Three dimensional computational imaging with single-pixel detectors

Computational imaging with single-pixel detectors utilises spatial correlation of light to obtain images. A series of structured illumination is generated using a spatial light modulator to encode the spatial information of an object. The encoded object images are recorded as total intensities with no spatial information by a single-pixel detector. These intensities are then sent to correlate with their corresponding illumination structures to derive an image. This correlation imaging method was first recognised as a quantum imaging technique called ghost imaging (GI) in 1995. Quantum GI uses the spatial correlation of entangled photon pairs to form images and was later demonstrated also by using classical correlated light beams. In 2008, an adaptive classical GI system called computational GI which employed a spatial light modulator and a single-pixel detector was proposed. Since its proposal, this computational imaging technique received intensive interest for this potential application. The aim of the work in this thesis was to improve this new imaging technique into a more applicable stage. Our contribution mainly includes three aspects. First an advanced reconstruction algorithm called normalised ghost imaging was developed to improve the correlation efficiency. By normalising the object intensity with a reference beam, the reconstruction single-to-noise ratio can be increased, especially for a more transmissive object. In the second work, a computational imaging scheme adapted from computational GI was designed by using a digital light projector for structured illumination. Compared to a conventional computational GI system, the adaptive system improved the reconstruction efficiency significantly. And for the first time, correlation imaging using structured illumination and single-pixel detection was able to image a 3 dimensional reflective object with reasonable details. By using several single-pixel detectors, the system was able to retrieve the 3 dimensional profile of the object. In the last work, effort was devoted to increase the reconstruction speed of the single-pixel imaging technique, and a fast computational imaging system was built up to generate real-time single-pixel videos

3D Computational Ghost Imaging

Computational ghost imaging retrieves the spatial information of a scene using a single pixel detector. By projecting a series of known random patterns and measuring the back reflected intensity for each one, it is possible to reconstruct a 2D image of the scene. In this work we overcome previous limitations of computational ghost imaging and capture the 3D spatial form of an object by using several single pixel detectors in different locations. From each detector we derive a 2D image of the object that appears to be illuminated from a different direction, using only a single digital projector as illumination. Comparing the shading of the images allows the surface gradient and hence the 3D form of the object to be reconstructed. We compare our result to that obtained from a stereo- photogrammetric system utilizing multiple high resolution cameras. Our low cost approach is compatible with consumer applications and can readily be extended to non-visible wavebands.Comment: 13pages, 4figure

Simultaneous real-time visible and infrared video with single-pixel detectors

Conventional cameras rely upon a pixelated sensor to provide spatial resolution. An alternative approach replaces the sensor with a pixelated transmission mask encoded with a series of binary patterns. Combining knowledge of the series of patterns and the associated filtered intensities, measured by single-pixel detectors, allows an image to be deduced through data inversion. In this work we extend the concept of a ‘single-pixel camera’ to provide continuous real-time video at 10 Hz , simultaneously in the visible and short-wave infrared, using an efficient computer algorithm. We demonstrate our camera for imaging through smoke, through a tinted screen, whilst performing compressive sampling and recovering high-resolution detail by arbitrarily controlling the pixel-binning of the masks. We anticipate real-time single-pixel video cameras to have considerable importance where pixelated sensors are limited, allowing for low-cost, non-visible imaging systems in applications such as night-vision, gas sensing and medical diagnostics

Fast full-color computational imaging with single-pixel detectors

Single-pixel detectors can be used as imaging devices by making use of structured illumination. These systems work by correlating a changing incident light field with signals measured on a photodiode to derive an image of an object. In this work we demonstrate a system that utilizes a digital light projector to illuminate a scene with approximately 1300 different light patterns every second and correlate these with the back scattered light measured by three spectrally-filtered single-pixel photodetectors to produce a full-color high-quality image in a few seconds of data acquisition. We utilize a differential light projection method to self normalize the measured signals, improving the reconstruction quality whilst making the system robust to external sources of noise. This technique can readily be extended for imaging applications at non-visible wavebands

