Imaging Fourier Research Articles

Analysis of Vision based Techniques for the Translation of Indian Sign Language

Sign language acts as a medium of communication among those of the hearing impaired and mute community. However, it cannot be easily understood by common people. Various research has been done to bridge this gap by developing Sign Language Recognition (SLR) methodologies. Studies say that 1 in every 5 deaf people is Indian.
 In this paper, a thorough review of these methodologies has been done, to compare and contrast various aspects of them. This includes an overview on different preprocessing methods used like segmentation, image morphological processing, cropping, etc, feature extraction techniques like Fourier Descriptors, Image Moments, Eigen values, Mediapipe and others. This study also covered classification models spanning from Distance metrics to Kernel based approaches and feedforward neural networks, along with Deep Learning based methods such as CNNs, LSTMs, GANs, Transformers etc.

Broadband, High Resolution, Sensitive Spectrometer Using an Integrated Optical Phased Array in Silicon Nitride and Fourier Imaging

Broadband, High Resolution, Sensitive Spectrometer Using an Integrated Optical Phased Array in Silicon Nitride and Fourier Imaging

Spatially robust adaptive ensemble average propagator reconstruction via spherical polar Fourier imaging

Spatially robust adaptive ensemble average propagator reconstruction via spherical polar Fourier imaging

Fourier-Based Fast 3-D Ultrasound Imaging Using Row-Column-Addressed 2-D Arrays.

A Fourier-based fast 3-D ultrasound imaging method using row-column-addressed (RCA) 2-D arrays is presented. The row elements in an RCA array are activated sequentially, and all the column elements are used to receive. The obtained dataset is adapted to approximate to that obtained using a fully sampled array after a plane wave at a given incident angle is transmitted. In this way, the fast algorithm in plane-wave Fourier imaging (PWFI) can be applied to the adapted dataset. In addition, synthesizing multiple datasets based on multiple incident angles enables angular compounding, which improves the image quality. The proposed method was validated using computer simulations and physical-phantom experiments. The results show that the spatial resolution and contrast of the proposed method are comparable with those of its PWFI counterpart without requiring a fully sampled (FS) array. Compared with the delay-and-sum (DAS) method using the RCA array, the proposed method provides comparable spatial resolution but lower contrast; however, the computational complexity is significantly reduced from O(N4Nz) to O(WN2Nz log2(N2Nz)) , where N is the number of elements on each side of the RCA array, Nz is the number of voxels in the axial direction in the output image, and W is the number of compounding angles. For example, in the simulated results when the maximum compounding angle M is 5°, at a given point the lateral - 6-dB width provided by the proposed method is 0.241 mm (0.267 mm for DAS), the contrast ratio of a hyperechoic cyst is 8.87 dB (9.10 dB for DAS), the number of real number operations is reduced by a factor of 20.62, and the number of memory accesses is reduced by a factor of 47.21, both compared with DAS. This novel fast algorithm could facilitate the development of compact real-time 3-D imaging systems, especially when the channel count is high and a large field of view (FOV) is required.

Color Routing of the Emission from Magnetic and Electric Dipole Transitions of Eu3+ by Broken-Symmetry TiO2 Metasurfaces.

Manipulation of magnetic dipole emission with resonant photonic nanostructures is of great interest for both fundamental research and applications. However, obtaining selective control over the emission properties of magnetic dipole transitions is challenging, as they usually occur within a manifold of spectrally close emission lines associated with different spin states of the involved electronic levels. Here we demonstrate spectrally selective directional tailoring of magnetic dipole emission using designed photonic nanostructures featuring a high quality factor. Specifically, we employ a hybrid nanoscale optical system consisting of a Eu3+ compound coupled to a designed broken-symmetry TiO2 metasurface to demonstrate directional color routing of the compound's emission through its distinct electric and magnetic-dominated electronic transition channels. Using low numerical aperture collection optics, we achieve a fluorescence signal enhancement of up to 33.13 for the magnetic-dominated dipole transition at 590 nm when it spectrally overlaps with a spectrally narrow resonance of the metasurface. This makes the, usually weak, magnetic dipole transition the most intense spectral line in our recorded fluorescence spectra. By studying the directional emission properties for the coupled system using Fourier imaging and time-resolved fluorescence measurements, we demonstrate that the high-quality-factor modes in the metasurface enable free-space light routing, where forward-directed emission is established for the magnetic-dominated dipole transition, whereas the light emitted via the electric dipole transition is mainly directed sideways. Our results underpin the importance of magnetic light-matter interactions as an additional degree of freedom in photonic and optoelectronic systems. Moreover, they facilitate the development of spectrometer-free and highly integrated nanophotonic imaging, sensing, and probing devices.

