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Journal articles on the topic 'Imagerie IR'

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Published: 7 July 2024

Last updated: 7 July 2024

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1

Loye, Dominique. "Rendre le signe distinctif visible dans l'infrarouge thermique." Revue Internationale de la Croix-Rouge 79, no. 824 (April 1997): 212–16. http://dx.doi.org/10.1017/s0035336100059098.

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Depuis de nombreuses années, les forces armées développent de nouveaux moyens d'observation afin d'augmenter leur capacité de mener le combat à toute heure et par tous les temps. Plusieurs forces armées se sont ainsi équipées de caméras à imagerie thermique (IR) qui permettent de reconnaître et de détecter des personnes et des objets non seulement de nuit, mais aussi de jour, même quand la visibilité est restreinte (comme, par exemple, à travers la fumée, le feuillage ou la pluie légère).

2

Kamiya, K., T. Fuse, and M. Takahashi. "APPLICABILITY EVALUATION OF OBJECT DETECTION METHOD TO SATELLITE AND AERIAL IMAGERIES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (June 21, 2016): 229–34. http://dx.doi.org/10.5194/isprs-archives-xli-b7-229-2016.

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Since satellite and aerial imageries are recently widely spread and frequently observed, combination of them are expected to complement spatial and temporal resolution each other. One of the prospective applications is traffic monitoring, where objects of interest, or vehicles, need to be recognized automatically. Techniques that employ <i>object detection</i> before <i>object recognition</i> can save a computational time and cost, and thus take a significant role. However, there is not enough knowledge whether object detection method can perform well on satellite and aerial imageries. In addition, it also has to be studied how characteristics of satellite and aerial imageries affect the object detection performance. This study employ binarized normed gradients (BING) method that runs significantly fast and is robust to rotation and noise. For our experiments, 11-bits BGR-IR satellite imageries from WorldView-3, and BGR-color aerial imageries are used respectively, and we create thousands of ground truth samples. We conducted several experiments to compare the performances with different images, to verify whether combination of different resolution images improved the performance, and to analyze the applicability of mixing satellite and aerial imageries. The results showed that infrared band had little effect on the detection rate, that 11-bit images performed less than 8-bit images and that the better spatial resolution brought the better performance. Another result might imply that mixing higher and lower resolution images for training dataset could help detection performance. Furthermore, we found that aerial images improved the detection performance on satellite images.

3

Kamiya, K., T. Fuse, and M. Takahashi. "APPLICABILITY EVALUATION OF OBJECT DETECTION METHOD TO SATELLITE AND AERIAL IMAGERIES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (June 21, 2016): 229–34. http://dx.doi.org/10.5194/isprsarchives-xli-b7-229-2016.

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Since satellite and aerial imageries are recently widely spread and frequently observed, combination of them are expected to complement spatial and temporal resolution each other. One of the prospective applications is traffic monitoring, where objects of interest, or vehicles, need to be recognized automatically. Techniques that employ <i>object detection</i> before <i>object recognition</i> can save a computational time and cost, and thus take a significant role. However, there is not enough knowledge whether object detection method can perform well on satellite and aerial imageries. In addition, it also has to be studied how characteristics of satellite and aerial imageries affect the object detection performance. This study employ binarized normed gradients (BING) method that runs significantly fast and is robust to rotation and noise. For our experiments, 11-bits BGR-IR satellite imageries from WorldView-3, and BGR-color aerial imageries are used respectively, and we create thousands of ground truth samples. We conducted several experiments to compare the performances with different images, to verify whether combination of different resolution images improved the performance, and to analyze the applicability of mixing satellite and aerial imageries. The results showed that infrared band had little effect on the detection rate, that 11-bit images performed less than 8-bit images and that the better spatial resolution brought the better performance. Another result might imply that mixing higher and lower resolution images for training dataset could help detection performance. Furthermore, we found that aerial images improved the detection performance on satellite images.

4

Lloyd, James, and Magda Marczak. "Imagery rescripting and negative self-imagery in social anxiety disorder: a systematic literature review." Behavioural and Cognitive Psychotherapy 50, no. 3 (February 28, 2022): 280–97. http://dx.doi.org/10.1017/s135246582200008x.

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AbstractBackground:Imagery rescripting (IR) is an effective intervention for social anxiety disorder (SAD) that targets memories of distressing formative events linked to negative self-imagery (NSI). IR is thought to update unhelpful schema by addressing the needs of the younger self within the memory. An accumulating body of evidence indicates that by modifying NSI, IR can significantly affect distressing imagery, memory appraisal, and beliefs about the self.Aims:This systematic review aims to critically evaluate and synthesise literature investigating the existing research on the effects IR has on NSI in SAD.Method:A systematic electronic search of Academic Search Complete, ProQuest, Medline, Scopus and PubMed was performed in February 2021 using pre-defined criteria. Ten studies met the inclusion criteria and were selected for review.Results:Analysis of the reviewed articles’ findings identified three main themes: Changes to negative self-images, Memories linked to images and Encapsulated beliefs. IR was associated with significant decreases in image distress, image vividness, memory vividness, memory distress, and encapsulated beliefs. Although reductions were found with image frequency, they were non-significant. Interpretation of results is limited by the small number of studies.Conclusions:IR appears to effectively alter images, memories and beliefs in SAD in as little as a single session. The findings indicate that IR could be utilised as a cost-effective intervention for SAD. However, additional studies and longer-term follow-ups are needed.

