SUMMARY
Actuality. Ensuring the efficiency and versatility of modern media for processing visual information requires the development ofvarious methods for the effective implementation of the discrete cosine transform. In accordance with the requirements of modernvideo standards, providing high-definition compressed visual information is achieved on the basis of adaptively block-dimensionaltransforms, which requires efficient computational schemes for the implementation of discrete cosine transform of variable dimensions.The purpose of the work is to create a generalized structural scheme for the efficient computation of an integer discrete cosinetransform on the basis of cyclic convolutions of dimensions equal to the integer power of two, which provides low computationalcomplexity and the possibility of using visual information compression systems on the basis of adaptively block-dimensional transforms.Method. The use of hashing arrays for efficient synthesis of algorithms and structure schemes for computing an integer discretecosine transform on the basis of cyclic convolutions is proposed.Results. The result of the study is the development of a generalized structural scheme for the implementation of an integer discretecosine transform of dimensions equal to the integer power of the two for the compression of visual information on the basis ofadaptively block-dimensional transforms.Conclusions. In the study, we apply the approach of bringing the basis of an integral discrete cosine transform to a set of left cyclicsubmatrices, which allows us to calculate transforms based on cyclic convolutions. The basic idea of using an appropriatemathematical apparatus is to use hashing arrays containing a brief description of the block-cyclic structure of the transform basis. Onthe basis of the received set of cyclic submatrices of the transform core, a generalized structural scheme for the effective implementationof an integer discrete cosine transform of small dimensions equal to an integer power of the two is developed. The computationof the corresponding set of cyclic convolutions and the combining of their results by the structural scheme ensures the implementationof adaptively block-dimensional transforms for compression of visual information.