Hypercomplex algebras for dictionary learning


This paper presents an application of hypercomplex algebras combined with dictionary learning for sparse representation of multichannel images. Two main representatives of hypercomplex algebras, Clifford algebras and algebras generated by the Cayley-Dickson procedure are considered. Related works reported quaternion methods (for color images) and octonion methods, which are applicable to images with up to 7 channels. We show that the current constructions cannot be generalized to dimensions above eight.

Early Proceedings of the AGACSE 2018 Conference
Srđan Lazendić
Doctoral researcher

My current research interests focus on Clifford algebra methods for efficient multidimensional data analysis and image processing. I am also interested in complex analysis, in particular Blaschke products and their properties.