title: Characterization of a compressive imaging system using laboratory and natural light scenes.
abstract: Compressive imagers acquire images, or other optical scene information, by a series of spatially filtered intensity measurements, where the total number of measurements required depends on the desired image quality. Compressive imaging (CI) offers a versatile approach to optical sensing which can improve size, weight, and performance (SWaP) for multispectral imaging or feature-based optical sensing. Here we report the first (to our knowledge) systematic performance comparison of a CI system to a conventional focal plane imager for binary, grayscale, and natural light (visible color and infrared) scenes. We generate 1024×1024 images from a range of measurements (0.1%-100%) acquired using digital (Hadamard), grayscale (discrete cosine transform), and random (Noiselet) CI basis sets. Comparing the outcome of the compressive images to conventionally acquired images, each made using 1% of full sampling, we conclude that the Hadamard Transform offered the best performance and yielded images with comparable aesthetic quality and slightly higher spatial resolution than conventionally acquired images.
authors.affiliation: Photonic Systems Integration Laboratory, Electrical Engineering Department, University of California at San Diego, 9500 Gilman Dr., La Jolla, California 92093, USA. sjolivas@ucsd.edu
authors.forename: Stephen J
authors.initials: SJ
authors.lastname: Olivas
authors.forename: Yaron
authors.initials: Y
authors.lastname: Rachlin
authors.forename: Lydia
authors.initials: L
authors.lastname: Gu
authors.forename: Brian
authors.initials: B
authors.lastname: Gardiner
authors.forename: Robin
authors.initials: R
authors.lastname: Dawson
authors.forename: Juha-Pekka
authors.initials: JP
authors.lastname: Laine
authors.forename: Joseph E
authors.initials: JE
authors.lastname: Ford
mesh_terms: D016477:Artifacts; D044962:Data Compression; D005898:Glass / Q000737:chemistry; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D007259:Infrared Rays; D008029:Lighting / Q000295:instrumentation* / Q000379:methods; D055095:Optics and Photonics; D010363:Pattern Recognition, Automated; D010781:Photography / Q000295:instrumentation* / Q000379:methods