invited keynote

Abstract: Many fields of science and technology face an ever-growing accumulation of “data”, such as signals, images, video, or biomedical data volumes. As a result, many techniques and algorithms, such as principal component analysis, clustering or random projection methods, have been devised to summarize these objects in reduced representations while preserving key information in this compression.

(joint work with T. Feuillen) Abstract: In this talk, we consider the estimation of a sparse (or low-complexity) signal from the phase of complex random measurements, a “phase-only compressive sensing” (PO-CS) scenario.

Abstract: Fourier Transform Interferometry (FTI) is an appealing Hyperspectral (HS) imaging modality for applications demanding high spectral resolution. In fluorescence microscopy (FM), the effective spectral resolution is, however, limited by the durability (or photobleaching) of biological elements when exposed to the illuminating light.