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ADAPTIVE THREE-DIMENSIONAL DISCRETE COSINE TRANSFORM OF TRANSPORT IMAGES

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Subject of Research. The paper presents encoding and decoding method for video information obtained from video surveillance cameras in transport. The method is based on the usage of adaptive three-dimensional discrete cosine transform. Video compression typically has two goals: to reduce spatial redundancy between image elements and temporal redundancy between successive frames. The basic principle of spatial encoding is the consideration of the correlation of the adjacent pixel brightnesses, and the basic principle of interframe encoding is prognosis and motion compensation for the interpolated sample positions in the reference frame in all known standard video codecs such as H. 26х and MPEG-x. Method. The method is characterized by applying an adaptive cosine transform in the signal space and with respect to time, and the sizes of the cubes are unspecified depending on spartial and time statistical characteristics of the image signal. Main Results. The results show that the proposed algorithm can improve the encoding and decoding efficiency of images taking into account the specifics of the transport images. The best performance is achieved at low and medium traffic intensity. At the same time, the algorithm computational complexity is reduced by 4-5 times while maintaining the quality of the restored video streams in comparison with codec standards. Practical Relevance. The proposed algorithms based on adaptive cosine transform give the possibility: firstly, to decrease the transmission rate of the transport sequences by 2–2.5 times compared to the classical cosine transform with the size of cubes equal to (8 × 8 × 8); secondly, to reduce significantly computational costs in the implementation of transport video surveillance systems in real time compared to standard codecs. The results of the work can be recommended to specialists in the field of video information encoding and decoding to provide the necessary transmission speed at a given distortion level.

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