Imaging Fourier Research Articles

Concrete crack classification based on fourier image enhancement and convolutional neural network

This paper investigates the application of Fourier image enhancement combined with Convolutional Neural Networks (CNNs) for detecting cracks in concrete structures. Fourier enhancement is used to preprocess crack images, improving their clarity and reducing noise, which in turn enhances the performance of the CNN in accurately classifying cracks. The results demonstrate that this combination improves the classification accuracy, with the enhanced images achieving a higher accuracy compared to non-enhanced images. Additionally, the study examines the effects of this preprocessing on CNN training time. However, accuracy varies depending on the dataset used, with one dataset reaching a maximum accuracy of 95% after enhancement. These findings highlight the potential of using frequency-domain image enhancement techniques in conjunction with deep learning models for structural health monitoring.

The Large Imaging Spectrometer for Solar Accelerated Nuclei (LISSAN): A next-generation solar gamma-ray spectroscopic imaging instrument concept

We present the Large Imaging Spectrometer for Solar Accelerated Nuclei (LISSAN), a new solar dedicated satellite instrument concept. LISSAN relies on an indirect Fourier imaging technique valid over an energy range from 40 keV up to 100 MeV. Spatial information is encoded into 15 moiré patterns by 15 pairs of slightly offset grids (bigrids) separated by a fixed distance enabling a predicted spatial resolution of 10”. The time, location, and energy of each incoming photon is recorded via a pixelated gadolinium aluminium gallium garnet (GAGG) crystal scintillator detector placed in alignment with each bigrid, therefore providing simultaneous imaging and spectroscopy from the same imaging system. X-ray and gamma-ray emission are key diagnostics of electron and ion acceleration, respectively. However, despite being a fundamental process that occurs throughout the Universe, particularly in the solar atmosphere, only one resolved gamma-ray image of ion acceleration in a solar flare has ever been achieved. LISSAN will shed new light on this process by providing spectral resolution better than 1.5% FWHM at 6.1 MeV, an imaging effective area at 2.2 MeV of 100 cm2 (more than 25 times greater than past missions such as RHESSI) and a 10 s cadence. Thanks to these significant advances over the previous satellite-based solar detectors, LISSAN will provide reliable imaging and the spectral characterization of both electron and ion acceleration in solar eruptive events simultaneously for the first time, enabling to it to answer several important open questions regarding solar particle acceleration and the initiation of space weather events.

Properties of supernova remnants in SIGNALS galaxies – I. NGC 6822 and M33

Abstract We present a spatially resolved study of the kinematical properties of known supernova remnants (SNRs) in the nearest galaxies of the SIGNALS survey, namely NGC 6822 (one object) and M33 (163 objects), based on data obtained with the SITELLE Imaging Fourier Transform Spectrometer (iFTS) at the Canada-France-Hawaii Telescope. The purpose of this paper is to provide a better scheme of identification for extragalactic SNRs and, in particular, to distinguish between H ii regions and SNRs. For that we have used diagrams which involve both the [S ii]/Hα ratio and the velocity dispersion (σ). We also introduce a new parameter, $\xi = {[\rm S\, \small {II}] \over H\alpha } \times \sigma$, which enhances still the contrast between SNRs and the rest of the ionised gas. More than 90% of the SNRs in our entire sample show an integrated [S ii]/Hα ratio larger than the canonical value (0.4). 86% of the SNRs present in our field show a significant velocity dispersion. The spectral resolution of our observations allows us to observe the complex velocity structure of some SNRs.

Pseudopolar Format Matrix Description of Near-Range Radar Imaging and Fractional Fourier Transform

Near-range radar imaging (NRRI) has evolved into a vital technology with diverse applications spanning fields such as remote sensing, surveillance, medical imaging and non-destructive testing. The Pseudopolar Format Matrix (PFM) has emerged as a promising technique for representing radar data in a compact and efficient manner. In this paper, we present a comprehensive PFM description of near-range radar imaging. Furthermore, this paper also explores the integration of the Fractional Fourier Transform (FrFT) with PFM for enhanced radar signal analysis. The FrFT—a powerful mathematical tool for signal processing—offers unique capabilities in analysing signals with time-frequency localization properties. By combining FrFT with PFM, we have achieved significant advancements in radar imaging, particularly in dealing with complex clutter environments and improving target detection accuracy. Meanwhile, this paper highlights the imaging matrix form of FrFT under the PFM, emphasizing the potential for addressing challenges encountered in near-range radar imaging. Finally, numerical simulation and real-world scenario measurement imaging results verify optimized accuracy and computational efficiency with the fusion of PFM and FrFT techniques, paving the way for further innovations in near-range radar imaging applications.

