The efficiency of threshold decoding of non-binary self-orthogonal convolutional codes in the communication channel with additive white Gaussian noise with the correction of t ( t ≥ 1) symbolic errors is considered. The characters or elements of the code sequence (CS) used by the self-triggered convolutional code with the code transmission rate equaled R = k 0 / n 0 = 1/2 are the elements of the final field GF ( a i ), i ≥ 2. The number of erroneous code symbols and their positions in the received CS on the length of the code constraint equaled n a = ( m + 1)∙ n 0 binary symbols is determined by the decoder based on the structure of the generated syndrome sequence (SS) S ( x ) = { S 0 , S 1 , …, S N }, depending on the structure of errors in the communication channel and the structure of the generating polynomials: m is maximum degree of the generating polynomials. It has been established that while preserving the merits of the threshold decoding algorithm, an increase in i ( i ≥ 2) times the multiplicity of corrected errors is ensured by binary self-orthogonal codes with an equal transfer rate of codes.

Some algorithms of probabilistic coding of bits series lengths based on the confirmation of bit repetition and differing with an explicit or implicit indication of the length of the repetition symbol are proposed. The efficiency of these algorithms using for lossless compression of bit planes of halftone images is investigated.

It's proposed an algorithm for probabilistic coding of the lengths of series with confirmation of repetition and preliminary sorting. The efficiency of this algorithm using for compression without loss of bit planes of halftone images is investigated.

Algorithms of sector localization and parameterization of reference points in the wavelet domain for aligning the overlapping images based on the utility of corner coefficients to describe the contour structure in the vicinity of the reference point are proposed. It is shown that these algorithms compared to the methods of SIFT and SURF provide a reduction in the computational complexity of localization and parameterization of reference points and increase the stability of their descriptors at parallax.