The Large Imaging Spectrometer for Solar Accelerated Nuclei (LISSAN): A Next-Generation Solar γ-ray Spectroscopic Imaging Instrument Concept

Models of particle acceleration in solar eruptive events suggest that roughly equal energy may go into accelerating electrons and ions. However, while previous solar X-ray spectroscopic imagers have transformed our understanding of electron acceleration, only one resolved image of γ-ray emission from solar accelerated ions has ever been produced. This paper outlines a new satellite instrument concept—the large imaging spectrometer for solar accelerated nuclei (LISSAN)—with the capability not only to observe hundreds of events over its lifetime, but also to capture multiple images per event, thereby imaging the dynamics of solar accelerated ions for the first time. LISSAN provides spectroscopic imaging at photon energies of 40 keV–100 MeV on timescales of ≲10 s with greater sensitivity and imaging capability than its predecessors. This is achieved by deploying high-resolution scintillator detectors and indirect Fourier imaging techniques. LISSAN is suitable for inclusion in a multi-instrument platform such as an ESA M-class mission or as a smaller standalone mission. Without the observations that LISSAN can provide, our understanding of solar particle acceleration, and hence the space weather events with which it is often associated, cannot be complete.

600-GHz Fourier imaging based on heterodyne detection at the 2nd sub-harmonic.

Fourier imaging is an indirect imaging method which records the diffraction pattern of the object scene coherently in the focal plane of the imaging system and reconstructs the image using computational resources. The spatial resolution, which can be reached, depends on one hand on the wavelength of the radiation, but also on the capability to measure - in the focal plane - Fourier components with high spatial wave-vectors. This leads to a conflicting situation at THz frequencies, because choosing a shorter wavelength for better resolution usually comes at the cost of less radiation power, concomitant with a loss of dynamic range, which limits the detection of higher Fourier components. Here, aiming at maintaining a high dynamic range and limiting the system costs, we adopt heterodyne detection at the 2nd sub-harmonic, working with continuous-wave (CW) radiation for object illumination at 600 GHz and local-oscillator (LO) radiation at 300 GHz. The detector is a single-pixel broad-band Si CMOS TeraFET equipped with substrate lenses on both the front- and backside for separate in-coupling of the waves. The entire scene is illuminated by the object wave, and the Fourier spectrum is recorded by raster scanning of the single-detector unit through the focal plane. With only 56 µW of power of the 600-GHz radiation, a dynamic range of 60 dB is reached, sufficient to detect the entire accessible Fourier space spectrum in the test measurements. We present a detailed comparison between plane-to-plane imaging and Fourier imaging, and show that, with both, a lateral spatial resolution of better than 0.5 mm, at the diffraction limit, is reached.

An Invariant Representation of Coupler Curves Using a Variational AutoEncoder: Application to Path Synthesis of Four-Bar Mechanisms

Abstract This paper focuses on the representation and synthesis of coupler curves of planar mechanisms using a deep neural network. While the path synthesis of planar mechanisms is not a new problem, the effective representation of coupler curves in the context of neural networks has not been fully explored. This study compares four commonly used features or representations of four-bar coupler curves: Fourier descriptors, wavelets, point coordinates, and images. The results demonstrate that these diverse representations can be unified using a generative AI framework called variational autoencoder (VAE). This study shows that a VAE can provide a standalone representation of a coupler curve, regardless of the input representation, and that the compact latent dimensions of the VAE can be used to describe coupler curves of four-bar linkages. Additionally, a new approach that utilizes a VAE in conjunction with a fully connected neural network to generate dimensional parameters of four-bar linkage mechanisms is proposed. This research presents a novel opportunity for the automated conceptual design of mechanisms for robots and machines.

