DD-Net: spectral imaging from a monochromatic dispersed and diffused snapshot.

We propose a snapshot spectral imaging method for the visible spectral range using a single monochromatic camera equipped with a two-dimensional (2D) binary-encoded phase diffuser placed at the pupil of the imaging lens and by resorting to deep learning (DL) algorithms for signal reconstruction. While spectral imaging was shown to be feasible using two cameras equipped with a single, one-dimensional (1D) binary diffuser and compressed sensing (CS) algorithms [Appl. Opt.59, 7853 (2020).APOPAI0003-693510.1364/AO.395541], the suggested diffuser design expands the optical response and creates optical spatial and spectral encoding along both dimensions of the image sensor. To recover the spatial and spectral information from the dispersed and diffused (DD) monochromatic snapshot, we developed novel DL algorithms, dubbed DD-Nets, which are tailored to the unique response of the optical system, which includes either a 1D or a 2D diffuser. High-quality reconstructions of the spectral cube in simulation and lab experiments are presented for system configurations consisting of a single monochromatic camera with either a 1D or a 2D diffuser. We demonstrate that the suggested system configuration with the 2D diffuser outperforms system configurations with a 1D diffuser that utilize either DL-based or CS-based algorithms for the reconstruction of the spectral cube.

Design of binary-phase diffusers for a compressed sensing snapshot spectral imaging system with two cameras.

We propose designs of pupil-domain optical diffusers for a snapshot spectral imaging system using binary-phase encoding. The suggested designs enable the creation of point-spread functions with defined optical response, having profiles that are dependent on incident wavefront wavelength. This efficient combination of dispersive and diffusive optical responses enables us to perform snapshot spectral imaging using compressed sensing algorithms while keeping a high optical throughput alongside a simple fabrication process. Experimental results are reported.

Dual-camera snapshot spectral imaging with a pupil-domain optical diffuser and compressed sensing algorithms.

We propose a snapshot spectral imaging method for the visible spectral range using two digital cameras placed side-by-side: a regular red-green-blue (RGB) camera and a monochromatic camera equipped with a dispersive diffractive diffuser placed at the pupil of the imaging lens. While spectral imaging was shown to be feasible using a single monochromatic camera with a pupil diffuser [Appl. Opt.55, 432 (2016)APOPAI0003-693510.1364/AO.55.000432], adding an RGB camera provides more spatial and spectral information for stable reconstruction of the spectral cube of a scene. Results of optical experiments confirm that the combined data from the two cameras relax the complexity of the underdetermined reconstruction problem and improve the reconstructed image quality obtained using compressed sensing-based algorithms.

Compressed sensing snapshot spectral imaging by a regular digital camera with an added optical diffuser.

We propose a spectral imaging method that allows a regular digital camera to be converted into a snapshot spectral imager by equipping the camera with a dispersive diffuser and with a compressed sensing-based algorithm for digital processing. Results of optical experiments are reported.

Spectral multiplexing method for digital snapshot spectral imaging.

We propose a spectral imaging method for piecewise "macropixel" objects, which allows a regular digital camera to be converted into a digital snapshot spectral imager by equipping the camera with only a disperser and a demultiplexing algorithm. The method exploits a "multiplexed spectrum" intensity pattern, i.e., the superposition of spectra from adjacent different image points, formed on the image sensor of the digital camera. The spatial image resolution is restricted to a macropixel level in order to acquire both spectral and spatial data (i.e., an entire spectral cube) in a single snapshot. Results of laboratory experiments with a special macropixel object image, composed of small, spatially uniform squares, provide to our knowledge a first verification of the proposed spectral imaging method.

A new family of spline-based biorthogonal wavelet transforms and their application to image compression.

In this paper. we design a new family of biorthogonal wavelet transforms and describe their applications to still image compression. The wavelet transforms are constructed from various types of interpolatory and quasiinterpolatory splines. The transforms use finite impulse response and infinite impulse response filters that are implemented in a fast lifting mode.