Compressive Sensing (CS) can alleviate the sensing effort involved in the acquisition of three dimensional image (3D) data. The most common CS sampling schemes employ uniformly random sampling because it is universal, thus it is applicable to almost any signals. However, by considering general properties of images and properties of the acquisition mechanism, it is possible to design random sampling schemes with variable density that have improved CS performance. We have introduced the concept of non-uniform CS random sampling a decade ago for holography. In this paper we overview the non-uniform CS random concept evolution and application for coherent holography, incoherent holography and for 3D LiDAR imaging.
|State||Published - 1 Jan 2019|
|Event||Three-Dimensional Imaging, Visualization, and Display 2019 - Baltimore, United States|
Duration: 15 Apr 2019 → 16 Apr 2019
|Conference||Three-Dimensional Imaging, Visualization, and Display 2019|
|Period||15/04/19 → 16/04/19|
- Compressive sensing
- variable random sensing