MODELING OF AN IMAGE PROCESSING SYSTEM BASED ON THE KHURGIN-YAKOVLEV REPRESENTATION

The article presents the development and modeling of an image processing system based on the application of the Khurgin-Yakovlev representation aimed at minimizing information loss while reducing the data volume. The study proposes a method for dividing the original signal into two frequency channels: the signal itself and its derivative. Both channels were decimated by a factor of 2, which reduced the volume of transmitted data by four times. At the restoration stage, synthesized optimal Khurgin-Yakovlev interpolation filters were used to compensate for distortions caused by decimation by minimizing the mean square error. For the first channel, bicubic interpolation was used, preserving the smoothness of low-frequency components, and for the second, a third-order Lanczos filter was used, aimed at accurately restoring high-frequency details.