Single-pixel imaging with Fourier filtering: Application to vision through scattering media

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this recordWe present a novel approach for imaging through scattering media that combines the principles of Fourier spatial filtering and single-pixel imaging. We compare the performance of our single-pixel imaging setup with that of a conventional system. First, we show that a single-pixel camera does not reduce the frequency content of the object, when a small pinhole is used as a low-pass filter at the detection side. Second, we show that the introduction of Fourier gating improves the contrast of imaging through scattering media in both optical systems. We conclude that single-pixel imaging fits better than conventional imaging on imaging through scattering media by the Fourier gating

Signal-to-noise ratio of single-pixel cameras based on photodiodes

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this recordSingle-pixel cameras have been successfully used in different imaging applications in the last years. One of the key elements affecting the quality of these cameras is the photodetector. Here, we develop a numerical model of a single-pixel camera, which takes into account not only the characteristics of the incident light but also the physical properties of the detector. In particular, our model considers the photocurrent, the dark current, the photocurrent shot noise, the dark-current shot noise, and the Johnson–Nyquist (thermal) noise of the photodiode used as a light detector. The model establishes a clear relationship between the electric signal and the quality of the final image. This allows us to perform a systematic study of the quality of the image obtained with single-pixel cameras in different contexts. In particular, we study the signal-to-noise ratio as a function of the optical power of the incident light, the wavelength, and the photodiode temperature. The results of the model are compared with those obtained experimentally with a single-pixel camera

Transillumination imaging through biological tissue by single-pixel detection

One challenge that has long held the attention of scientists is that of clearly seeing objects hidden by turbid media, as smoke, fog or biological tissue, which has major implications in fields such as remote sensing or early diagnosis of diseases. Here, we combine structured incoherent illumination and bucket detection for imaging an absorbing object completely embedded in a scattering medium. A sequence of low-intensity microstructured light patterns is launched onto the object, whose image is accurately reconstructed through the light fluctuations measured by a single-pixel detector. Our technique is noninvasive, does not require coherent sources, raster scanning nor time-gated detection and benefits from the compressive sensing strategy. As a proof of concept, we experimentally retrieve the image of a transilluminated target both sandwiched between two holographic diffusers and embedded in a 6mm-thick sample of chicken breast

Roadmap on digital holography [Invited]

This Roadmap article on digital holography provides an overview of a vast array of research activities in the field of digital holography. The paper consists of a series of 25 sections from the prominent experts in digital holography presenting various aspects of the field on sensing, 3D imaging and displays, virtual and augmented reality, microscopy, cell identification, tomography, label-free live cell imaging, and other applications. Each section represents the vision of its author to describe the significant progress, potential impact, important developments, and challenging issues in the field of digital holography

Giga-voxel multispectral time-resolved imaging with single-pixel detection and data fusion

We present a technique for multispectral fluorescence lifetime imaging with high spatial resolution by combining both single-pixel and data fusion imaging techniques. The system relies on the combined use of three different sensors: two SP cameras capturing multispectral and time-resolved information, and a conventional 2D array detector capturing high spatial resolution images The resultant giga-voxel 4D hypercube is acquired in a fast manner measuring only 0.03% of the dataset. The fusion procedure is done by solving a regularization problem which is efficiently solved via gradient descent. The system can be used to identify fluorophore species

Computational imaging with a balanced detector

Single-pixel cameras allow to obtain images in a wide range of challenging scenarios, including broad regions of the electromagnetic spectrum and through scattering media. However, there still exist several drawbacks that single-pixel architectures must address, such as acquisition speed and imaging in the presence of ambient light. In this work we introduce balanced detection in combination with simultaneous complementary illumination in a single-pixel camera. This approach enables to acquire information even when the power of the parasite signal is higher than the signal itself. Furthermore, this novel detection scheme increases both the frame rate and the signal-to-noise ratio of the system. By means of a fast digital micromirror device together with a low numerical aperture collecting system, we are able to produce a live-feed video with a resolution of 64 × 64 pixels at 5 Hz. With advanced undersampling techniques, such as compressive sensing, we can acquire information at rates of 25 Hz. By using this strategy, we foresee real-time biological imaging with large area detectors in conditions where array sensors are unable to operate properly, such as infrared imaging and dealing with objects embedded in turbid media