FPGA-based architecture for hyperspectral endmember extraction

Hyperspectral instruments have been incorporated in satellite missions, providing data of high spectral resolution of the Earth. This data can be used in remote sensing applications, such as, target detection, hazard prevention, and monitoring oil spills, among others. In most of these applications, one of the requirements of paramount importance is the ability to give real-time or near real-time response. Recently, onboard processing systems have emerged, in order to overcome the huge amount of data to transfer from the satellite to the ground station, and thus, avoiding delays between hyperspectral image acquisition and its interpretation. For this purpose, compact reconfigurable hardware modules, such as field programmable gate arrays (FPGAs) are widely used. This paper proposes a parallel FPGA-based architecture for endmember’s signature extraction. This method based on the Vertex Component Analysis (VCA) has several advantages, namely it is unsupervised, fully automatic, and it works without dimensionality reduction (DR) pre-processing step. The architecture has been designed for a low cost Xilinx Zynq board with a Zynq-7020 SoC FPGA based on the Artix-7 FPGA programmable logic and tested using real hyperspectral data sets collected by the NASA’s Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS) over the Cuprite mining district in Nevada. Experimental results indicate that the proposed implementation can achieve real-time processing, while maintaining the methods accuracy, which indicate the potential of the proposed platform to implement high-performance, low cost embedded systems, opening new perspectives for onboard hyperspectral image processing.

A fast parallel hyperspectral coded aperture algorithm for compressive sensing using OpenCL

In this paper, we develop a fast implementation of an hyperspectral coded aperture (HYCA) algorithm on different platforms using OpenCL, an open standard for parallel programing on heterogeneous systems, which includes a wide variety of devices, from dense multicore systems from major manufactures such as Intel or ARM to new accelerators such as graphics processing units (GPUs), field programmable gate arrays (FPGAs), the Intel Xeon Phi and other custom devices. Our proposed implementation of HYCA significantly reduces its computational cost. Our experiments have been conducted using simulated data and reveal considerable acceleration factors. This kind of implementations with the same descriptive language on different architectures are very important in order to really calibrate the possibility of using heterogeneous platforms for efficient hyperspectral imaging processing in real remote sensing missions.

Detection Of Explosives On The Surface Of Banknotes By Raman Hyperspectral Imaging And Independent Component Analysis.

The aim of this study was to develop a methodology using Raman hyperspectral imaging and chemometric methods for identification of pre- and post-blast explosive residues on banknote surfaces. The explosives studied were of military, commercial and propellant uses. After the acquisition of the hyperspectral imaging, independent component analysis (ICA) was applied to extract the pure spectra and the distribution of the corresponding image constituents. The performance of the methodology was evaluated by the explained variance and the lack of fit of the models, by comparing the ICA recovered spectra with the reference spectra using correlation coefficients and by the presence of rotational ambiguity in the ICA solutions. The methodology was applied to forensic samples to solve an automated teller machine explosion case. Independent component analysis proved to be a suitable method of resolving curves, achieving equivalent performance with the multivariate curve resolution with alternating least squares (MCR-ALS) method. At low concentrations, MCR-ALS presents some limitations, as it did not provide the correct solution. The detection limit of the methodology presented in this study was 50μgcm(-2).

GPU implementation of the simplex identification via split augmented Lagrangian

Hyperspectral imaging can be used for object detection and for discriminating between different objects based on their spectral characteristics. One of the main problems of hyperspectral data analysis is the presence of mixed pixels, due to the low spatial resolution of such images. This means that several spectrally pure signatures (endmembers) are combined into the same mixed pixel. Linear spectral unmixing follows an unsupervised approach which aims at inferring pure spectral signatures and their material fractions at each pixel of the scene. The huge data volumes acquired by such sensors put stringent requirements on processing and unmixing methods. This paper proposes an efficient implementation of a unsupervised linear unmixing method on GPUs using CUDA. The method finds the smallest simplex by solving a sequence of nonsmooth convex subproblems using variable splitting to obtain a constraint formulation, and then applying an augmented Lagrangian technique. The parallel implementation of SISAL presented in this work exploits the GPU architecture at low level, using shared memory and coalesced accesses to memory. The results herein presented indicate that the GPU implementation can significantly accelerate the method's execution over big datasets while maintaining the methods accuracy.

