquake disaster rescue command and dispatch system and a method thereof; the system consists of a command center subsystem, a remote sensing satellite subsystem, an unmanned plane subsystem, a police population information subsystem, a weather information subsystem, a medical information subsystem, a relief goods repertory subsystem and input / output interfaces; by analyzing disaster information and disaster rescue information collected by each aforementioned system, a hierarchical model of earthquake disaster rescue can be built by an analytic hierarchy process; meanwhile, based on the actual situations of former earthquake disaster rescue, respective disaster rescue plan and analytic hierarchy process disaster rescue parameter database can be built. When an actual earthquake disaster happens, the current disaster situations are analyzed by the analytic hierarchy process, and the disaster rescue plan is quickly determined. The designed system and method herein are more applicable to collecting relative information quickly as soon as the earthquake happens, and automatically selecting the rescue plan for the command dispatch of the disaster rescue.

The invention discloses a follow-up tracking dynamic and static isolation type dual-super satellite platform and a working mode implementation method thereof. The follow-up tracking dynamic and static isolation type dual-super satellite platform is suitable for sensitive load spacecrafts with the ultra-precision and ultra-stability requirement. Dynamic and static isolation is used as the means, a satellite is divided into a load cabin and a service cabin, the load cabin can ensure that the effective load meets the expected ultra-precision and ultra-stability control requirement through a high-performance magnetic levitation flywheel arranged on the load cabin, the service cabin can resist environmental disturbance and track the load cabin in a follow-up mode through an external actuator mounted on the service cabin, and accordingly the two cabins can meet the expected relative pose requirement. The load cabin is connected with the service cabin through a suspension device in a non-contact mode, vibration disturbance of the service cabin can be effectively isolated, and the vibration isolation effect cannot be affected by the sensor performance. The satellite based on the dual-super satellite platform at least has the launching, ultra-precision and ultra-stability, anti-collision or mobility working mode. The dual-super satellite platform can be applied to high resolution sensitivity effective load spacecrafts such as a high resolution remote sensing satellite and a deep space exploration astronomical telescope.

The invention discloses a grassland dry matter mass remote sensing estimating method, which belongs to the field of remote sensing application. The method comprises the following steps of: collecting and processing field test data; downloading and processing Modis (Moderate Resolution Imaging Spectroradiometer) satellite data; analyzing and modeling the data and detecting the accuracy and the like. The method for establishing a ground spectrum model for predicating ground dry matter mass and correcting a Modis spectrum model through ground hyperspectral experiments is different from the method for directly predicating biomass liveweight by using NDVI (Normalized Difference Vegetation Index) data of the Modis remote sensing satellite in other like researches so that the grassland dry matter mass remote sensing estimating method is helpful for improving the predicating accuracy, is beneficial for scientific management and reasonable utilization of the grassland resources and has important practical significance in correct evaluation of the real productivity of the grassland and the sustainable use of the grass resources.

The invention discloses an automatic geometric correction and orthorectification method for multispectral remote sensing satellite images of a mountainous area. The method comprises the following steps of: selection and splicing of reference images; automatic selection of object points with same names; screening of the object points with same names, and geometric correction and orthorectification for correcting the images; precision evaluation; and output of the images. The multispectral remote sensing satellite images of the mountainous area, such as images of China domestic environment and disaster monitoring small satellite (with the model HJ-1A / B), have the characteristic of serious geometric distortion, but the automatic geometric correction and orthorectification method can be used for performing the orthorectification on the multispectral remote sensing satellite images of the mountainous area in mass and generating residual error reports of the coherent images by adopting a concept of the object points with same names to implement the geometric correction and orthorectification. The automatic geometric correction and orthorectification method has the advantages of high efficiency and precision, is very efficient when being used for processing the multispectral remote sensing satellite images with mass data of the mountainous area, can remarkably save manpower and material resources needed by the conventional remote sensing image processing process, and particularly is beneficial to the processing of the images of the China domestic environment and disaster monitoring small satellite.

The invention belongs to the technical field of agricultural insurance, and particular relates to an agricultural insurance survey and loss assessment system capable of combining a geographic information technology, a remote sensing technology and a satellite positioning technology and an implementation method thereof. The system comprises a remote sensing satellite image data module, an image preprocessing module, an image map service module and a central server, wherein the image preprocessing module is in communication data connection with the remote sensing satellite image data module; the image map service module is in the communication data connection with the image preprocessing module; the central server is in the communication data connection with the image map service module; and the central server is connected with an object information storage module, a crop database module, a meteorological data server module, a scene investigation component, a module used for an agricultural expert side and a module used for an insurance company side through a data communication line. By use of the agricultural insurance survey and loss assessment system and the implementation method thereof provided by the invention, a damage area can be accurately measured extensively, and an accurate judgment basis can be quickly given to the damage range and degree of a damaged object.