Impact of Zeeman and hyperfine interactions on the magnetic properties of paramagnetic metal Ions: III. Analysis of the local interactions in a single crystal of 173Yb3+ doped Y5SiO5

The electron spin echo envelope modulation (ESEEM) technique is a direct method to probe the nuclear spin coherences induced by electron spin transitions. Recently, this approach was used to study an isotopically pure Y2SiO5 crystal doped with 173Yb3+ ions, and the presence of the Fermi contact interaction was proposed to explain the frequency comb detected in the two-pulse ESEEM experiment [Solovarov N. K. et al. JETP Letters 115 (6): 362–67]. Here we simulate the Fourier images of the ESEEM data. The numerical analysis shows that the modulation is mainly due to the nuclear spin coherences induced by the dipole–dipole interactions. However, the correlation between the experimental and simulated data is better when the super-hyperfine interactions of the nearby yttrium nuclei have an additional isotropic contribution. The analysis of the rescaled X-band ESEEM spectra shows that for the EPR transitions at magnetic fields > 100 mT, the main contribution to the modulation comes from the oscillations of the individual nuclei and the effect of interference between coherences originating from several nuclei is not strong. Further experiments to distinguish the sources of the echo modulation are discussed.

Novel method of image analysis that combines Radon and Fourier image transformations for the purpose of differentiating between malignant and benign colonic biopsies.

Colorectal cancer is the third most common type of cancer. It develops slowly as a polyp that can turn into a cancerous tumor. This study aimed to develop a decision-making algorithm of microscopic images using texture analysis that is orientation free, to be used for automated classification of normal and neoplastic (malignant or premalignant) colonic biopsies. Forty-nine colonic adenocarcinomas, 41 adenomas and a control group of adjacent normal colonic mucosa were included in the texture analysis. Radon transform followed by the Fast Fourier transform were applied to the images. Subsequently, the gray level co-occurrence matrix (GLCM) transform was applied allowing the extraction of four textural variables (homogeneity, contrast, correlation, and entropy). For classification and prediction of the diagnosis, a statistical multivariate regression model and a neural network (NNET) model were used and compared. The statistical model provided a sensitivity of 71.3% and a specificity of 50% (Area under the ROC curve: 0.67) for classifying the neoplastic and the normal images, respectively. The NNET model was superior to the statistical model and produced a sensitivity of 97.9% and specificity of 88% (Area under the ROC curve: 0.92). To our knowledge, this is the first study that used a combination of Radon, FFT, and GLCM transformations in order to overcome the tissue orientation problem in texture analysis of microscopic images of colonic biopsies. The NNET classifier trained by the extracted textural features proved to be superior to the statistical classifier, thus predicting colonic neoplasia with high accuracy. RESEARCH HIGHLIGHTS: We propose a novel decision-making algorithm of orientation invariant image texture analysis, fast and easily implemented for automated differentiation between benign and neoplastic epithelial tumors of the colon. This method can reduce the turnaround time allowing to prioritize the biopsies during their examination and diagnosis by the pathologist.

More Frequent Spaceborne Sampling of XCO2 Improves Detectability of Carbon Cycle Seasonal Transitions in Arctic‐Boreal Ecosystems

AbstractSurface, aircraft, and satellite measurements indicate pervasive early cold season (Augut–September) CO2 emissions across Arctic regions, consistent with increased ecosystem metabolism in plants and soils. A key remaining question is whether cold season sources will become large enough to permanently shift the Arctic into a net carbon source. Polar orbiting GHG satellites provide robust estimation of regional carbon budgets but lack sufficient spatial coverage and repeat frequency to track sink‐to‐source transitions in the early cold season. Mission concepts such as the Arctic Observing Mission (AOM) advocate for flying imaging spectrometers in highly elliptical orbits (HEO) over the Arctic to address sampling limitations. We perform retrieval and flux inversion simulation experiments using the AURORA mission concept, leveraging a Panchromatic imaging Fourier Transform Spectrometer (PanFTS) in HEO. Our simulations demonstrate the potential benefits of increased CO2 sampling for detecting emissions during the early cold season.

