Compressive spectral imaging Conference Paper uri icon

abstract

  • Compressive sensing techniques brought numerous advantages to the spectral imaging arena, such as reduction of the acquisition time, reduction of the captured data volume, reduction of the system size, among many others. In this talk we shall overview the main compressive spectral imaging approaches proposed during the last decade and compare their performances. The theory of Compressive Sensing, aka Compressed Sampling (CS), was introduced a little more than a decade ago and it has generated a great deal of attention in a various fields, including applied mathematics, computer science, physics, engineering and, in fact, almost every field that involves data sensing. The CS theory offers a much more economical sensing framework, in terms of number of samples, compared to the traditional Shannon-Nyquist paradigm. The CS theory has found natural application for optical …

publication date

  • January 1, 2017