Intelligent pointing increases the fraction of cloud-free CO2 and CH4 observations from space

For most CO2 and CH4 satellites, only a small percentage (∼10%) of observations yield successful retrievals, with the remaining ∼90% rejected, primarily due to the effects of clouds. Discarding this large fraction of data is an inefficient strategy worth reconsidering due to the costs involved in developing, launching and operating the satellites to make these observations. However, if real-time cloud data are available together with pointing capability, cloud data can guide the instrument pointing in an “intelligent pointing” strategy for cloud avoidance. In this work, multiple intelligent pointing simulations were conducted, demonstrating the significant advantages of this approach for satellites in a highly elliptical orbit (HEO), from which nearly the whole Earth disk can be observed. Multiple factors are shown to contribute to intelligent pointing efficiency such as the size and shape (or aspect ratio) of the field of view (FOV). For the current baseline orbit and Imaging Fourier Transform Spectrometer (IFTS) observing characteristics for the proposed Arctic Observing Mission (AOM), the monthly fraction of cloud-free observations is roughly a factor of 2 (ranging from ∼1.5–2.5) more than obtained with standard pointing (in which cloud information is not used). A similar efficiency is expected in a geostationary orbit (GEO) with an IFTS, however, for a dispersive instrument in HEO or GEO, the gain is more modest. This result is primarily attributed to the ∼1:1 aspect ratio of the IFTS FOV, since it is more efficient for cloud avoidance and scanning irregularly-shaped land masses than the long and narrow slit projection of a typical dispersive spectrometer. These results have implications for the design of future CO2 or CH4 monitoring satellites and constellation architectures, as well as other fields of satellite earth observation in which clouds significantly impact observations.

Image denoising and deringing for fourier single-pixel imaging based on upgraded weighted nuclear norm minimization

Single-pixel imaging techniques have been extensively studied because of the low requirements for the detector resolution and the low equipment cost. However, a large amount of noise and ringing commonly occur in the reconstructed images via previous single-pixel imaging methods at ultra-low sampling rates, which limits the real applications. In this paper, a novel Fourier single-pixel imaging method is proposed to reconstruct high-quality single-pixel imaging images at ultra-low sampling rates, which involves the stages of Fourier single-pixel imaging, block matching, upgraded weight nuclear norm minimization, and aggregation. To decrease the computational burden while important image details, block matching and aggregation are employed for the blocks divided from the low-quality image reconstructed by Fourier single-pixel imaging. To adapt the proposed upgraded weight nuclear norm minimization to different contaminated images, an adaptive scheme for the iterative regularization parameter is proposed to update the traditional weight nuclear norm minimization. Experimental results indicate that the proposed Fourier single-pixel imaging method based on upgraded weight nuclear norm minimization exhibits the capacity to reliably and effectively reconstruct high-quality images for single-pixel imaging at low sampling rates, even at the sampling rate of 1 %. Experimental results also demonstrate that the proposed method performs better image reconstruction than some existing single-pixel imaging.

Spectrum of One-Dimensional Potential Perturbed by a Small Convolution Operator: General Structure

We consider an operator of multiplication by a complex-valued potential in L2(R), to which we add a convolution operator multiplied by a small parameter. The convolution kernel is supposed to be an element of L1(R), while the potential is a Fourier image of some function from the same space. The considered operator is not supposed to be self-adjoint. We find the essential spectrum of such an operator in an explicit form. We show that the entire spectrum is located in a thin neighbourhood of the spectrum of the multiplication operator. Our main result states that in some fixed neighbourhood of a typical part of the spectrum of the non-perturbed operator, there are no eigenvalues and no points of the residual spectrum of the perturbed one. As a consequence, we conclude that the point and residual spectrum can emerge only in vicinities of certain thresholds in the spectrum of the non-perturbed operator. We also provide simple sufficient conditions ensuring that the considered operator has no residual spectrum at all.

Remote Detection and Quantification of Methane Emissions Based on Hyperspectral Data Analysis

Measurement of methane emissions from leaks occurring on the territorially extensive network of transmission gas grid is a topical issue and highly desirable from the point of view of safety and reducing methane emissions into the atmosphere. Remote detection of methane is a problem whose technical solution is based on several types of optoelectronic devices, e.g. thermal imaging cameras with sets of optical filters, spectroradiometers, laser systems of the DIAL (DIfferential Absorption Lidar) type. On the other hand, the quantification of emission magnitudes is in most cases realized by spectoradiometric systems. This paper will present a method for analyzing hyperspectral data from an imaging Fourier infrared spectroradiometer. Measurements will be made on a purpose-built bench simulating methane emissions from a transmission network. Data obtained from ground level under different atmospheric conditions will be presented, together with the results of their analysis for different methane emissions.