The invention discloses a universal transport packing case for a remote sensing satellite, which comprises a case cover and a case bottom, wherein an air conditioner, a temperature-humidity sensor, an inflatable / deflatable device capable of being automatically and / or manually inflated or deflated, hoisting points, transport fixing points and a data acquisition and control system are arranged on the case cover; a damping device is arranged on the inner side of the case bottom; an L-shaped bracket used during integrated satellite transport or a transport bracket used during subdivided transport, sensors comprising the temperature-humidity sensor and the like, and fans are arranged above the damping device; the data acquisition and control system is respectively and electrically telecommunicated with the temperature-humidity sensor, a pressure sensor, a vibration sensor, an impact sensor and the like, and is electrically telecommunicated with a remote control terminal so as to conveniently control the transport of the remote sensing satellite over a long distance in real time. The universal transport packing case for the remote sensing satellite can fulfill functions of highway transport, railway transport, system leakage detection and the like when different remote sensing satellites in integrated states or subdivided states are in various working conditions, the remote sensing satellites in the integrated states or the subdivided states can be highly reliably transported and the satellite development cycle is simultaneously shortened.

In view of the characteristics of the high-resolution remote sensing images, the invention provides a practical intelligent method for classifying images, which comprises the following six steps: generating the image segmentation result of a full-color image; acquiring the segmentation result of a multispectral image by utilizing space mapping; determining whether the segmented regions of the full-colour image are insufficiently segmented; resegmenting the detected insufficiently-segmented region; generating the regional feature space; and classifying the image by using a classifier. The invention solves the problem that the insufficiently-segmented regions frequently influence the image classification precision in the image classification process. The method is suitable for high-resolution images from remote sensing satellites, such as IKONOS, QUICKBID and the like, and plays an important role in extracting application messages, such as target identification, resource environment survey, land utilization trends, disaster monitoring, disaster situation evaluation and the like.

The invention discloses a method for on-orbit absolute radiation calibration, which comprises the steps of: conducting root calculation on optical thickness of an aerosol; determining parameters of an MODTRAN model according to atmospheric spectral transmittance of a measured wave band; adopting the MODTRAN model with determined parameters, and calculating to obtain atmospheric spectral transmittance on a ground target-satellite path; calculating total solar irradiance on the surface of a target; and calculating entrance pupil radiance of a satellite; looking up DN values of gray scale targets on a satellite digital image, and determining absolute calibration parameters of load carried by the satellite by combining the DN values with the entrance pupil radiance corresponding to the ground target. The invention further discloses a device for on-orbit absolute radiation calibration. By adopting the method and the device for on-orbit absolute radiation calibration, the atmospheric parameter processing procedure for on-orbit absolute radiation calibration of a remote sensing satellite is simplified, and an atmospheric transmission model most accordant with the actually-measured atmospheric condition can be determined, thereby improving the on-orbit absolute radiation calibration precision of the remote sensing satellite.

The invention discloses an autonomous orbit control method for a low-orbit remote sensing satellite. The autonomous orbit control method comprises the following steps that firstly, the deviation between a current orbit semi-major axis and a nominal orbit semi-major axis is calculated on orbit in real time; secondly, the length of working time of an orbit-control engine is acquired according to orbit-control impulse, an apogee position is acquired through orbit extrapolation calculation autonomously, the time that the satellite arrives at the apogee position is taken as an orbit-control center moment, and the moment that the engine begins to ignite and the moment of brennschluss are acquired according to the length of working time of the orbit-control engine and the orbit-control center moment; and thirdly, the orbit-control engine is controlled to ignite autonomously according to the moment that the engine begins to ignite in the second step, then the orbit-control engine is controlled to conduct brennschluss autonomously according to the brennschluss moment in the second step, and finally the low-orbit remote sensing satellite completes state recovery. According to the autonomous orbit control method for the low-orbit remote sensing satellite, on-orbit autonomous compensation of the orbit semi-major axis error can be achieved on the condition without ground station support, the ground operation control cost of the satellite is lowered, and abilities of autonomous management and autonomous operating of the satellite are promoted.

