This article is cited in 7 papers

IMAGE PROCESSING, PATTERN RECOGNITION

Optimization of the multidimensional signal interpolator in a lower dimensional space

M. V. Gashnikov<sup>ab

a</sup> IPSI RAS – Branch of the FSRC “Crystallography and Photonics” RAS, Molodogvardeyskaya 151, 443001, Samara, Russia
^b Samara National Research University, Moskovskoye Shosse 34, 443086, Samara, Russia

Abstract: Adaptive multidimensional signal interpolators are developed. These interpolators take into account the presence and direction of boundaries of flat signal regions in each local neighborhood based on the automatic selection of the interpolating function for each signal sample. The selection of the interpolating function is performed by a parameterized rule, which is optimized in a parametric lower dimensional space. The dimension reduction is performed using rank filtering of local differences in the neighborhood of each signal sample. The interpolating functions of adaptive interpolators are written for the multidimensional, three-dimensional and two-dimensional cases. The use of adaptive interpolators in the problem of compression of multidimensional signals is also considered. Results of an experimental study of adaptive interpolators for real multidimensional signals of various types are presented.

Keywords: optimization, interpolation, multidimensional signal, dimension reduction, compression.

Received: 21.03.2019
Accepted: 14.05.2019

DOI: 10.18287/2412-6179-2019-43-4-653-660