Probability of correct reconstruction in compressive spectral imaging

Coded Aperture Snapshot Spectral Imaging (CASSI) systems capture the 3-dimensional (3D) spatio-spectral information of a scene using a set of 2-dimensional (2D) random coded Focal Plane Array (FPA) measurements. A compressed sensing reconstruction algorithm is then used to recover the underlying spatio-spectral 3D data cube. The quality of the reconstructed spectral images depends exclusively on the CASSI sensing matrix, which is determined by the statistical structure of the coded apertures. The Restricted Isometry Property (RIP) of the CASSI sensing matrix is used to determine the probability of correct image reconstruction and provides guidelines for the minimum number of FPA measurement shots needed for image reconstruction. Further, the RIP can be used to determine the optimal structure of the coded projections in CASSI. This article describes the CASSI optical architecture and develops the RIP for the sensing matrix in this system. Simulations show the higher quality of spectral image reconstructions when the RIP property is satisfied. Simulations also illustrate the higher performance of the optimal structured projections in CASSI.

• Autores: Pinilla, Samuel Eduardo; Vargas García, Héctor Miguel; Arguello Fuentes, Henry
• Tipo de recurso: Article of journal
• Fecha de publicación: 2016
• Institución: Universidad Nacional de Colombia
• Repositorio: Universidad Nacional de Colombia
• Idioma: spa
• OAI Identifier: oai:repositorio.unal.edu.co:unal/67619
• Acceso en línea: https://repositorio.unal.edu.co/handle/unal/67619; http://bdigital.unal.edu.co/68648/
• Palabra clave: 62 Ingeniería y operaciones afines / Engineering; Restricted Isometry Property; RIP; CASSI; compressive sensing; spectral imaging; coded aperture; Propiedad Isométrica Restrictiva; RIP; CASSI; muestreo compresivo; imágenes hiperespectrales; códigos de apertura.
• Rights: openAccess
• License: Atribución-NoComercial 4.0 Internacional