5

PORCÚ, F., and V. LEVIZZANI. "Cloud classification using METEOSAT VIS-IR imagery." International Journal of Remote Sensing 13, no. 5 (March 1992): 893–909. http://dx.doi.org/10.1080/01431169208904162.

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6

Liu, Chunguang, Jiancheng Shi, Tianxing Wang, Kirpa Ram, and Tianjie Zhao. "Mathematical Assessment of the Effects of Substituting the Band Radiative Transfer Equation (RTE) for the Spectral RTE in the Applications of Earth’s Surface Temperature Retrievals from Spaceborne Infrared Imageries." Remote Sensing 11, no. 3 (January 22, 2019): 226. http://dx.doi.org/10.3390/rs11030226.

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The Planck’s thermal emission function, the reflectivity-emissivity decoupled Kirchhoff’s law and the associated atmospheric radiative transfer equation (RTE) is a theoretical base for Earth surface temperature (ST) retrievals from spaceborne infrared imageries. The infrared (IR) instruments generally collect band averaged radiance which are usually different from the RT codes simulated spectral one. Although IR band RTE is widely used, the effects of substituting the band-averaged RTE for the corresponding spectral one for those broadband observations (e.g., the Moderate Resolution Imaging Spectroradiometer (MODIS) thermal IR bands) have not been evaluated. In this paper, mathematical analysis and numerical experiments have been conducted to clarify the uncertainties arising from this substitution treatment. Firstly, we present the IR spectral RTE in a concise manner, and then, based on the law of conservation of energy and the integral assumption, a detailed mathematical derivation of the commonly-used IR band RTE has been derived. The significant improvement of the derivation is the validation of the integral assumption, which states that over a small spectral region, the integral of a product is approximately equal to the product of integrals. In the IR spectral region, taking the most significant term of the IR band RTE as an example (i.e., the surface emission term), we confirmed that, for the satellite collected IR signals emitted from the Earth’s surface, over any bandwidth at any band-location and under any instrument spectral response function (SRF), the integral approximation (IA) is a well-founded approximation and thus the IR band RTEs are good approximations for the corresponding spectral ones. Furthermore, in the ST, especially the land ST, product validation investigations, the ST errors introduced by the substituting treatment are negligible and do not need to be taken into consideration.

7

Takanashi, Rieko, Naoki Yoshinaga, Keiko Oshiro, Satoshi Matsuki, Mari Tanaka, Hanae Ibuki, Fumiyo Oshima, Yuko Urao, Daisuke Matsuzawa, and Eiji Shimizu. "Patients’ perspectives on imagery rescripting for aversive memories in social anxiety disorder." Behavioural and Cognitive Psychotherapy 48, no. 2 (September 17, 2019): 229–42. http://dx.doi.org/10.1017/s1352465819000493.

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AbstractBackground:Imagery rescripting (IR) for early aversive memories in patients with social anxiety disorder (SAD) has shown promising results, but no study has investigated the reactions and perspectives of patients who received IR.Aims:This study aimed to gain understanding of patients’ experiences/perspectives on IR as an adjunct to cognitive behavioural therapy (CBT) for SAD.Method:Twenty-five individuals with SAD received one or two sessions of IR over 16 CBT sessions. Contents of recurrent images and linked memories were identified during IR. Outcome measures included social anxiety, image and memory distress and vividness, and encapsulated belief. Patients completed a questionnaire about their perspectives of IR after the session. Thematic analysis was used to analyse the qualitative data.Results:IR resulted in significant within-session improvement in most outcome measures. Linked memories to negative recurrent images in social situations were categorized into nine groups. Common memories were ‘Being criticized by others’, ‘Being made fun of’, ‘Failing or not doing something well’ and ‘Being left out in a group’. Most patients (82%) experienced IR as impressive, and more than half of patients (59%) found IR effective. Themes of reasons of impressiveness and effectiveness were categorized as ‘Results of IR session’ and ‘Processes of IR session’. The theme ‘Results of IR session’ included six subthemes, and the theme ‘Processes of the IR session’ included five subthemes.Conclusions:Regarding patients’ perspectives, although they may experience negative emotions in the process of an IR session, our results suggest that many patients with SAD found IR sessions effective.

8

Collin, A., D. James, A. Mury, M. Letard, and B. Guillot. "PREDICTING THE INFRARED UAV IMAGERY OVER THE COAST." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B1-2021 (June 28, 2021): 149–56. http://dx.doi.org/10.5194/isprs-archives-xliii-b1-2021-149-2021.

