Abstract
The work compares the work of sparse image interpolation methods such as: - interpolation method of sequential computation of the Fourier spectrum (IMSCS), the method of projections onto convex sets (projections onto convex sets, POCS), and the method of amplitude iterations (MAI). All calculations necessary for the reconstruction of sparse images are performed only on spatial spectra. As an example, an aerospace digital image is used, which is typical for the tasks of remote sensing of the earth's surface. A high degree of sparseness is modeled (90 percent of the information is missing). The effectiveness of the studied methods was carried out according to several objective criteria.
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