English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Nowadays the systems of information extraction that include spatial apertures of signal sensors are widely used in robotics, for the remote exploration of Earth, in medicine, geology and in other fields. Such sensors generate dynamic arrays of data having the proper feature which is in their space-time correlation and due to which they can be represented in the form of multidimensional images (Gonzalez & Woods, 2002). When producing algorithmic software for the processing of such images it is necessary to take into account the dynamics of the scene to be observed, distortions caused by signal propagation environment, spatial movements of signal sensors and imperfection of their construction. The influence of the mentioned factors can be described through mathematical models of space-time deformations of multidimensional grids with the specified images. The estimation of varying parameters of image spatial deformations is required not only in robotics applications, but also to solve a wide range of other problems, for example, for automated search of a fragment on the image, navigational tracking of mobile object course in the conditions of limited visibility, combination of multiregion images at remote explorations of Earth, in medical research. A lot of scientific calls for papers are devoted to different problems of image sequence space-time deformation parameters estimation (the bibliography is given, for example, in (Tashlinskii, 2000)). This chapter is devoted to one of the directions of solving this type of problems, where pseudogradient estimation of image interframe geometrical deformations (IIGDs) is considered. Let us assume that the model of IIGDs is defined to an accuracy of a parameters vector α and the estimation quality criterion is formulated in terms of some functional ) J(α

Pseudogradient Estimation of Digital Images Interframe Geometrical Deformations