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Abstract. The infrared (IR) imagery provides additional information to the visible (red-green-blue, RGB) about vegetation, soil, water, mineral, or temperature, and has become essential for various disciplines, such as geology, hydrology, ecology, archeology, meteorology or geography. The integration of the IR sensors, ranging from near-IR (NIR) to thermal-IR through mid-IR, constitutes a baseline for Earth Observation satellites but not for unmanned airborne vehicles (UAV). Given the hyperspatial and hypertemporal characteristics associated with the UAV survey, it is relevant to benefit from the IR waveband in addition to the visible imagery for mapping purposes. This paper proposes to predict the NIR reflectance from RGB digital number predictors collected with a consumer-grade UAV over a structurally and compositionally complex coastal area. An array of 15 000 data, distributed into calibration, validation and test datasets across 15 representative coastal habitats, was used to build and compare the performance of the standard least squares, decision tree, boosted tree, bootstrap forest and fully connected neural network (NN) models. The NN family surpassed the four other ones, and the best NN model (R2 = 0.67) integrated two hidden layers provided, each, with five nodes of hyperbolic tangent and five nodes of Gaussian activation functions. This perceptron enabled to produce a NIR reflectance spatially-explicit model deprived of original artifacts due to the flight constraints. At the habitat scale, sedimentary and dry vegetation environments were satisfactorily predicted (R2 > 0.6), contrary to the healthy vegetation (R2 < 0.2). Those innovative findings will be useful for scientists and managers tasked with hyperspatial and hypertemporal mapping.

9

Solnyshkin, A. V., G. Suchaneck, I. L. Kislova, and G. Gerlach. "Modeling of a Pyroelectric Thin Film IR Imager." Ferroelectrics 353, no. 1 (May 18, 2007): 225–32. http://dx.doi.org/10.1080/00150190701368182.

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10

Coustenis, Athena. "Titan's amosphere and surface from IR spectroscopy and imagery." Advances in Space Research 19, no. 8 (January 1997): 1288. http://dx.doi.org/10.1016/s0273-1177(97)83127-4.

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11

Heinz, Daniel C., Charles E. Davidson, and Avishai Ben-David. "Temporal-Spectral Detection in Long-Wave IR Hyperspectral Imagery." IEEE Sensors Journal 10, no. 3 (March 2010): 509–17. http://dx.doi.org/10.1109/jsen.2009.2038624.

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12

Jaewan, Choi. "Unsupervised Change Detection for Very High-spatial Resolution Satellite Imagery by Using Object-based IR-MAD Algorithm." Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography 33, no. 4 (August 31, 2015): 297–304. http://dx.doi.org/10.7848/ksgpc.2015.33.4.297.

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13

Kunze, Anna E., Arnoud Arntz, and Merel Kindt. "Investigating the effects of imagery rescripting on emotional memory: A series of analogue studies." Journal of Experimental Psychopathology 10, no. 2 (April 1, 2019): 204380871985073. http://dx.doi.org/10.1177/2043808719850733.

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Imagery rescripting (IR) is a promising treatment for a variety of disorders, but its working mechanisms remain largely unknown. To elucidate the associative and evaluative learning processes underlying IR, we exposed participants to an aversive film clip followed by an instructed fear-conditioning procedure. The acquired fear memory was subsequently manipulated by either rescripting- (IR) or exposure-based (imaginal exposure; IE) interventions and their effects were examined on subjective and psychophysiological fear responses in three successive studies. Though the interpretation of the results was challenged with respect to the employed analogue IR intervention (Exp 1) and unexpected findings in the control condition (Exp 3), the present results establish preliminary evidence for the hypothesis that IR produces differential effects on fear responding when compared to IE. For example, in line with stimulus devaluation theory, IR effectively reduced subjective distress to the conditioned stimulus (Exp 2). Also, IR resulted in decreased physiological fear responses after fear reinstatement (Exp 3). The findings advance our general understanding of the processes involved in IR and they tentatively indicate that rescripting- and exposure-based treatments may work through different mechanisms. Moreover, this line of research demonstrates the challenges encountered when working with analogue models to test mechanisms of therapeutic change.

14

Paulish, A. G., B. N. Novgorodov, S. V. Khryashchev, and S. A. Kuznetsov. "Terahertz Imager Based on a THz-to-IR Converter." Optoelectronics, Instrumentation and Data Processing 55, no. 1 (January 2019): 45–51. http://dx.doi.org/10.3103/s8756699019010084.

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15

Vauglin, I., P. Prugniel, and M. Koleva. "A wide field IR imager at Concordia and HyperLeda." EAS Publications Series 40 (December 24, 2009): 207–10. http://dx.doi.org/10.1051/eas/1040030.

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16

Jordan, Jay B., W. R. Watkins, F. R. Palacios, and D. R. Billingsley. "Simulated dynamic effects of atmospheric turbulence on IR digital imagery." Infrared Physics & Technology 37, no. 5 (August 1996): 607–17. http://dx.doi.org/10.1016/1350-4495(95)00127-1.