Microplastics in Arctic waters of the Finnish Sámi area

We explored the presence of microplastics in the Finnish Arctic Sámi home area. A dialogue between Indigenous knowledge and scientific field work produced data about microplastics in remote wilderness aquatic ecosystems. Methods included geographical Indigenous knowledge analysis, water sampling with fraction filtration, and imaging Fourier transform infrared spectroscopy. The MPs found were small; the mean particle size was 126 ± 121 μm. Particle concentrations of MPs in freshwater and marine samples varied between 45 and 423 MPs m−3 and the most common polymer types were polyethylene, polypropylene, and polyethylene terephthalate. In conclusion, because microplastics are present even in the wilderness areas, their abundance should be monitored to assess plastic pollution in the relatively pristine Arctic environments. Sámi Indigenous knowledge proved to be a beneficial and important initiator, because locals recognize the possible sources and transport pathways of plastic litter, and practical sampling sites in the complex freshwater systems of the area.

Revealing spatial distribution and accessibility of cell wall polymers in bamboo through chemical imaging and mild chemical treatments

Understanding the distribution and accessibility of polymers within plant cell walls is crucial for addressing biomass recalcitrance in lignocellulosic materials. In this work, Imaging Fourier Transform Infrared (FTIR) and Raman spectroscopy, coupled with targeted chemical treatments, were employed to investigate cell wall polymer distribution in two bamboo species at both tissue and cell wall levels. Tissue-level Imaging FTIR revealed significant disparities in the distribution and chemical activity of cell wall polymers between the fibrous sheath and fibrous strand. At the cell wall level, Imaging Raman spectroscopy delineated a distinct difference between the secondary wall and intercellular layer, with the latter containing higher levels of lignin, hydroxycinnamic acid (HCA), and xylan, and lower cellulose. Mild acidified sodium chlorite treatment led to partial removal of lignin, HCA, and xylan from the intercellular layer, albeit to a lesser extent than alkaline treatment, indicating susceptibility of these polymers to chemical treatment. In contrast, lignin in the secondary wall exhibited limited reactivity to acidified sodium chlorite but was slightly removed by alkaline treatment, suggesting stable chemical properties with slight alkaline intolerance. These findings provide valuable insights into the inherent design mechanism of plant cells and their efficient utilization.

Direct Detection and Characterization of Exoplanets Using Imaging Fourier Transform Spectroscopy

Space-based direct imaging provides prospects for detection and spectral characterization of exoplanets at optical and near-infrared wavelengths. Integral field spectrographs (IFS) have been historically baselined for these mission concepts. However, multiple studies have revealed that detector noise is a serious obstacle for such instruments when observing extremely faint targets such as Earth-like planets. Imaging Fourier transform spectrographs (iFTS) are generally less sensitive to detector noise, and have several other compelling features such as simultaneous imaging and spectroscopy, smaller-format detector requirements, and variable spectral resolving power. To date, they have not been studied as options for such missions. Here, we compare the capabilities of IFS and iFTS for directly obtaining spectra from an Earth-like planet using both analytic and numerical models. Specifically, we compare the required exposure times to achieve the same signal-to-noise ratio with the two architectures over a range of detector and optical system parameters. We find that for a 6 m telescope, an IFS outperforms an iFTS at optical wavelengths due to the effects of distributed photon noise. In the near-IR, the relative efficiency of an IFS and iFTS depends critically on the instrument design and detector noise. An iFTS will be more efficient than an IFS if the readout noise of the near-IR detector is above ∼2–3 e− pix−1 frame−1 (t frm = 1000 s), which correspond to half to one-third of the state-of-art detector noise. However, if the readout noise is reduced below this threshold, the performance of an IFS will experience a substantial improvement and become more efficient. These results motivate consideration of an iFTS as an alternative option for future direct imaging space missions in the near-IR.

Single-exposure quantitative differential interference contrast microscopy using bandlimited image and its Fourier transform constraints

Phase microscopy that records the bandlimited image and its Fourier image simultaneously (BIFT) is a phase retrieval method with unique and rapid convergence. In this paper, we present a single-exposure quantitative differential interference contrast (DIC) microscopy based on BIFT method. The contrasts of the recorded DIC image and its Fourier image, analyzed by simulation and experiment, can be largely improved by the initial phase difference between two sheared lights (bias), however their trends with biases are opposite. By adding the optimized bias with the compromise of the contrasts in image and Fourier space, the phase sensitivity can be improved than BIFT method only. We have experimentally demonstrated that a sample of 25 nm height can be successfully recovered from a single exposure. The presented single-exposure quantitative DIC microscopy provides a promising technique for real-time phase imaging.