The invention provides an optical remote sensing satellite rigorous imaging geometrical model building method. The optical remote sensing satellite rigorous imaging geometrical model building method comprises the following steps that the geometrical relationship between the image point coordinates of an optical remote sensing satellite and the satellite is determined according to design parameters and on-orbit calibration parameters of an optical remote sensing satellite camera and the installation relation of the camera and the satellite; the shooting position of a satellite image is determined according to the GPS carried by the optical remote sensing satellite, the observation data of a laser corner reflector and the installation relation of the laser corner reflector and the satellite; the shooting angle of the satellite image is determined according to a star sensor carried by the optical remote sensing satellite and the observation data of a gyroscope and the installation relation of the gyroscope and the optical remote sensing satellite, a collinearity equation of all image points of the optical remote sensing satellite is built, and a rigorous imaging geometrical model of optical remote sensing satellite images is formed. The optical remote sensing satellite rigorous imaging geometrical model building method is the basis of optical remote sensing satellite follow-up geometrical imaging processing and application.

The invention relates to a novel commercial remote sensing satellite configuration layout. The novel commercial remote sensing satellite configuration layout comprises a hollow satellite structure (4) in a regular pentagon stand column manner, a body-mounted solar wing (3) and unfolding solar wings (2,6 and 7); and the satellite structure (4) further comprises a base plate (402), five same side plates (403-407), a camera installation plate (409) and a truss structure (408). According to the novel commercial remote sensing satellite configuration layout, factors such as a main load camera machine connector, the satellite main structure manner, the solar wing installation layout and the electronic equipment installation layout are comprehensively considered, and comprehensive optimization design is carried out, miniaturization, light weight, small rotational inertia and good final assembly operation of a satellite can be achieved on the basis that the effective load and the platform equipment installation layout requirement are met, and the satellite in-orbit application requirement is met.

The invention provides a remote sensing satellite image quality evaluation method, which includes steps as follows: acquiring an original image; acquiring a set of degraded images with different qualities through the degradation treatment; analyzing the quality indexes of the degraded images; analyzing application effects of the degraded images; establishing a linear relation model from the quality indexes of the degraded images to the application effects of the degraded images; and evaluating the quality of the remote sensing satellite image based on the relation model. Targeted at the application effects of the remote sensing satellite image, the remote sensing satellite image quality evaluation method specifically evaluates the quality of the image through the combination of the subjective evaluation and the objective evaluation.

The invention provides a remote sensing satellite data transmission product automatic testing system and method. The remote sensing satellite data transmission product automatic testing system comprises a PXI system controller which provides a real-time operating system for a whole PXI platform; a PXI module set which is connected with a PXI bus and provides a direct interface for a tested product; a PXI case which provides a stable mechanically structured platform and a reliable power supply and heat radiation system for the PXI system; and a piece of testing system software which cooperates with the PXI module set to realize corresponding functions and provides an interacting interface for a user. Based on universal PXI architecture design, the remote sensing satellite data transmission product automatic testing system overcomes the disadvantages of huge device scale, high construction difficulty and long period of an existing remote sensing satellite data transmission ground testing system.

The invention discloses a hierarchical distributed autonomous collaborative task planning system for an intelligent remote sensing satellite. The system comprises a multi-satellite task coordinator and an on-satellite scheduler, wherein the multi-satellite task coordinator distributes tasks in a task set to be distributed to multiple affiliated intelligent satellites and processes the tasks into meta-tasks which can be directly identified by the on-satellite scheduler; each intelligent satellite utilizes the on-satellite scheduler to carry out uniform scheduling on a new distributed task and an existing task; and before the multi-satellite task coordinator carries out task distribution, a scheduling result on the relevant on-satellite scheduler is estimated in advance and is taken as a basis for task distribution. Key scientific problems and technical problems of imaging task schedulability prediction, multi-task multi-resource dynamic scheduling under a high-dimensional space, refinedplanning and scheduling algorithm design are successfully tackled, a multi-satellite autonomous collaborative task planning technology can be better applied to the field of national defense construction, and the rationalization of a distribution scheme and the high efficiency of resource utilization can be accelerated.

The invention discloses an aircraft thermally-induced vibration dynamics response evaluation method. A flexible aircraft thermally-induced micro-vibration coupling dynamics analysis method is adopted, so that response higher in accuracy can be acquired when compared with a simplified aircraft thermally-induced micro-vibration non-coupling dynamics modeling method which is currently used and composed of a two-dimensional cantilever and a central rigid body, analysis of influence on aircraft posture, especially high-resolution remote sensing satellite imaging resolution, by flexible accessory thermally-induced micro-vibration dynamics environment is better facilitated.