A Comparison Between Fourier and Hadamard Single-Pixel Imaging in Deep Learning-Enhanced Image Reconstruction

A Comparison Between Fourier and Hadamard Single-Pixel Imaging in Deep Learning-Enhanced Image Reconstruction

An Extended Generalized Average Modeling Framework for Power Converters

The Generalized Averaged Modeling (GAM) technique is traditionally employed to capture the dynamic performance of power electronic converters. This paper proposes an improved version of it, named the Extended-GAM (EGAM) technique, which supports the multiplication of two Double Fourier Series (DFS) signals in the time domain. Multiplication of DFS signals in the time domain translates to the 2D-convolution of coefficients of the DFS terms of their equivalent Discrete Fourier Image (DFI) representations. Thus, the proposed EGAM technique, capable of capturing many harmonics present in the output of a power converter, effectively captures the dynamic behavior of power converters excited by two distinct frequencies. The proposed technique is then converted into an algorithm suitable for numerical platforms, which typically use Ordinary Differential Equation (ODE) solvers. The proposed algorithm is validated based on the observations of the effects of harmonic truncation. The efficacy of the proposed technique is assessed through a case study, wherein a single-phase inverter employs LC filters on both the dc-link and the ac-side. Finally, it is shown that the results obtained with the proposed method show an excellent congruence between simulation and hardware experimental models. Additionally, the proposed algorithm is packaged into a MATLAB toolbox and shared for future implementations.

Perancangan Aplikasi Pengolahan Citra Digital Untuk Penajaman Sisi Citra Hasil Fingerprint Menggunakan Metode Fourier Phase Only Synthesis

Detecting fringerprints (fingerprints) is one way to sharpen image results to make them look clearer and cannot be manipulated. In general, the attendance system used by employees is still mostly done manually. This has many weaknesses where in addition to data that can be easily imitated, the time is not clear, it also takes quite a long time. So to avoid this, an electronic system is needed. In this case the system that will be used is the fingerprint method. The development of image processing technology now provides the possibility for humans to create a system that can recognize a digital image. Various image processing applications that have been developed at this time include security systems, the world of robotics, and so on. Image processing is one type of technology to solve problems regarding image processing. In image processing, images are processed in such a way that they can be used for further applications. The fingerprint recognition system must be able to identify a person's fingerprint from a large set of fingerprint databases. This is a separate problem for the efficiency of the identification system. Therefore, various classification approaches are used based on the general characteristics that appear in fingerprints. The process begins with detecting the fringerprint result by sticking your finger on the scan machine, then the image will be detected and the image is sharpened with a value using arithmetic operations. The results of image processing are indicated by changes in the resulting image and fourier image changes. In this case the system that will be used is the fingerprint method. This fingerprint system uses the fourier phase only synthesis method.

Planetary nebulae and supernova remnants in NGC 4214 from the SIGNALS survey

ABSTRACT Using datacubes from the imaging Fourier transform spectrometer SITELLE at the Canada–France–Hawaii Telescope as part of the star formation, ionized gas, and nebular abundances legacy survey, we identify 15 new planetary nebulae (PNe) as well as five new supernova remnants (SNRs) in the outer parts of the nearby dwarf starburst galaxy NGC 4214. These data also allow us to study the morphology and kinematics of all 18 known SNRs in this galaxy. We highlight the use of a $\xi = \sigma \frac{\rm {[S{\small \,II}]}}{\rm {H\alpha }}$ diagnostic diagram (σ being the velocity dispersion) to separate SNRs from H ii regions and its advantage compared to classical BPT or Sabbadin diagrams. We provide the emission-line flux ([O iii] λ5007, H α, and H β) and radial velocities of all new PNe candidates, as well as those of 12 of the 17 PNe previously discovered in the central part of the galaxy with Hubble Space Telescope (HST) data. Finally, we use the [O iii] emission-line luminosity function of the PNe sample to establish a new velocity-independent distance for NGC 4214: $D = 3.23^{+0.18}_{-0.25}$ Mpc.