Ring nebulae around Wolf–Rayet stars in M33 as seen by SITELLE

ABSTRACT We have conducted an analysis of nebulae around Wolf–Rayet (WR) stars in M33 using data collected by the imaging Fourier transform spectrometer SITELLE at the Canada–France–Hawaii telescope as part of the SIGNALS Large Program. Of the 211 known WR stars in M33, 178 are located in the fields observed in this study. We present the results of this analysis in the form of a comprehensive summary of all nebulae found around the observed WR stars. Based on three criteria we find to be the most effective for their detection, we detect a clear association with a circumstellar bubble around 33 of them (19 per cent). Our results show that the presence of bubbles does not correlate with the spectral type of the central star. The mean diameter of the WR nebulae we have found is 21 parsec.

Substantiating the mechanisms of electronic and phonon friction in the conjugation of materials of samples (parts) by the methods of solid state physics

The article elucidates the essence of the mechanisms of electronic and phonon friction in the coupling of samples (parts) using the methods of solid state physics.
 It is shown that in the triboconjugation of samples made of metallic materials, the flow of fluctuation-electromagnetic and electron-phonon processes should be distinguished. Fluctuation-electromagnetic interactions have long-range effects, and electron-phonon interactions have short-range effects. Based on Lifshitz's fluctuation-electromagnetic theory, the force of friction in moving couplings of metal samples is substantiated, taking into account the frequency ratio in the atomic absorption spectrum and the plasma frequency. A formula for estimating the friction force was obtained, taking into account the dielectric function and the Clausius-Mossotti formula.
 The electronic friction force was estimated using the "jelly" model and the generation of electron-hole pairs in the quantum perturbation theory of solid-state physics.
 The mechanism of electronic friction was discovered based on the phenomenological theory of braking losses of slow ions in solids. The scheme of the model of the electronic friction mechanism is close to the Persson model, which connects the braking force with the electron scattering process. A refined formula for estimating the electronic friction force is proposed.
 The strength of phonon friction is justified on the basis of structural effects that can be induced by the mechanism of breaking adhesive bonds, and perturbation theory. A formula was obtained for estimating the force of phonon friction, taking into account the frequency of phonons, the inverse decay time and the function of the two-dimensional Fourier image of the force of interaction between the atoms of the conjugated surface of the triboelement.
 Cases of static and dynamic phonon friction are considered.
 Electronic and phonon frictional forces are considered at the nanolevel. The Debye low-temperature approximation and refinement of the expressions for estimating the electronic and phonon friction forces are given, taking into account the type of interatomic potential

Electric and magnetic metal-insulator-metal metasurfaces in the mid-infrared based on Babinet’s, Lorentz’s, and Kirchhoff’s principles

Metasurfaces can extend the optical properties of conventional materials by structuring surfaces at a subwavelength scale. These artificial subwavelength surfaces mimic the physics of conventional materials and can, in principle, be designed to provide novel optical material properties. Metal-insulator-metal (MIM) antenna metasurfaces are among the most widely used as ideal absorbers and emitters. In this work, we present MIM metasurfaces in the mid-infrared that comply in the electric and magnetic forms of Babinet’s, Lorentz’s, and Kirchhoff’s principles. To verify the validity of Babinet's, Lorentz's, and Kirchhoff's MIM metasurfaces, we computed their reflection and absorption spectra as well as electric and magnetic field maps. We found that even in the presence of graphene on top of the electric and magnetic MIM metasurfaces, these principles still hold qualitatively. However, the excitation of gap surface plasmon polaritons (SPPs) and graphene SPPs fails to comply quantitatively. Additionally, we fabricated the MIM metasurfaces and used imaging Fourier transform infrared spectroscopy in the mid infrared spectrum to validate them. Finally, we explore the potentials and limits of the use of graphene as tunability material, with a tunability bandwidth up to 0.6 µm. Our findings can be applied to the development of electric and magnetic frequency selectivity metasurfaces, polarizers, coherent thermal sources, and detectors.