Single-pixel three-dimensional imaging with time-based depth resolution

Time-of-flight three-dimensional imaging is an important tool for applications such as object recognition and remote sensing. Conventional time-of-flight three-dimensional imaging systems frequently use a raster scanned laser to measure the range of each pixel in the scene sequentially. Here we show a modified time-of-flight three-dimensional imaging system, which can use compressed sensing techniques to reduce acquisition times, whilst distributing the optical illumination over the full field of view. Our system is based on a single-pixel camera using short-pulsed structured illumination and a high-speed photodiode, and is capable of reconstructing 128 × 128-pixel resolution three-dimensional scenes to an accuracy of ~3 mm at a range of ~5 m. Furthermore, by using a compressive sampling strategy, we demonstrate continuous real-time three-dimensional video with a frame-rate up to 12 Hz. The simplicity of the system hardware could enable low-cost three-dimensional imaging devices for precision ranging at wavelengths beyond the visible spectrum

Normalized ghost imaging

We present an experimental comparison between different iterative ghost imaging algorithms. Our experimental setup utilizes a spatial light modulator for generating known random light fields to illuminate a partially-transmissive object. We adapt the weighting factor used in the traditional ghost imaging algorithm to account for changes in the efficiency of the generated light field. We show that our normalized weighting algorithm can match the performance of differential ghost imaging

Bis[μ-bis­(diphenyl­phosphino)methane-κ2 P:P′]bis­[(4-toluene­sulfonato-κO)silver(I)] monohydrate

The title complex, [Ag2(C7H7O3S)2(C25H22P2)2]·H2O, was obtained by the reaction of silver toluene­sulfonate with diphenyl­phosphinomethane (dppm) in acetonitrile. There are two unique half-mol­ecules of the complex in the asymmetric unit, together with one water mol­ecule, which is disordered over two positions with site occupancy factors of 0.6 and 0.4. In each centrosymmetric neutral dimeric mol­ecule, two Ag atoms are bridged by a pair of dppm ligands to give an eight-membered Ag2P4C2 ring with a distorted AgOP2 trigonal–planar environment. The Ag—Ag distances of 2.9215 (9) and 3.027 (1) Å indicate a direct bonding inter­action

Clinical biomarker profiles reveals gender differences and mortality factors in sepsis

BackgroundSepsis is a major contributor to global morbidity and mortality, affecting millions each year. Notwithstanding the decline in sepsis incidence and mortality over decades, gender disparities in sepsis outcomes persist, with research suggesting higher mortality rates in males.MethodsThis retrospective study aims to delineate gender-specific clinical biomarker profiles impacting sepsis progression and mortality by examining sepsis cases and related clinical data from the past three years. Propensity score matching was used to select age-matched healthy controls for comparison.ResultsAmong 265 sepsis patients, a significantly higher proportion were male (60.8%, P<0.001). While mortality did not significantly differ by gender, deceased patients were significantly older (mean 69 vs 43 years, P=0.003), more likely to have hypertension (54% vs 25%, P=0.019), and had higher SOFA scores (mean ~10 vs 4, P<0.01) compared to survivors. Principal Component Analysis (PCA) showed clear separation between sepsis patients and healthy controls. 48 serum biomarkers were significantly altered in sepsis, with Triiodothyronine, Apolipoprotein A, and Serum cystatin C having the highest diagnostic value by ROC analysis. Gender-stratified comparisons identified male-specific (e.g. AFP, HDLC) and female-specific (e.g. Rheumatoid factor, Interleukin-6) diagnostic biomarkers. Deceased patients significantly differed from survivors, with 22 differentially expressed markers; Antithrombin, Prealbumin, HDL cholesterol, Urea nitrogen and Hydroxybutyrate had the highest diagnostic efficiency for mortality.ConclusionThese findings enhance our understanding of gender disparities in sepsis and may guide future therapeutic strategies. Further research is warranted to validate these biomarker profiles and investigate the molecular mechanisms underlying these gender differences in sepsis outcomes