In this paper, we analyze graphic documents with a weakly formalized description of objects (WFGD) and reveal their main features that influence the choice of models, methods and algorithms for processing such documents. In the framework of the development of the combinatorial-geometric approach, a geometric model for describing WFGDs with a pronounced orientation of linear objects is proposed. We also propose a technology for vectorization of raster images of WFGDs in the presence of noise in the source data. The effectiveness of an extended class of vector models (linear and segment-node models) used for describing WFGDs with a distinctive linear orientation of objects is shown, which was revealed during practical experiments on real WFGDs.

We study a problem of complex analysis and monitoring of the environment based on Earth Sensing Data, with the emphasis on the use of hyperspectral images (HSI), and propose a solution based on developing algorithmic procedures for HSI processing and storage. HSI is considered as a two-dimensional field of pixel signatures. Methods are proposed for evaluating the similarity of a HSI pixel signature with a reference signature, via simple alignment transformations: identical; amplitude scaling; shift along y-axis; and a combination of the last two. A clustering / recognition method with self-learning is proposed, which determines values of the transformation parameters that ensure the alignment of the current pixel signature with the reference signature. Similarity with the reference is determined by a standard deviation value. A HSI compression method with controlled losses has been proposed. The method forms a basis via accumulating reference signatures and represents the rest of the signatures by parameters matching them with the already detected class-reference signature. In an experiment with the GSI f100520t01p00-12 data of the AVIRIS spectrometer, the method provided a 2 % loss and compression coefficients of the original HSI ranging from 43 to 165 for various types of alignment transformation, while not requiring archiving and thus maintaining active access to the HSI and using the list of references as an analogue of the HSI palette. An algorithm for the formation of dense groups of detectable objects (for example, oil spots) and their nonconvex contouring, controlled by 4 parameters, is proposed. A pilot version of the concept of geographic information system (GIS) and an appropriate database management system (DBMS) was built and implemented, which provides monitoring and is based on the prioritized processing and storage of the HSI, which serve as a data source for the system. A laboratory complex with new algorithms for processing and storing the GSE is introduced into the structure of the system.

The paper considers some issues of eliminating information redundancy of hyperspectral images (HSI). The characteristic properties of the HSI are listed, a brief description of the existing HSI compression methods is given. The possibility of using local, homogeneous “well-adapted” basis functions (LHWABF) to eliminate information redundancy and adaptive compression of the HSI is considered. An algorithm for constructing a LHWABF system for the HSI based on the Chebyshev approximation is proposed. The results of computational experiments, including the use of a graphics processor, are presented. The effectiveness of the proposed method of adaptive compression HSI is shown.

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