Vol. 14, no.2, 2022


Application of the Interpolation Method of Sequential Computation of the Fourier Spectrum to Sparse Images

Alexander V. Kokoshkin, Evgeny P. Novichikhin

Kotelnikov Institute of Radioengineering and Electronics of RAS, Fryazinsky branch, http://fireras.su/
Fryazino 141190, Moscow region, Russian Federation
E-mail: shvarts65@mail.ru, epnov@mail.ru

Received April 28, 2022, peer-reviewed May 05, 2022, accepted May 12, 2022

Abstract:: Interpolation Method of Sequential Computation of the Fourier spectrum (IMSCS) is used for the reconstruction of sparse digital images. Peculiarities of application of the method are investigated on different types of images with a large sparseness (from 90 to 99 percent of information is missing). To improve the work of IMSCS, when considering the large sparseness of the initial data, its totality includes a procedure for additional iterative refinement of each of the restored harmonics of the spatial spectrum. As an alternative approach, to determine the analysis by objective criteria, spline interpolation is chosen. The conducted study allows us to conclude that it is fundamentally possible to use IMSCS to restore rarefied images, both for the reconstruction of gaps, and in order to reduce the amount of data.

Keywords: remote sensing, sparse digital images, image processing, interpolation method of sequential computation of the Fourier spectrum

UDC 621.397

RENSIT, 2022, 14(2):165-174e DOI: 10.17725/rensit.2022.14.165.

Full-text electronic version of this article - web site http://en.rensit.ru/vypuski/article/444/14(2)165-174e.pdf