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17

Ng, Eddie Y. K., G. J. L. Kawb, and W. M. Chang. "Analysis of IR thermal imager for mass blind fever screening." Microvascular Research 68, no. 2 (September 2004): 104–9. http://dx.doi.org/10.1016/j.mvr.2004.05.003.

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18

Bouchet, P., R. Gastaud, A. Coulais, M. J. Barlow, C. Fransson, P. J. Kavanagh, J. Larsson, et al. "JWST MIRI Imager Observations of Supernova SN 1987A." Astrophysical Journal 965, no. 1 (April 1, 2024): 51. http://dx.doi.org/10.3847/1538-4357/ad2770.

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Abstract There exist very few mid-infrared (IR) observations of supernovae (SNe) in general. Therefore, SN 1987A, the closest visible SN in 400 yr, gives us the opportunity to explore the mid-IR properties of SNe, the dust in their ejecta, and the surrounding medium and to witness the birth of an SN remnant (SNR). The James Webb Space Telescope, with its high spatial resolution and extreme sensitivity, gives a new view on these issues. We report on the first imaging observations obtained with the Mid-InfraRed Instrument (MIRI). We build temperature maps and discuss the morphology of the nascent SNR. Our results show that the temperatures in the equatorial ring (ER) are quite nonuniform. This could be due to dust destruction in some parts of the ring, as had been assumed in some previous works. We show that the IR emission extends beyond the ER, illustrating the fact that the shock wave has now passed through this ring to affect the circumstellar medium on a larger scale. Finally, while submillimeter Atacama Large Millimeter Array observations have hinted at the location of the compact remnant of SN 1987A, we note that our MIRI data have found no such evidence.

19

Waxman, Allen M., Michael C. Seibert, Alan Gove, David A. Fay, Ann Marie Bernardon, Carol Lazott, William R. Steele, and Robert K. Cunningham. "Neural processing of targets in visible, multispectral IR and SAR imagery." Neural Networks 8, no. 7-8 (January 1995): 1029–51. http://dx.doi.org/10.1016/0893-6080(95)00080-1.

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20

Envall, J., S. N. Mekhontsev, Y. Zong, and L. M. Hanssen. "Spatial Scatter Effects in the Calibration of IR Pyrometers and Imagers." International Journal of Thermophysics 30, no. 1 (January 10, 2009): 167–78. http://dx.doi.org/10.1007/s10765-008-0547-1.

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21

Michel, J. D., N. Nandhakumar, Tushar Saxena, and Deepak Kapur. "Geometric, Algebraic, and Thermophysical Techniques for Object Recognition in IR Imagery." Computer Vision and Image Understanding 72, no. 1 (October 1998): 84–97. http://dx.doi.org/10.1006/cviu.1997.0669.

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22

Mecikalski, John R., and Kristopher M. Bedka. "Forecasting Convective Initiation by Monitoring the Evolution of Moving Cumulus in Daytime GOES Imagery." Monthly Weather Review 134, no. 1 (January 1, 2006): 49–78. http://dx.doi.org/10.1175/mwr3062.1.

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Abstract This study identifies the precursor signals of convective initiation within sequences of 1-km-resolution visible (VIS) and 4–8-km infrared (IR) imagery from the Geostationary Operational Environmental Satellite (GOES) instrument. Convective initiation (CI) is defined for this study as the first detection of Weather Surveillance Radar-1988 Doppler (WSR-88D) reflectivities ≥35 dBZ produced by convective clouds. Results indicate that CI may be forecasted ∼30–45 min in advance through the monitoring of key IR fields for convective clouds. This is made possible by the coincident use of three components of GOES data: 1) a cumulus cloud “mask” at 1-km resolution using VIS and IR data, 2) satellite-derived atmospheric motion vectors (AMVs) for tracking individual cumulus clouds, and 3) IR brightness temperature (TB) and multispectral band-differencing time trends. In effect, these techniques isolate only the cumulus convection in satellite imagery, track moving cumulus convection, and evaluate various IR cloud properties in time. Convective initiation is predicted by accumulating information within a satellite pixel that is attributed to the first occurrence of a ≥35 dBZ radar echo. Through the incorporation of satellite tracking of moving cumulus clouds, this work represents a significant advance in the use of routinely available GOES data for monitoring aspects of cumulus clouds important for nowcasting CI (0–1-h forecasts). Once cumulus cloud tracking is established, eight predictor fields based on Lagrangian trends in IR data are used to characterize cloud conditions consistent with CI. Cumulus cloud pixels for which ≥7 of the 8 CI indicators are satisfied are labeled as having high CI potential, assuming an extrapolation of past trends into the future. Comparison to future WSR-88D imagery then measures the method's predictive skill. Convective initiation predictability is demonstrated using several convective events—one during IHOP_2002—that occur over a variety of synoptic and mesoscale forcing regimes.