Stratospheric-trace-gas-profile retrievals from balloon-borne limb imaging of mid-infrared emission spectra

Abstract. The Limb Imaging Fourier Transform Spectrometer Experiment (LIFE) instrument is a balloon-borne prototype of a satellite instrument designed to take vertical images of atmospheric limb emission spectra in the 700–1400 cm−1 wavenumber range from the upper-troposphere–lower-stratosphere (UTLS) altitude region of the atmosphere. The prototype builds on the success of past and existing instruments while reducing the complexity of the imaging design. This paper details the results of a demonstration flight on a stabilized stratospheric balloon gondola from Timmins, Canada, in August 2019. Retrievals of vertical trace gas profiles for the important greenhouse gases H2O, O3, CH4, and N2O, as well as HNO3, are performed using an optimal estimation approach and the SASKTRAN radiative transfer model. The retrieved profiles are compared to approximately coincident observations made by the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) solar occultation and Microwave Limb Sounder (MLS) instruments. An evaluation of the LIFE measurements is performed, and areas of improvement are identified. This work increases the overall technical readiness of the approach for future balloon, aircraft, and space applications.

Phase microscopy using band-limited image and its Fourier transform constraints.

In this Letter, we present a new, to the best of our knowledge, form of single-exposure quantitative phase microscopy based on the phase retrieval method by recording the band-limited image and its Fourier image simultaneously. Applying the intrinsic physical constraints of microscopy systems in the phase retrieval algorithm, we remove the inherent ambiguities of the reconstruction and achieve a rapid iterative convergence. In particular, this system does not require tight support of the object and the oversampling needed in coherent diffraction imaging. We have demonstrated that, in both simulations and experiments, the phase can be rapidly retrieved from a single-exposure measurement using our algorithm. The presented phase microscopy provides a promising technique for real-time quantitative biological imaging.

Hybrid Fourier Descriptor Naïve Bayes dan CNN pada Klasifikasi Daun Herbal

Plants are vital to human life on earth, and the leaves and their whole parts have many benefits. These parts of the plant can help distinguish between different species. The leaf identification can be performed at any time, while the other parts of the plants can only be identified at a certain time. The study aims to classify two types of herbs i.e. saur-opus androgynous and moringa oleifera, implementing the Fourier Descriptor method to extract the shape and texture features. In the process of classification using the Naïve Bayes method with three types of nuclei (Gaussian, Bernoulli, and Multinomial) and a Convolutional Neural Network. The testing process was carried out using two scenarios, dark and light, where each scenario consisted of 240 images for a total of 480 images divided into 20% of the data testing and 80% of the training data. The Fourier Descriptor-Bernoulli Naive Bayes method gives the lowest accuracy in both light and dark scenarios, at 46% and 52%, respectively. As for the classification of herbal leaves using a combination of the Fourier Descriptor-Convolutional Neural Network method, it is recommended to be used in light image scenarios and Fourier Descriptor-Gaussian Naive Bayes in the dark scenarios because it is able to detect herbal leaf types with 100% accuracy.

The rhythm-adaptive Fourier series decompositions of cyclic numerical functions and one-dimensional probabilistic characteristics of cyclic random processes

The paper presents rhythm adaptive Fourier series decompositions of cyclic numerical functions and one-dimensional probabilistic characteristics of cyclic random processes, which are mathematical models of many deterministic and stochastic cyclic signals with a variable (irregular) rhythm. The adaptability of such decompositions to the change of rhythm of the investigated cyclic signals, on the one hand, ensures the elimination of the approximation error characteristic for classical Fourier series for periodic functions, and on the other hand, does not lead to an increase in the number of spectral components in the corresponding Fourier images, which occurs when Fourier transform is applied to cyclic deterministic and stochastic signals with variable rhythm. The work also presents the interconnected characteristics of the rhythm of cyclic deterministic and stochastic signals, and establishes their main properties for the base components of rhythm-adaptive Fourier series. The efficiency of rhythm adaptive Fourier series decompositions of cyclic numerical functions and one-dimensional probabilistic characteristics of cyclic random processes is confirmed by the results of a computer simulation.