METHOD RECONSTRUCTION SEGMENTED VIDEO DATA STREAM BY NORMALIZED DATA SETS IN SPECTRAL-PARAMETRIC SPACE

The article shows that depending on the features of applied application, different requirements are put forward for information and technical features and performance characteristics of information and network systems. This motivates the creation of new and improvement of existing video encoding technologies. However, with the development of information technologies, new opportunities are created for their applied application. The requirements for: completeness of video data are growing; analysis of complex video scenes, frames; providing information advantage in the context of cyber confrontation. Accordingly, there is an urgent need for further improvement of compression technologies in the direction of increasing their efficiency in the system of indicators "compression level – distortion level". The article substantiates the fact that improvement should first of all be carried out in the direction of processing flexibility, taking into account the types and significance of video scene objects. Hence the need to create a technology for classifying video scenes and in an additional search for new dependencies. It is shown that one of such approaches is a method based on the construction of spectral-parametric description for segments and clustering of their sequences (datasets) according to certain meta-characteristics. At the same time, the reverse process for recovering video data from data sets with their preliminary decoding does not have a defined and reasonably systematized technological solution. Hence, the purpose of the research of the article concerns the development of a method for recovering video data based on the process of decoding data sets in spectral-parametric description. A technology for restoring the sequence of transformants has been developed based on taking into account: the cluster distribution of transformants, which is presented in the spectral-parametric description according to their structural features; decoding of binary block codes with the appropriate length set by marker references; simultaneous restrictions on the intervals of the definition area in the direction of SPS slices and components of SPPT clusters; determination of the weight of the components of the components of the SPPT according to positional rules depending on their characteristics: the number of local spectral sub-bands; current capacity of the components of the SPPT; determination of the length of marker codes depending on the structural feature of the cluster by the length of the components of the SPPT.