23

Prakash, S., D. Jindal, N. Badal, B. Kartikeyan, and B. Gopala Krishna. "Radiometric Quality Evaluation of INSAT-3D Imager Data." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-8 (November 28, 2014): 299–305. http://dx.doi.org/10.5194/isprsarchives-xl-8-299-2014.

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INSAT-3D is an advanced meteorological satellite of ISRO which acquires imagery in optical and infra-red (IR) channels for study of weather dynamics in Indian sub-continent region. In this paper, methodology of radiometric quality evaluation for Level-1 products of Imager, one of the payloads onboard INSAT-3D, is described. Firstly, overall visual quality of scene in terms of dynamic range, edge sharpness or modulation transfer function (MTF), presence of striping and other image artefacts is computed. Uniform targets in Desert and Sea region are identified for which detailed radiometric performance evaluation for IR channels is carried out. Mean brightness temperature (BT) of targets is computed and validated with independently generated radiometric references. Further, diurnal/seasonal trends in target BT values and radiometric uncertainty or sensor noise are studied. Results of radiometric quality evaluation over duration of eight months (January to August 2014) and comparison of radiometric consistency pre/post yaw flip of satellite are presented. Radiometric Analysis indicates that INSAT-3D images have high contrast (MTF > 0.2) and low striping effects. A bias of <4K is observed in the brightness temperature values of TIR-1 channel measured during January–August 2014 indicating consistent radiometric calibration. Diurnal and seasonal analysis shows that Noise equivalent differential temperature (NEdT) for IR channels is consistent and well within specifications.

24

Newman-Taylor, Katherine, Pamela McSherry, and Lusia Stopa. "Imagery rescripting in non-clinical paranoia: a pilot study of the impact on key cognitive and affective processes." Behavioural and Cognitive Psychotherapy 48, no. 1 (July 15, 2019): 54–66. http://dx.doi.org/10.1017/s1352465819000419.

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AbstractBackground:Paranoia is often accompanied by distressing intrusions associated with traumatic memories, yet one of the best-evidenced interventions, imagery rescripting (IR), is not routinely offered. This is likely to be due to poor understanding of the effects of IR on postulated mechanisms of change as well as the absence of a robust evidence base.Aims:This study aimed to establish proof of principle that IR impacts key cognitive-affective processes associated with distressing intrusions – memory characteristics and self-representations – and level of paranoia.Method:We used a within-subject repeated measures design to examine the effect of single-session IR on memory characteristics (level of intrusions, vividness, distress, encapsulated belief strength, emotion intensity and frequency), self-representation variables, affect and paranoia. Fifteen participants were seen once before and once after the IR session, to gather baseline and follow-up data.Results:As predicted, participants reported reductions in memory characteristics, improved self-esteem and positive affect, and reduced negative affect and paranoia, with large effect sizes. These effects were maintained at follow-up.Conclusions:While a within-subject design is useful for initial exploration of novel interventions, controlled studies are needed to determine causality. This is the first study to examine mechanisms of IR in paranoia. A controlled trial is now warranted.

25

Summy, Kenneth R., and Christopher R. Little. "Using Color Infrared Imagery to Detect Sooty Mold and Fungal Pathogens of Glasshouse-propagated Plants." HortScience 43, no. 5 (August 2008): 1485–91. http://dx.doi.org/10.21273/hortsci.43.5.1485.

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Fungi are major biotic constraints for optimum production and quality of glasshouse plants. When plants are infested with sooty mold (Capnodium spp.) or infected with pathogens, the reflected wavelengths of the electromagnetic spectrum are altered. Spectroradiometric measurements and color infrared (CIR) images of control, honeydew-coated, and sooty mold-infested saplings and individual leaves from trifoliate orange (Poncirus trifoliata), sour orange (Citrus aurantium), ‘Valencia’ orange (C. sinensis), and ‘Bo’ tree (Ficus religiosa) were obtained. Grapefruit saplings and individual leaves infected with Mycosphaerella citri (greasy spot) were imaged under glasshouse conditions. Similarly, muskmelon foliage showing low and high levels of powdery mildew (Sphaerotheca fuliginea) disease severity were analyzed. When examining individual leaves, all fungal biotic stressors generally resulted in variable spectral reflectance data, especially in the blue (450 nm) and green (550 nm) wavelengths; however, values in the red (650 nm) tended to increase and values in the near-IR (850 nm) tended to decrease with stress. Near-IR/red image ratios were significantly reduced (P < 0.05) in stressed whole plant foliage and individual leaves relative to healthy controls. The accumulation of insect honeydew (which occurs before sooty mold infestation) significantly increased (P < 0.05) near-IR reflectance values and near-IR/red ratios in ‘Valencia’ orange and near-IR/ratios in ‘Bo’ tree foliage and individual leaves. Image acquisition and enhancement techniques may prove useful in large-scale production greenhouses where existing infrastructure and high plant populations require high throughput data analysis and identification of biotic stressors.

