Yaniv Oiknine

Ben-Gurion University of the Negev | bgu · Electro-Optics and Photonics Engineering

Spectroscopic imaging has been proved to be an effective tool for many applications in a variety of fields, such as biology, medicine, agriculture, remote sensing and industrial process inspection. However, due to the demand for high spectral and spatial resolution it became extremely challenging to design and implement such systems in a miniaturiz...

We present a new fast compressive spectroscopic technique based on the resonance spectrometric mechanism. This technique uses an appropriately designed Fabry-Perot resonator and a photo-sensor in order to acquire different multiplexed spectral modulations, from which the original signal is reconstructed using a compressive sensing reconstruction al...

In various applications, such as remote sensing and quality inspection, hyperspectral (HS) imaging is performed by spatially scanning an object. In this work, we present a new compressive hyperspectral imaging method that performs along-track scanning. The method relies on the compressive sensing miniature ultra-spectral imaging (CS-MUSI) system, w...

In this Letter, we present a method for hyperspectral imaging of three-dimensional objects. A compressive sensing approach is utilized to remedy the acquisition effort required to capture the large amount of data. The spectral dimension is compressively sensed by means of a liquid crystal-based encoder, and the volumetric data are captured using a...

Recently we introduced a hyperspectral compressive sensing scheme that uses separable projections in the spatial and spectral domains. The separable encoding schemes facilitates the optical implementation, reduces the computational burden dramatically, and storage requirements. Owing to these benefits we have been able to encode the hyperspectral c...

Significance: Hyperspectral microscopy grants the ability to characterize unique properties of tissues based on their spectral fingerprint. The ability to label and measure multiple molecular probes simultaneously provides pathologists and oncologists with a powerful tool to enhance accurate diagnostic and prognostic decisions. As the pathological...

In this paper, we present a new hyperspectral compact camera which is designed to have high spatial and spectral resolutions, to be vibrations tolerant, and to achieve state-of-the-art high optical throughput values compared to existing nanosatellite hyperspectral imaging payloads with space heritage. These properties make it perfect for airborne a...

Several hyperspectral (HS) systems based on compressive sensing (CS) theory have been presented to capture HS images with high accuracy and with a lower number of measurements than needed by conventional systems. However, the reconstruction of HS compressed measurements is time-consuming and commonly involves hyperparameter tuning per each scenario...

Liquid crystal phase retarders are utilized by photonic devices and imaging systems for various applications, such as tunable filtering, light modulation, polarimetric imaging, remote sensing and quality inspection. Due to technical difficulties in the manufacturing process, these phase retarders may suffer from spatial non-uniformities, which degr...

Compressive spectral imaging with spectral only encoding may exhibit several advantages over spatial-and-spectral encoding methods. We overview compressive spectral imaging systems that use modified Fabry-Perot resonators that perform only spectral encoding.

Hyperspectral (HS) imaging involves the sensing of a scene’s spectral properties, which are often redundant in nature. The redundancy of the information motivates our quest to implement Compressive Sensing (CS) theory for HS imaging. This article provides a review of the Compressive Sensing Miniature Ultra-Spectral Imaging (CS-MUSI) camera, its evo...

In this Letter, we present a new snapshot hyperspectral (HS) camera based on a multi-aperture design. The technique uses an array of modified Fabry–Perot resonators together with a lens array in order to acquire an array of spectrally multiplexed modulated sub-images. Then the original HS image is reconstructed using a compressive sensing reconstru...

The parametrization of light rays in form of light fields (LF) have become the standard and probably the most common way for the representation, analysis and processing of rays emitted from 3D objects or from 3D displays. Essentially, the LFs are 4D maps representing the spatial and angular distribution of the intensity of the rays. Nowadays, with...

Light fields are four-dimensional parametrizations of rays, extensively used for the representation of the rays emitted from three-dimensional objects. With the increasing availability of spectral imagers, conventional light fields can be augmented by the additional spectral information, yielding a five-dimensional ray parametrization referred to a...

The acquisition of hyperspectral (HS) image datacubes with available 2D sensor arrays involves a time consuming scanning process. In the last decade, several compressive sensing (CS) techniques were proposed to reduce the HS acquisition time. In this paper, we present a method for near-infrared (NIR) HS imaging which relies on our rapid CS resonato...

Compressive sensing techniques brought numerous advantages to the spectral imaging arena, such as reduction of the acquisition time, reduction of the captured data volume, reduction of the system size, among many others. In this talk we shall overview the main compressive spectral imaging approaches proposed during the last decade and compare their...

Recently we presented a Compressive Sensing Miniature Ultra-spectral Imaging System (CS-MUSI)1 . This system consists of a single Liquid Crystal (LC) phase retarder as a spectral modulator and a gray scale sensor array to capture a multiplexed signal of the imaged scene. By designing the LC spectral modulator in compliance with the Compressive Sens...

We review two compressive spectroscopy techniques based on modulation in the spectral domain that we have recently proposed. Both techniques achieve a compression ratio of approximately 10:1, however each with a different sensing mechanism. The first technique uses a liquid crystal cell as a tunable filter to modulate the spectral signal, and the s...

Compressive sensing theory was proposed to deal with the high quantity of measurements demanded by traditional hyperspectral systems. Recently, a compressive spectral imaging technique dubbed compressive sensing miniature ultraspectral imaging (CS-MUSI) was presented. This system uses a voltage controlled liquid crystal device to create multiplexed...

We overview the capability of a new compressive spectral imaging technique that we have recently introduced to capture spectral image datacubes that have giga entries by taking an order of magnitude less samples.

The theory of compressive sensing (CS) has opened up new opportunities in the field of imaging. However, its implementation in this field is often not straight-forward and the optical imaging system engineer encounters several hurdles on the way of compressive imaging (CI) realization. The principles of CI design may differ drastically from the pri...

Recently we introduced a Compressive Sensing Miniature Ultra-Spectral Imaging (CS-MUSI) system. The system is based on a single Liquid Crystal (LC) cell and a parallel sensor array where the liquid crystal cell performs spectral encoding. Within the framework of compressive sensing, the CS-MUSI system is able to reconstruct ultra-spectral cubes cap...

We overview the capability of a new compressive spectral imaging technique that we have recently introduced to capture spectral image datacubes that have giga entries by taking an order of magnitude less samples.

Recently we have proposed a new compressive spectral sensing method based on modulation in the spectral domain, without the need of diffractive or dispersive elements. Here, we expand the compressive sensing spectrometry to hyperspectral imaging.

In this paper we overview three hyperspectral compressive imaging methods that we have developed. The first method is an efficient extension of the single-pixel camera to include compressive spectrometry. The second method is an extension of a Radon-based compressive imaging technique to perform spectral sensing. The third method is based on a rece...

Hyperspectral imaging is a natural field for the implementation of compressive sensing because typical captured hyperspectral datacubes involve large amount of data which is also often very redundant. Compressive hypersepctral systems compress the hyperspectral data already in the acquisition step, thus remedy the severe storage and processing requ...