We opened the year with the theme of “embracing interdisciplinarity,” emphasizing the fact that signal processing naturally builds bridges across different domains and disciplines. The front cover image of an organic bridge across mature trees giving birth to a sapling helped convey our message. After two special issues (two parts of one special issue), we come back to you with an issue comprised of feature articles and columns, which all reinforce the message in our first issue of 2024.

In the first issue of 2024, we introduced the new lead editorial team of IEEE Signal Processing Magazine ( SPM ), composed of our four area editors. Their terms started with mine this January, and they oversee the Society e-newsletter and the three main components of our magazine: feature articles, special issues, and columns and forum articles.

Hypercomplex signal and image processing extends upon conventional methods by using hypercomplex numbers in a unified framework for algebra and geometry. The special issue is divided into two parts and is focused on current advances and applications in computational signal and image processing in the hypercomplex domain.

Hypercomplex signal processing (HSP) provides state-of-the-art tools to handle multidimensional signals by harnessing the intrinsic correlation of the signal dimensions through Clifford algebra. Recently, the hypercomplex representation of the phase retrieval (PR) problem, wherein a complex-valued signal is estimated through its intensity-only projections, has attracted significant interest.

Vector-valued signals are crucial in science and engineering. The evolving field of hypercomplex signal processing, particularly quaternion algebra, offers a concise and natural approach to handling vectorial data. In multicomponent seismology, for instance, vector-valued signal processing finds a natural fit that has been exploited in several applications.