Quantifying flare combustion efficiency using an imaging Fourier transform spectrometer

ABSTRACT Mid-wavelength infrared (MWIR) imaging Fourier transform spectrometers (IFTSs) are a promising technology for measuring flare combustion efficiency (CE) and destruction removal efficiency (DRE). These devices generate spectrally resolved intensity images of the flare plume, which may then be used to infer column densities of relevant species along each pixel line-of-sight. In parallel, a 2D projected velocity field may be inferred from the apparent motion of flow features between successive images. Finally, the column densities and velocity field are combined to estimate the mass flow rates for the species needed to calculate the CE or DRE. Since the MWIR IFTS can measure key carbon-containing species in the flare plume, it is possible to measure CE without knowing the fuel flow rate, which is important for fenceline measurements. This work demonstrates this approach on a laboratory heated vent, and then deploys the technique on two working flares: a combustor burning natural gas at a known rate, and a steam-assisted flare at a petrochemical refinery. Analysis of the IFTS data highlights the potential of this approach, but also areas for future development to transform this approach into a reliable technique for quantifying flare emissions. Implications: Our research is motivated by the need to assess hydrocarbon emissions from flaring, which is a critical problem of global significance. For example, recent studies have shown that methane destruction efficiency of flaring from upstream oil may be significantly lower than the commonly assumed figure of 98%; work by Plant et al., in particular, suggest that this discrepancy amounts to CO2 emissions from 2 to 8 million automobiles annually, considering the US alone. Similarly, the international energy agency (IEA) estimates a global flare efficiency of 92%,which translates in 8 million tons of CH4 emitted by flares in 2020. Highlighted by these studies and supported by the World Bankinitiatives toward zero routine flaring emissions, there is an urgent need for oil and gas industry to assess their flare methane emission, and overall hydrocarbon emissions. At the very least, it is critical to identify problematic flare operating conditions and means to mitigate flare emissions. Focusing on remote quantification of plume species, the measurement technique and quantification method presented in this paper is a considerable step forward in that direction by computing combustion efficiency and key components for destruction efficiency.

Ultrafast electro-optic time-frequency fractional Fourier imaging at the single-photon level.

The Fractional Fourier Transform (FRT) corresponds to an arbitrary-angle rotation in the phase space, e.g., the time-frequency (TF) space, and generalizes the fundamentally important Fourier Transform. FRT applications range from classical signal processing (e.g., time-correlated noise optimal filtering) to emerging quantum technologies (e.g., super-resolution TF sensing) which rely on or benefit from coherent low-noise TF operations. Here a versatile low-noise single-photon-compatible implementation of the FRT is presented. Optical TF FRT can be synthesized as a series of a spectral disperser, a time-lens, and another spectral disperser. Relying on the state-of-the-art electro-optic modulators (EOM) for the time-lens, our method avoids added noise inherent to the alternatives based on non-linear optical interactions (such as wave-mixing, cross-phase modulation, or parametric processes). Precise control of the EOM-driving radio-frequency signal enables fast all-electronic control of the FRT angle. In the experiment, we demonstrate FRT angles of up to 1.63 rad for pairs of coherent temporally separated 11.5 ps-wide pulses in the near-infrared (800 nm). We observe a good agreement between the simulated and measured output spectra in the bright-light and single-photon-level regimes, and for a range of pulse separations (20 ps to 26.7 ps). Furthermore, a tradeoff is established between the maximal FRT angle and optical bandwidth, with the current setup accommodating up to 248 GHz of bandwidth. With the ongoing progress in EOM on-chip integration, we envisage excellent scalability and vast applications in all-optical TF processing both in the classical and quantum regimes.

Fourier imaging for nanophotonics

Abstract Standard optical characterization and spectroscopy techniques rely on the measurement of specular reflection, transmission, or emission at normal incidence. Although the usefulness of these methods is without question, they do not provide information on the angular dependence of the scattered light and, therefore, miss crucial insights on the physical processes governing light emission and scattering. In this Review, we explain the basics of Fourier imaging and show how it can be used to measure the angular distribution of scattered light in single-shot measurements. We then give a comprehensive panorama on recent research exploiting this technique to analyze nanostructures and detail how it unlocks fundamental understandings on the underlying physics of nanophotonic structures. We finally describe how simple additions to a Fourier imaging setup enable measuring not only the radiation pattern of an object but also the energy, polarization, and phase toward resolving all aspects of light in real time.

