А.А. Romanov - Post-graduate Student, Moscow Aviation Institute (National Research University); Engineer, JSC «Concern «VEGA». E-mail: alexromanoviv@gmail.com

The most responsible and laborious part of radiolocation data processing is interpretation. Therefore the development of the theory and automated radar image interpretation systems is one of the most important problem the solution of which will improve the operativeness of getting results of radar monitoring. Most automated and automatic radar image processing systems (which solve the problems of radar image stitching or object recognition, for example) require sematically rich images or in other words the radar images with pronounced contranst changes within the image frame. Using such systems for processing of lean semantics images leads to a loss of time without any desired results. Currently there is no objective quantitative indicators that can describe the saturation of radar image sematics. That makes difficulties in estimation of requirments for automatic image processing systems. This problem is also relevant to image processing systems of different spectral ranges. In this paper we propose a method of radar image quality assessment using quantitative scalar indicators of semantic saturation S, Sps and a matrix one Sm. These indicators allow to formalize the requirements for semantic saturation of radar images for automatic radar image processing systems, to reduce processing time by sieving radar image fragments of no interest and to localize the area of interest in the radar image. The proposed image semantic saturation indicators can also be used in assessment of semantic saturation of optical images particularly aerial photos.

 

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