Search results for "Compressed sensing"
showing 4 items of 14 documents
Optical encryption with compressive ghost imaging
2011
Ghost imaging (GI) is a novel technique where the optical information of an object is encoded in the correlation of the intensity fluctuations of a light source. Computational GI (CGI) is a variant of the standard procedure that uses a single bucket detector. Recently, we proposed to use CGI to encrypt and transmit the object information to a remote party [1]. The optical encryption scheme shows compressibility and robustness to eavesdropping attacks. The reconstruction algorithm provides a relative low quality images and requires high acquisitions times. A procedure to overcome such limitations is to combine CGI with compressive sampling (CS), an advanced signal processing theory that expl…
Introduction to Digital Signal Processing
2018
Signal processing deals with the representation, transformation, and manipulation of signals and the information they contain. Typical examples include extracting the pure signals from a mixture observation (a field commonly known as deconvolution) or particular signal (frequency) components from noisy observations (generally known as filtering). This chapter outlines the basics of signal processing and then introduces the more advanced concepts of time‐frequency and time‐scale representations, as well as emerging fields of compressed sensing and multidimensional signal processing. When moving to multidimensional signal processing, a modern approach is taken from the point of view of statis…
SNAPSHOT SPECTRAL AND COLOR IMAGING USING A REGULAR DIGITAL CAMERA WITH A MONOCHROMATIC IMAGE SENSOR
2017
Spectral imaging (SI) refers to the acquisition of the three-dimensional (3D) spectral cube of spatial and spectral data of a source object at a limited number of wavelengths in a given wavelength range. Snapshot spectral imaging (SSI) refers to the instantaneous acquisition (in a single shot) of the spectral cube, a process suitable for fast changing objects. Known SSI devices exhibit large total track length (TTL), weight and production costs and relatively low optical throughput. We present a simple SSI camera based on a regular digital camera with (i) an added diffusing and dispersing phase-only static optical element at the entrance pupil (diffuser) and (ii) tailored compressed sensing…
Snapshot Spectral Imaging
2018
This chapter describes an application of the spline-based wavelet frames to the spectral imaging. It presents a method that enables to convert a regular digital camera into a snapshot spectral imager by equipping the camera with a dispersive diffuser and with a compressed sensing-based algorithm for digital processing. The method relies on the assumption that typical images can be sparsely represented in the frame domain. The solution is found from the constrained \(l_{1}\) minimization of a functional by Bregman iterations. Results of optical experiments are reported. The chapter is based on the paper (Golub et al., Appl. Opt. 55, 432–443, (2016), [11]).