Today is a reality that the novel coronavirus SARS-Cov-2 has become a global pandemic. For this reason, the study of real microscopic images of this coronavirus is of great importance, as it allows us to carry out a more precise research on it. However, as we pointed out in a former paper [1], many times these microscopic images present some blurring problems, which are always susceptible to be improved. The aim of this work is to carry out a theoretical analysis of the proposed algorithms to enhancement and segmentation of these microscopic images, which result important for the design and development of future algorithms before new epidemics.