Single-pixel imaging via compressive sampling

Abstract

Humans are visual animals, and imaging sensors that extend our reachcameras-have improved dramatically in recent times thanks to the introduction of CCD and CMOS digital technology. Consumer digital cameras in the megapixel range are now ubiquitous thanks to the happy coincidence that the semiconductor material of choice for large-scale electronics integration (silicon) also happens to readily convert photons at visual wavelengths into electrons. On the contrary, imaging at wavelengths where silicon is blind is considerably more complicated, bulky, and expensive. Thus, for comparable resolution, a US$500 digital camera for the visible becomes a US$50,000 camera for the infrared.In this article, we present a new approach to building simpler, smaller, and cheaper digital cameras that can operate efficiently across a much broader spectral range than conventional silicon-based cameras. Our approach fuses a new camera architecture

Single-pixel imaging by means of Fourier spectrum acquisition

“…Later single-pixel imaging techniques that use a classical light source to exploit Helmholtz reciprocity 3 have been proposed. These techniques include GI [4][5][6][7] , computational imaging [8][9][10][11] and dual photography 1,12,13 . These single-pixel techniques can potentially capture a scene with indirect measurement where detectors sample the indirect light only.…”

“…For example, a commercial digital projector displays the patterns in 24-bit mode; a programmable digital micromirror device (DMD) that displays the patterns in binary mode, and the defocusing 17 or the spatial filtering approach 16 is employed to make the resulting patterns sinusoidal; two coherent plane waves intersect at an angle to form a sinusoid pattern. What is more, the technique presented here is a compressive sampling 4,[8][9][10]12,13 like approach. It applies measurement in the Fourier domain, where most natural images are sparse.…”

Compressive microscopic imaging with “positive–negative” light modulation

“…The new reviewer suggest that the manuscript can be published only after we clear up the picture and the presentation of "ghost imaging", and present it as the compressive imaging aspect only. However, we think that the only difference between single-pixel compressive imaging [20] and computational GI [15] was that the spatial modulator was placed behind the object instead of in front. Furthermore, the GI community has already employed CS to obtain compressed ghost images (see in [22,23,25,26], Opt.…”

“…This modified technique was called computational GI by Shapiro [15] and demonstrated by Bromberg et al [16]. But a few months earlier, the same optical protocol had been proposed and demonstrated independently by Baraniuk et al, who combined it with the compressive sampling (compressed sensing) algorithm [17][18][19], and called it "Single-pixel imaging via compressive sampling" [20,21]. The only difference between singlepixel compressed sensing (CS) imaging and computational GI was that the spatial modulator was placed behind the object instead of in front.…”

Distributed compressed sensing of Hyperspectral images via blind source separation

“…If a data x ∈ R N has a sparse or compressible representation in some basis, CS is an alternative to the Shannon/Nyquist sampling, which reduces the number M of measurements required to acquire the data x i.e., M < N . In practice, the CS measurements can be done using the single-pixel hyperspectral camera (SPHC) [5].…”