Retouching and restoration of missing image fragments by means of the iterative calculation of their spectra

Abstract

This paper discusses the use of the interpolation method for the sequential calculation of the Fourier spectrum (IMSCS) for retouching and restoration of missing (shaded) image fragments. The proposed approach can be used with any form of a missing image fragment. Such image processing can give good results even at a significantly high percentage of missing image fragments. The method of digital virtual image reconstruction proposed here is strictly based on a scientific approach; as the source data, it uses all the data available (the image itself is the object to be recovered). Therefore, it is free from the human factor, because of which subjective changes can be introduced in the image under processing. The results presented indicate a significant increase in the quality of digital images (increasing the information content), which can offer helpful auxiliary tools for professionals using these images for their practical purposes.

Restoring Missing Fragments of a Distorted Image Due to Defocusing or Blur of a Known Hardware Function

“…We believe that this happens because MIPVS, working in the frequency domain, uses all available data (the entire original image), while spline or linear interpolation, performing actions in the spatial domain, operates with information only about the edges of the gap. Thus, MIPVS not only retouches, but also tries to reconstruct the lost data [14,15,16,19].…”

“…4 interpolation, performing actions in the spatial domain, operates with information about the edges of the gap. Thus, MIPVS not only retouches, but also tries to reconstruct the lost data [14,15,16,19]. Some fluctuations in the curves in Fig.…”

“…In [14], we have developed a method for interpolation of a sequentially calculated Fourier spectrum (MIPVS), which is capable of filling in gaps of arbitrary shape. In works [15][16][17][18][19], possible areas of application of MIPVS are shown and a comparative analysis of the methods used to fill gaps in images was carried out.…”

Elimination of Defects in Mammograms Caused by a Malfunction of the Device Matrix

“…Algorithms based on the Fourier spectrum, performing phase, and amplitude reconstruction are also used [ 24 ]. The main idea of this method is the sequential calculation of the image spectrum, with changes made only to the defect without changing the rest of the image [ 25 , 26 , 27 ].…”