Parallel hyperspectral compressive sensing method on GPU

Remote hyperspectral sensors collect large amounts of data per flight usually with low spatial resolution. It is known that the bandwidth connection between the satellite/airborne platform and the ground station is reduced, thus a compression onboard method is desirable to reduce the amount of data to be transmitted. This paper presents a parallel implementation of an compressive sensing method, called parallel hyperspectral coded aperture (P-HYCA), for graphics processing units (GPU) using the compute unified device architecture (CUDA). This method takes into account two main properties of hyperspectral dataset, namely the high correlation existing among the spectral bands and the generally low number of endmembers needed to explain the data, which largely reduces the number of measurements necessary to correctly reconstruct the original data. Experimental results conducted using synthetic and real hyperspectral datasets on two different GPU architectures by NVIDIA: GeForce GTX 590 and GeForce GTX TITAN, reveal that the use of GPUs can provide real-time compressive sensing performance. The achieved speedup is up to 20 times when compared with the processing time of HYCA running on one core of the Intel i7-2600 CPU (3.4GHz), with 16 Gbyte memory.

High-performance payload data handling system for Gaia

Gaia is the most ambitious space astrometry mission currently envisaged and is a technological challenge in all its aspects. We describe a proposal for the payload data handling system of Gaia, as an example of a high-performance, real-time, concurrent, and pipelined data system. This proposal includes the front-end systems for the instrumentation, the data acquisition and management modules, the star data processing modules, and the payload data handling unit. We also review other payload and service module elements and we illustrate a data flux proposal.

High-performance payload data handling system for Gaia

Gaia is the most ambitious space astrometry mission currently envisaged and is a technological challenge in all its aspects. We describe a proposal for the payload data handling system of Gaia, as an example of a high-performance, real-time, concurrent, and pipelined data system. This proposal includes the front-end systems for the instrumentation, the data acquisition and management modules, the star data processing modules, and the payload data handling unit. We also review other payload and service module elements and we illustrate a data flux proposal.

Studies on the characterization of dental whitening process by using both hyperspectral imaging and colorimeter techniques

A beautiful smile is directly related with white teeth. Nowadays oral care has increased and developed processes for beautiful smiles. Dental bleaching is frequently used in odontology, not just for health care also for aesthetic treatment. With the possibility of teeth bleaching, now the importance is in, how white the tooth is? Because color is relate to an individual perception. In order to assets teeth correct color identification has been developed many color guides, models, spaces and analytical methods. Spite all of these useful tools the color interpretation depends on environmental factors, position of the sample in the data acquisition and most importantly the instrument sensitivity. The commons methods have proved to be useful. They are easy to handle, some are portable but they do not have a high sensitivity. The present work is based on the integration of a new analytical technique for color acquisition. High spectral Image (HSI) is able to performed image analysis with high quality and efficiency. HSI is used in many fields and we used it for color image analysis within the bleaching process. The main comparison was done with the HSI and the colorimeter through the processes of two different bleaching protocols. The results showed that HSI has higher sensitivity than the colorimeter. During the analysis the dental surface with the HSI we were able to notice surface changes. These changes were analyzed by roughness studies.

Developing correlative Optical-Photoacustic microscopy for high-resolution in vivo imaging

PhotoAcoustic Imaging (PAI) is a branch in clinical and pre-clinical imaging, that refers to the techniques mapping acoustic signals caused by the absorption of the short laser pulse. This conversion of electromagnetic energy of the light to the mechanical (acoustic) energy is usually called photoacoustic effect. PAI, by combining optical excitation with acoustical detection, is able to preserve the diffraction limited spatial resolution. At the same time, the penetration depth is extended beyond the diffusive limit. The Laser-Scanning PhotoAcoustic Microscope system (LS-PAM) has been developed, that offers the axial resolution of 7.75 µm with the lateral resolution better than 10 µm. The first in vivo imaging experiments were carried out. Thus, in vivo label-free imaging of the mouse ear was performed. The principle possibility to image vessels located in deep layers of the mouse skin was shown. As well as that, a gold printing sample, vasculature of the Chick Chorioallantoic Membrane Assay, Drosophila larvae were imaged by PAI. During the experimental work, a totally new application of PAM was found, in which the acoustic waves, generated by incident light can be used for further imaging of another sample. In order to enhance the performance of the presented system two main recommendation can be offered. First, the current system should be transformed into reflection-mode setup system. Second, a more powerful source of light with the sufficient repetition rate should be introduced into the system.