High-spectral-resolution Observations of the Optical Filamentary Nebula Surrounding NGC 1275

We present new high-spectral-resolution observations (R = λ/Δλ = 7000) of the filamentary nebula surrounding NGC 1275, the central galaxy of the Perseus cluster. These observations have been obtained with SITELLE, an imaging Fourier transform spectrometer installed on the Canada–France–Hawai Telescope with a field of view of 11′×11′ , encapsulating the entire filamentary structure of ionized gas despite its large size of 80 kpc × 50 kpc. Here, we present renewed fluxes, velocities, and velocity dispersion maps that show in great detail the kinematics of the optical nebula at [S ii] λ6716, [S ii] λ6731, [N ii] λ6584, Hα (6563 Å), and [N ii] λ6548. These maps reveal the existence of a bright flattened disk-shaped structure in the core extending to r ∼10 kpc and dominated by a chaotic velocity field. This structure is located in the wake of X-ray cavities and characterized by a high mean velocity dispersion of 134 km s−1. The disk-shaped structure is surrounded by an extended array of filaments spread out to r ∼ 50 kpc that are 10 times fainter in flux, remarkably quiescent, and have a uniform mean velocity dispersion of 44 km s−1. This stability is puzzling given that the cluster core exhibits several energetic phenomena. Based on these results, we argue that there are two mechanisms that form multiphase gas in clusters of galaxies: a first triggered in the wake of X-ray cavities leading to more turbulent multiphase gas and a second, distinct mechanism, that is gentle and leads to large-scale multiphase gas spreading throughout the core.

Ultrafast Bragg coherent diffraction imaging of epitaxial thin films using deep complex-valued neural networks

Domain wall structures form spontaneously due to epitaxial misfit during thin film growth. Imaging the dynamics of domains and domain walls at ultrafast timescales can provide fundamental clues to features that impact electrical transport in electronic devices. Recently, deep learning based methods showed promising phase retrieval (PR) performance, allowing intensity-only measurements to be transformed into snapshot real space images. While the Fourier imaging model involves complex-valued quantities, most existing deep learning based methods solve the PR problem with real-valued based models, where the connection between amplitude and phase is ignored. To this end, we involve complex numbers operation in the neural network to preserve the amplitude and phase connection. Therefore, we employ the complex-valued neural network for solving the PR problem and evaluate it on Bragg coherent diffraction data streams collected from an epitaxial La2-xSrxCuO4 (LSCO) thin film using an X-ray Free Electron Laser (XFEL). Our proposed complex-valued neural network based approach outperforms the traditional real-valued neural network methods in both supervised and unsupervised learning manner. Phase domains are also observed from the LSCO thin film at an ultrafast timescale using the complex-valued neural network.

Reconstructing robust background integral field unit spectra using machine learning

ABSTRACT In astronomy, spectroscopy consists of observing an astrophysical source and extracting its spectrum of electromagnetic radiation. Once extracted, a model is fit to the spectra to measure the observables, leading to an understanding of the underlying physics of the emission mechanism. One crucial, and often overlooked, aspect of this model is the background emission, which contains foreground and background astrophysical sources, intervening atmospheric emission, and artefacts related to the instrument such as noise. This paper proposes an algorithmic approach to constructing a background model for SITELLE observations using statistical tools and supervised machine learning algorithms. SITELLE is an imaging Fourier transform spectrometer located at the Canada-France-Hawaii Telescope, which produces a three-dimensional data cube containing the position of the emission (two dimensions) and the spectrum of the emission. SITELLE has a wide field of view (11 arcmin × 11 arcmin), which makes the background emission particularly challenging to model. We apply a segmentation algorithm implemented in photutils to divide the data cube into background and source spaxels. After applying a principal component analysis (PCA) on the background spaxels, we train an artificial neural network to interpolate from the background to the source spaxels in the PCA coefficient space, which allows us to generate a local background model over the entire data cube. We highlight the performance of this methodology by applying it to SITELLE observations obtained of a Star-formation, Ionized Gas and Nebular Abundances Legacy Survey galaxy, NGC 4449, and the Perseus galaxy cluster of galaxies, NGC 1275. We discuss the physical interpretation of the principal components and noise reduction in the resulting PCA-based reconstructions. Additionally, we compare the fit results using our new background modelling approach with standard methods used in the literature and find that our method better captures the emission from H ii regions in NGC 4449 and the faint emission regions in NGC 1275. These methods also demonstrate that the background does change as a function of the position of the data cube. While the approach is applied explicitly to SITELLE data in this study, we argue that it can be readily adapted to any integral field unit style data, enabling the user to obtain more robust measurements on the flux of the emission lines.