26

Beckman, Samuel K. "Use of Enhanced IR/Visible Satellite Imagery to Determine Heavy Snow Areas." Monthly Weather Review 115, no. 9 (September 1987): 2060–87. http://dx.doi.org/10.1175/1520-0493(1987)115<2060:uoeisi>2.0.co;2.

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27

Manizade, K. F., J. D. Spinhirne, and R. S. Lancaster. "Stereo Cloud Heights From Multispectral IR Imagery via Region-of-Interest Segmentation." IEEE Transactions on Geoscience and Remote Sensing 44, no. 9 (September 2006): 2481–91. http://dx.doi.org/10.1109/tgrs.2006.873339.

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28

Bellerby, T. J. "A Feature-Based Approach to Satellite Precipitation Monitoring Using Geostationary IR Imagery." Journal of Hydrometeorology 5, no. 5 (October 2004): 910–21. http://dx.doi.org/10.1175/1525-7541(2004)005<0910:afatsp>2.0.co;2.

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29

Rich, Evan A., John P. Wisniewski, Satoshi Mayama, Timothy D. Brandt, Jun Hashimoto, Tomoyuki Kudo, Nobuhiko Kusakabe, et al. "NEAR-IR POLARIZED SCATTERED LIGHT IMAGERY OF THE DoAr 28 TRANSITIONAL DISK." Astronomical Journal 150, no. 3 (August 25, 2015): 86. http://dx.doi.org/10.1088/0004-6256/150/3/86.

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30

Kaufman, Yoram J., and Claudia Sendra. "Algorithm for automatic atmospheric corrections to visible and near-IR satellite imagery." International Journal of Remote Sensing 9, no. 8 (August 1988): 1357–81. http://dx.doi.org/10.1080/01431168808954942.

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31

Wang, Xiao-rui, Jian-qi Zhang, Zhuo-xiang Feng, and Hong-hua Chang. "Analysis of improvement amount of typical microscanning modes to IR imagery quality." Infrared Physics & Technology 46, no. 5 (June 2005): 412–17. http://dx.doi.org/10.1016/j.infrared.2004.09.003.

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32

Castellano, Gabriela, James Boyce, and Mark Sandler. "Regularized CDWT optical flow applied to moving-target detection in IR imagery." Machine Vision and Applications 11, no. 6 (May 1, 2000): 277–88. http://dx.doi.org/10.1007/s001380050112.

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33

Knaff, John A., and Robert T. DeMaria. "Forecasting Tropical Cyclone Eye Formation and Dissipation in Infrared Imagery." Weather and Forecasting 32, no. 6 (November 9, 2017): 2103–16. http://dx.doi.org/10.1175/waf-d-17-0037.1.

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Abstract The development of an infrared (IR; specifically near 11 μm) eye probability forecast scheme for tropical cyclones is described. The scheme was developed from an eye detection algorithm that used a linear discriminant analysis technique to determine the probability of an eye existing in any given IR image given information about the storm center, motion, and latitude. Logistic regression is used for the model development and predictors were selected from routine information about the current storm (e.g., current intensity), forecast environmental factors (e.g., wind shear, oceanic heat content), and patterns/information (e.g., convective organization, tropical cyclone size) extracted from the current IR image. Forecasts were created for 6-, 12-, 18-, 24-, and 36-h forecast leads. Forecasts were developed using eye existence probabilities from North Atlantic tropical cyclone cases (1996–2014) and a combined North Atlantic and North Pacific (i.e., Northern Hemisphere) sample. The performance of North Atlantic–based forecasts, tested using independent eastern Pacific tropical cyclone cases (1996–2014), shows that the forecasts are skillful versus persistence at 12–36 h, and skillful versus climatology at 6–36 h. Examining the reliability and calibration of those forecasts shows that calibration and reliability of the forecasts is good for 6–18 h, but forecasts become a little overconfident at longer lead times. The forecasts also appear unbiased. The small differences between the Atlantic and Northern Hemisphere formulations are discussed. Finally, and remarkably, there are indications that smaller TCs are more prone to form eye features in all of the TC areas examined.

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Zagubisalo, Peter S., Andrey G. Paulish, and Sergey A. Kuznetsov. "Simulation of thermal processes in metamaterial millimeter-wave to infrared converter for millimeter-wave imager." International Journal of Modeling, Simulation, and Scientific Computing 05, supp01 (October 2014): 1441009. http://dx.doi.org/10.1142/s1793962314410098.

