Compressive coded aperture imaging

Nonlinear image reconstruction based upon sparse representations of images has recently received widespread attention with the emerging framework of compressed sensing (CS). This theory indicates that, when feasible, judicious selection of the type of distortion induced by measurement systems may dramatically improve our ability to perform image reconstruction. However, applying compressed sensing theory to practical imaging systems poses a key challenge: physical constraints typically make it infeasible to actually measure many of the random projections described in the literature, and therefore, innovative and sophisticated imaging systems must be carefully designed to effectively exploit CS theory. In video settings, the performance of an imaging system is characterized by both pixel resolution and field of view. In this work, we propose compressive imaging techniques for improving the performance of video imaging systems in the presence of constraints on the focal plane array size...

• Type: Conference
• Year: 2009
• Where: CIMAGING
• Authors: Roummel F. Marcia, Zachary T. Harmany, Rebecca Willett
• Keywords: CIMAGING 2008, CIMAGING 2009, Compressed Sensing, Focal Plane Array, Imaging Systems