The invention discloses a miniaturized universal platform for preprocessing remote-sensing satellite data. Hardware equipment of the platform comprises a common PC (Personal Computer) server, an NFS (Network File System) storage system and decompression equipment among which communication is carried out by an Ethernet; a basic structure of the platform comprises an inner core layer, a module layer and a service layer; the common PC server comprises a management node and a processing node; the inner core layer and the service layer are deployed on the management node; the module layer is deployed in the NFS storage system; the decompression equipment outputs a signal to a demodulator to carry out data format decompression processing; the module layer comprises various data processing algorithms of remote-sensing satellites and the data processing algorithms operate on the processing node when being called; the service layer analyzes an XML (Extensible Markup Language) file which is input from outside and describes the processing flow of the remote-sensing satellites to be processed, selects the algorithms suitable for data processing of the satellites from the module layer and carries out service logic combination on the algorithms; and the inner core layer calls the corresponding algorithms in the module layer according to the service logic relation, carries out data processing on data output by the decompression equipment and generates needed data products.

Provided is a multi-source remote sensing satellite data parallel processing system and method based on algorithm classification. The system and method support new algorithm register, store and manage the registered algorithm, select one or more algorithms from a algorithm register module, push remote sensing satellite data required to be processed and the selected algorithms to a parallel processing node to be processed; the parallel processing nodes simultaneously parallel compute the remote sensing satellite data required to be processed according to the algorithms received by nodes and an executing order; monitors the execution of the algorithms pushed to the parallel processing nodes; and files and stores processed results acquired by the parallel processing nodes. The system and the method support various remote sensing algorithm and multi-source remote sensing data, may simultaneously respond to and execute a multi-source remote sensing data processing request in a distributed cluster, solves multi-source remote sensing satellite data multi-algorithm comprehensive processing, parallel computing, and distributed storage, and achieve a multi-source remote sensing satellite data parallel processing effect.

The invention provides an in-orbit real-time imaging navigation and registration method for stationary satellites. The in-orbit real-time imaging navigation and registration method includes steps of firstly, analyzing error sources with influence on the sight line pointing precision of the remote sensing satellites and dividing the error sources into random errors and system errors; secondly, dividing given system error sources into attitude deviation, orbit excursion and thermal deformation; thirdly, arranging imaging navigation and registration special computation units on the satellites; fourthly, adding computation results of three compensation modules by the aid of each onboard imaging navigation and registration unit and utilizing the sums of the computation results as total compensation quantities. The in-orbit real-time imaging navigation and registration method has the advantages that scanning paths, on earth surfaces, of instrument sight lines can be navigated to reach expected locations by means of compensation under the conditions of interference and influence of space environments on the remote sensing satellites, accordingly, images downloaded from the satellites can be matched with earth nominal grid images generated under nominal ideal conditions, and errors can be within index ranges under the control.

The invention discloses a method for extracting glacial lakes in a highland area based on a remote sensing satellite image. The method comprises the steps of (1) obtaining the remote sensing satelliteimage and DEM data and carrying out pre-processing on the remote sensing satellite image and the DEM data, (2) carrying out global glacial lake crude extraction which comprises a step of obtaining anormalized different water index (NDWI) value of a whole region according to pre-processed remote sensing satellite image, combining a near infrared reflectance (NIR) value and a short wave infraredreflectance (SWIR) value, setting threshold values of NDWI, NIR and SWIR for the whole image, and eliminating the influences of glaciers and other ground features and a step of generating a slope mapof the area by using pre-processed DEM data, setting a slope threshold value and removing the effect of a hill shadow, and roughly extracting all glacial lakes and mixed backgrounds, and (3) carryingout local glacial lake fine extraction which comprises the steps of introducing a C-V model of a symbolic pressure function to accurately extract the glacial lakes one by one based on a result of glacial lake crude extraction. According to the extraction method of the invention, various factors affecting the extraction of the glacial lakes can be effectively removed, accurate extraction is achieved, and the method also has a good extraction result for smaller glacial lakes in the image.

The invention discloses a progressive distribution type encoding and decoding method for a multispectral image. In the method, each band image is directly and independently encoded at an encoding end,and data dependence is only excavated at a decoding end, therefore, the complexity of data calculation can be transferred from the encoding end with resource constraint to the decoding end with richresources so as to optimally utilize resources of a system and be suitable for a remote sensing satellite. The invention also discloses a distribution type encoding and decoding device for a multispectral image. A module which is used for excavating the data dependence is arranged at the decoding end, and therefore, the encoding end is simplified to the maximum to enable the system to be more reasonable. The invention has the advantages of low encoding complexity, high compression efficiency, strong error resilience ability and progressive transfer characteristic and is suitable for lossless compression or nearly lossless compression of the multispectral image, in particular to an image compression application on the satellite.