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The main characteristics of millimeter-wave (MM-wave) image detector were simulated by means of accurate numerical modeling of thermophysical processes in a metamaterial MM-to-IR converter. The converter represents a multilayer structure consisting of an ultra thin resonant metamaterial absorber and a perfect emissive layer. The absorber consists of a dielectric self-supporting film that is metallized from both sides. A micro-pattern is fabricated from one side. Resonant absorption of the MM waves induces the converter heating that yields enhancement of IR emission from the emissive layer. IR emission is detected by IR camera. In this contribution an accurate numerical model for simulation of the thermal processes in the converter structure was created by using COMSOL Multiphysics software. The simulation results are in a good agreement with experimental results that validates the model. The simulation shows that the real-time operation is provided for the converter thickness less than 3 μm and time response can be improved by decreasing of the converter thickness. The energy conversion efficiency of MM waves into IR radiation is over 80%. The converter temperature increase is a linear function of a MM-wave radiation power within three orders of the dynamic range. The blooming effect and ways of its reducing are also discussed. The model allows us to choose the ways of converter structure optimization and improvement of image detector parameters.

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Gunshor, Mathew M., Timothy J. Schmit, W. Paul Menzel, and David C. Tobin. "Intercalibration of Broadband Geostationary Imagers Using AIRS." Journal of Atmospheric and Oceanic Technology 26, no. 4 (April 1, 2009): 746–58. http://dx.doi.org/10.1175/2008jtecha1155.1.

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Abstract Geostationary simultaneous nadir observations (GSNOs) are collected for Earth Observing System (EOS) Atmospheric Infrared Sounder (AIRS) on board Aqua and a global array of geostationary imagers. The imagers compared in this study are on (Geostationary Operational Environmental Satellites) GOES-10, GOES-11, GOES-12, (Meteorological Satellites) Meteosat-8, Meteosat-9, Multifunctional Transport Satellite-IR (MTSAT-IR), and Fenguyun-2C (FY-2C). It has been shown that a single polar-orbiting satellite can be used to intercalibrate any number of geostationary imagers. Using a high-spectral-resolution infrared sensor, in this case AIRS, brings this method closer to an absolute reckoning of imager calibration accuracy based on laboratory measurements of the instrument’s spectral response. An intercalibration method is presented here, including a method of compensating for AIRS’ spectral gaps, along with results for approximately 22 months of comparisons. The method appears to work very well for most bands, but there are still unresolved issues with bands that are not spectrally covered well by AIRS (such as the water vapor bands and the 8.7-μm band on Meteosat). To the first approximation, most of the bands on the world’s geostationary imagers are reasonably well calibrated—that is, they compare to within 1 K of a standard reference (AIRS). The next step in the evolution of geostationary intercalibration is to use Infrared Atmospheric Sounding Interferometer (IASI) data. IASI is a high-spectral-resolution instrument similar to AIRS but without significant spectral gaps.

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Liu, Hai Lei, Li Sheng Xu, Ji Lie Ding, Ba Sang, and Xiao Bo Deng. "An Atmospheric Correction Method for Medium Resolution Spectral Imager Thermal IR Soundings." Key Engineering Materials 500 (January 2012): 397–402. http://dx.doi.org/10.4028/www.scientific.net/kem.500.397.

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Based on the thermal radiative transfer equation (RTE), a new atmospheric correction method named Single Band Water Vapor Dependent (SBWVD) method is developed for land surface temperature (LST) retrieval for the FY-3A Medium Resolution Spectral Imager (MERSI) with only one thermal infrared (TIR) channel. Assuming that the surface emissivity is known, water vapor content (WVC) is the only one parameter for input to the SBWVD algorithm to retrieve LST from MERSI TIR observations. FY-3A MERSI Level 2 water vapor product is employed to evaluate the performance of the proposed method, and a 2-D data interpolation procedure is applied in order to match the MERSI L1B data in spatial resolution. Some tests, including numerical simulation for MERSI sensor and the synchronous measurements of MERSI and the radiosondes for the radiative calibration of the FY-3A tests in Qinghai Lake, have been carried out for the proposed algorithm, respectively. The results show that the difference between the retrieved LST and the in-situ measurements is less than 0.6 K for most situations. The comparison with the MODIS LST products (V5) shows that the root mean square error (RMSE) is under 0.72 K. Thus, our proposed new algorithm is applicable for the atmospheric correction and LST retrieval using MERSI TIR channel observations.

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Xu, Guibin, Huafeng Li, Yuwei Zang, Lianke Xie, and Chunxiao Bai. "Change Detection Based on IR-MAD Model for GF-5 Remote Sensing Imagery." IOP Conference Series: Materials Science and Engineering 768 (March 31, 2020): 072073. http://dx.doi.org/10.1088/1757-899x/768/7/072073.

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Jain, Ajay, Amit Sharma, SL Borana, Brahmmajyosula Ravindra, and JP Mangalhara. "Study and Analysis of Exhaust Emission of Diesel Vehicles using Thermal IR Imagers." Defence Science Journal 68, no. 6 (October 31, 2018): 533. http://dx.doi.org/10.14429/dsj.68.12701.