High performance, low latency double digit decimal multiplier on ASIC and FPGA

Decimal multiplication is an integral part of financial, commercial, and internet-based computations. This paper presents a novel double digit decimal multiplication (DDDM) technique that offers low latency and high throughput. This design performs two digit multiplications simultaneously in one clock cycle. Double digit fixed point decimal multipliers for 7digit, 16 digit and 34 digit are simulated using Leonardo Spectrum from Mentor Graphics Corporation using ASIC Library. The paper also presents area and delay comparisons for these fixed point multipliers on Xilinx, Altera, Actel and Quick logic FPGAs. This multiplier design can be extended to support decimal floating point multiplication for IEEE 754- 2008 standard.

High-performance infrared filters for the HIRDLS 21-channel focal plane detector array

The High Resolution Dynamics Limb Sounder is described, with particular reference to the atmospheric measurements to be made and the rationale behind the measurement strategy. The demands this strategy places on the filters to be used in the instrument and the designs to which this leads to are described. A second set of filters at an intermediate image plane to reduce "Ghost Imaging" is discussed together with their required spectral properties. A method of combining the spectral characteristics of the primary and secondary filters in each channel are combined together with the spectral response of the detectors and other optical elements to obtain the system spectral response weighted appropriately for the Planck function and atmospheric limb absorption. This method is used to demonstrate whether the out-of-band spectral blocking requirement for a channel is being met and an example calculation is demonstrated showing how the blocking is built up for a representative channel. Finally, the techniques used to produce filters of the necessary sub-millimetre sizes together with the testing methods and procedures used to assess the environmental durability and establish space flight quality are discussed.

A novel strategy for building interoperable MPI environment in heterogeneous high performance systems

Breakthrough advances in microprocessor technology and efficient power management have altered the course of development of processors with the emergence of multi-core processor technology, in order to bring higher level of processing. The utilization of many-core technology has boosted computing power provided by cluster of workstations or SMPs, providing large computational power at an affordable cost using solely commodity components. Different implementations of message-passing libraries and system softwares (including Operating Systems) are installed in such cluster and multi-cluster computing systems. In order to guarantee correct execution of message-passing parallel applications in a computing environment other than that originally the parallel application was developed, review of the application code is needed. In this paper, a hybrid communication interfacing strategy is proposed, to execute a parallel application in a group of computing nodes belonging to different clusters or multi-clusters (computing systems may be running different operating systems and MPI implementations), interconnected with public or private IP addresses, and responding interchangeably to user execution requests. Experimental results demonstrate the feasibility of this proposed strategy and its effectiveness, through the execution of benchmarking parallel applications.

Pore structure and column efficiency of silica monoliths in high performance liquid chromatography (HPLC)

