In the paper is described clouds segmentation algorithm based on convolutional neural network. It has been made an analysis of existed convolutional neural networks topologies and it was made a decision of using the modifying U-Net topology. The preliminary data processing has been made taking into account a source data specific. Learning dataset has been made using real high spatial resolution remote sensing data and manual segmented clouds mask. Methodology of using learning dataset in network learning process has been proposed. Results of learned network implementation on real data are shown in the paper.
Control and refinement of the geodetic linkage according to control points are one of the stages for processing of satellite image with high spatial resolution. The present paper has suggested a solution of two issues connected with high speed search of control points. Firstly, continuous supporting coating synthesized from separate images obtained from the spacecraft Landsat-8 has been created. Existing solutions for storage of the reference data have been studied and implementation of the tile storage being significantly exceeding than open solutions GeoServer, MapServer by speed has been suggested. Secondly, a possibility of effective parallel implementation of algorithms for search of control points using modern computer technology including multicore CPU and GPU has been researched. Method to search control points allowing forming a set of control points with the specified reliability and speed greatly increasing the correlation-based algorithm speed has been suggested.
The present paper has been devoted to the selection of an optimal cartographic projection for standard products of the new hydrometeorological observing system from the high elliptical orbit “Arktika-M”. Conditions of imaginary from the high orbit and the issue how to preserve spatial resolution have been analyzed. The paper has shown that usage of widely used standard projections leads to the excessive number of images. The projections representing imaginary materials with better quality with minimal amount of data have been suggested and researched.
In the paper is described fast 3-staged algorithm for segmentation of low-information areas on high spatial resolution panchromatic images of Earth surface. At the first stage, an image is divided into the fragments of 128×128 pixels in size and analysis of pixels “Top of the atmosphere” reflectance is performed. At the second stage the analysis of frequency characteristic of fragments is performed. At the third stage the objects of an artificial origin such as strongly pronounced straight lines is assessed using the Hough transformation. The developed algorithm got high expert appraisal. In the case of high percent of low-informative fragments on the image the proposed algorithm provides significant decrease of GCP finding time.
The present paper has described main functioning principles of imagery instruments of high spatial resolution of Russian satellites “Resource-P”. Processing of images obtained from these instruments according to the level 1 includes: relative radiometric correction, stitching of video data obtained from separate CCD-matrices, geometric matching of multitemporal multispectral images from optoelectronic converters (ОЕС), pansharpening, saving of results in distribution formats. Stages for acquisition of a high-precision model for the Earth surface imagery being a base of processing are considered. Descriptions of algorithms for realization of mentioned processing types, examples of their practical usage and also precise characteristics of outputs are described.
The paper provides an overview of the terrain survey realized on the base of the Russian small space vehicle (SV) “Canopus-V”. The on-ground information technology for the SV’s data processing is considered. The suggested technology includes the primary processing of the telemetric stream data, cataloguing of survey routs and forming output information products on different standard levels. The paper does briefly describe the algorithms of cloud object detection and navigation measurement processing. Besides, the paper describes the types of output information products distributed to consumers.
The paper is devoted to the earth surface image formation by means of multi-matrix scanning cameras. The realized formation of continuous and spatially combined images consists of consistent solutions for radiometric scan correction, stitching and geo-referencing of multispectral images. The radiometric scan correction algorithm based on statistical analyses of input images is described. Also, there is the algorithm for sub-pixel stitching of scans into one continuous image which could be formed by the virtual scanner. The paper contains algorithms for geometrical combining of multispectral images obtained in different moments; and, examples illustrating effectiveness of the suggested processing algorithms.
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