Five different methods were critically examined to characterize the pore structure of the silica monoliths. The mesopore characterization was performed using: a) the classical BJH method of nitrogen sorption data, which showed overestimated values in the mesopore distribution and was improved by using the NLDFT method, b) the ISEC method implementing the PPM and PNM models, which were especially developed for monolithic silicas, that contrary to the particulate supports, demonstrate the two inflection points in the ISEC curve, enabling the calculation of pore connectivity, a measure for the mass transfer kinetics in the mesopore network, c) the mercury porosimetry using a new recommended mercury contact angle values. rnThe results of the characterization of mesopores of monolithic silica columns by the three methods indicated that all methods were useful with respect to the pore size distribution by volume, but only the ISEC method with implemented PPM and PNM models gave the average pore size and distribution based on the number average and the pore connectivity values.rnThe characterization of the flow-through pore was performed by two different methods: a) the mercury porosimetry, which was used not only for average flow-through pore value estimation, but also the assessment of entrapment. It was found that the mass transfer from the flow-through pores to mesopores was not hindered in case of small sized flow-through pores with a narrow distribution, b) the liquid penetration where the average flow-through pore values were obtained via existing equations and improved by the additional methods developed according to Hagen-Poiseuille rules. The result was that not the flow-through pore size influences the column bock pressure, but the surface area to volume ratio of silica skeleton is most decisive. Thus the monolith with lowest ratio values will be the most permeable. rnThe flow-through pore characterization results obtained by mercury porosimetry and liquid permeability were compared with the ones from imaging and image analysis. All named methods enable a reliable characterization of the flow-through pore diameters for the monolithic silica columns, but special care should be taken about the chosen theoretical model.rnThe measured pore characterization parameters were then linked with the mass transfer properties of monolithic silica columns. As indicated by the ISEC results, no restrictions in mass transfer resistance were noticed in mesopores due to their high connectivity. The mercury porosimetry results also gave evidence that no restrictions occur for mass transfer from flow-through pores to mesopores in the small scaled silica monoliths with narrow distribution. rnThe prediction of the optimum regimes of the pore structural parameters for the given target parameters in HPLC separations was performed. It was found that a low mass transfer resistance in the mesopore volume is achieved when the nominal diameter of the number average size distribution of the mesopores is appr. an order of magnitude larger that the molecular radius of the analyte. The effective diffusion coefficient of an analyte molecule in the mesopore volume is strongly dependent on the value of the nominal pore diameter of the number averaged pore size distribution. The mesopore size has to be adapted to the molecular size of the analyte, in particular for peptides and proteins. rnThe study on flow-through pores of silica monoliths demonstrated that the surface to volume of the skeletons ratio and external porosity are decisive for the column efficiency. The latter is independent from the flow-through pore diameter. The flow-through pore characteristics by direct and indirect approaches were assessed and theoretical column efficiency curves were derived. The study showed that next to the surface to volume ratio, the total porosity and its distribution of the flow-through pores and mesopores have a substantial effect on the column plate number, especially as the extent of adsorption increases. The column efficiency is increasing with decreasing flow through pore diameter, decreasing with external porosity, and increasing with total porosity. Though this tendency has a limit due to heterogeneity of the studied monolithic samples. We found that the maximum efficiency of the studied monolithic research columns could be reached at a skeleton diameter of ~ 0.5 µm. Furthermore when the intention is to maximize the column efficiency, more homogeneous monoliths should be prepared.rn

FPGA-Based Wireless Sensor Node Architecture for High Performance Applications

While for years traditional wireless sensor nodes have been based on ultra-low power microcontrollers with sufficient but limited computing power, the complexity and number of tasks of today’s applications are constantly increasing. Increasing the node duty cycle is not feasible in all cases, so in many cases more computing power is required. This extra computing power may be achieved by either more powerful microcontrollers, though more power consumption or, in general, any solution capable of accelerating task execution. At this point, the use of hardware based, and in particular FPGA solutions, might appear as a candidate technology, since though power use is higher compared with lower power devices, execution time is reduced, so energy could be reduced overall. In order to demonstrate this, an innovative WSN node architecture is proposed. This architecture is based on a high performance high capacity state-of-the-art FPGA, which combines the advantages of the intrinsic acceleration provided by the parallelism of hardware devices, the use of partial reconfiguration capabilities, as well as a careful power-aware management system, to show that energy savings for certain higher-end applications can be achieved. Finally, comprehensive tests have been done to validate the platform in terms of performance and power consumption, to proof that better energy efficiency compared to processor based solutions can be achieved, for instance, when encryption is imposed by the application requirements.

Detection and quantification of peanut traces in wheat flour by near infrared hyperspectral imaging spectroscopy using principal-component analysis

The use of a common environment for processing different powder foods in the industry has increased the risk of finding peanut traces in powder foods. The analytical methods commonly used for detection of peanut such as enzyme-linked immunosorbent assay (ELISA) and real-time polymerase chain reaction (RT-PCR) represent high specificity and sensitivity but are destructive and time-consuming, and require highly skilled experimenters. The feasibility of NIR hyperspectral imaging (HSI) is studied for the detection of peanut traces down to 0.01% by weight. A principal-component analysis (PCA) was carried out on a dataset of peanut and flour spectra. The obtained loadings were applied to the HSI images of adulterated wheat flour samples with peanut traces. As a result, HSI images were reduced to score images with enhanced contrast between peanut and flour particles. Finally, a threshold was fixed in score images to obtain a binary classification image, and the percentage of peanut adulteration was compared with the percentage of pixels identified as peanut particles. This study allowed the detection of traces of peanut down to 0.01% and quantification of peanut adulteration from 10% to 0.1% with a coefficient of determination (r2) of 0.946. These results show the feasibility of using HSI systems for the detection of peanut traces in conjunction with chemical procedures, such as RT-PCR and ELISA to facilitate enhanced quality-control surveillance on food-product processing lines.