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<p>Exhaust emission analysis from diesel vehicles has received a lot of attention in recent times in the context of implementation of Bharat Stage-IV norms and thermal signature analysis for civil and military applications. The exhaust emission thermal IR signatures of military diesel vehicles such as truck and bus using a gas analyser and thermal imager under idling and accelerating conditions of these vehicles is investigated. Concentration and temperature of diesel exhaust emission CO, NOx, and HC remains almost constant during engine running in idle condition and varies with the engine acceleration. Exhaust gases maximum temperature reaches in the range of 240 °C - 270 °C during engine acceleration. A detailed investigation of thermal signature in mid wave infrared, 3 µm - 5 µm waveband and long wave infrared, 8 µm - 14 µm waveband is also presented under the same engine running conditions. Thermal image analysis exhibited that the area of thermal IR image of diesel vehicles truck and bus has been increased 0.077 per cent and 0.594 per cent, respectively with the engine acceleration. It has been observed that thermal signature of exhaust gases is a good tool for vehicle exhaust emission visualisation and analysis.</p>

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Waxman, Allen M., Alan N. Gove, David A. Fay, Joseph P. Racamato, James E. Carrick, Michael C. Seibert, and Eugene D. Savoye. "Color Night Vision: Opponent Processing in the Fusion of Visible and IR Imagery." Neural Networks 10, no. 1 (January 1997): 1–6. http://dx.doi.org/10.1016/s0893-6080(96)00057-3.

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Lee, Seung Won, and Jung-Hye Kwon. "The efficacy of Imagery Rescripting (IR) for social phobia: A randomized controlled trial." Journal of Behavior Therapy and Experimental Psychiatry 44, no. 4 (December 2013): 351–60. http://dx.doi.org/10.1016/j.jbtep.2013.03.001.

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Zhang, Tianxiang, Zhiyong Xu, Jinya Su, Zhifang Yang, Cunjia Liu, Wen-Hua Chen, and Jiangyun Li. "Ir-UNet: Irregular Segmentation U-Shape Network for Wheat Yellow Rust Detection by UAV Multispectral Imagery." Remote Sensing 13, no. 19 (September 28, 2021): 3892. http://dx.doi.org/10.3390/rs13193892.

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Crop disease is widely considered as one of the most pressing challenges for food crops, and therefore an accurate crop disease detection algorithm is highly desirable for its sustainable management. The recent use of remote sensing and deep learning is drawing increasing research interests in wheat yellow rust disease detection. However, current solutions on yellow rust detection are generally addressed by RGB images and the basic semantic segmentation algorithms (e.g., UNet), which do not consider the irregular and blurred boundary problems of yellow rust area therein, restricting the disease segmentation performance. Therefore, this work aims to develop an automatic yellow rust disease detection algorithm to cope with these boundary problems. An improved algorithm entitled Ir-UNet by embedding irregular encoder module (IEM), irregular decoder module (IDM) and content-aware channel re-weight module (CCRM) is proposed and compared against the basic UNet while with various input features. The recently collected dataset by DJI M100 UAV equipped with RedEdge multispectral camera is used to evaluate the algorithm performance. Comparative results show that the Ir-UNet with five raw bands outperforms the basic UNet, achieving the highest overall accuracy (OA) score (97.13%) among various inputs. Moreover, the use of three selected bands, Red-NIR-RE, in the proposed Ir-UNet can obtain a comparable result (OA: 96.83%) while with fewer spectral bands and less computation load. It is anticipated that this study by seamlessly integrating the Ir-UNet network and UAV multispectral images can pave the way for automated yellow rust detection at farmland scales.

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Prinz, Jessica, Eshkol Rafaeli, Jana Wasserheß, and Wolfgang Lutz. "Clients’ Emotional Experiences Tied to Therapist-Led (but Not Client-Led) Physiological Synchrony during Imagery Rescripting." Entropy 23, no. 12 (November 23, 2021): 1556. http://dx.doi.org/10.3390/e23121556.

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Imagery rescripting (IR), an effective intervention technique, may achieve its benefits through various change mechanisms. Previous work has indicated that client–therapist physiological synchrony during IR may serve as one such mechanism. The present work explores the possibility that therapist-led vs. client-led synchrony may be differentially tied to clients’ emotional experiences in therapy. The analyses were conducted with data taken from an open trial of a brief protocol for treating test anxiety (86 IR sessions from 50 client–therapist dyads). Physiological synchrony in electrodermal activity was indexed using two cross-correlation functions per session: once for client leading and again for therapist leading (in both cases, with lags up to 10 s). The clients’ and therapists’ in-session emotions were assessed with the Profile of Mood States. Actor–partner interdependence models showed that certain client (but not therapist) in-session emotions, namely higher contentment and lower anxiety and depression, were tied to therapist-led (but not client-led) physiological synchrony. The results suggest that therapist-led synchrony (i.e., clients’ arousal tracking therapists’ earlier arousal) is tied to more positive and less negative emotional experiences for clients.

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Vergé-Dépré, G., M. Legrand, C. Moulin, A. Alias, and P. François. "Improvement of the detection of desert dust over the Sahel using METEOSAT IR imagery." Annales Geophysicae 24, no. 8 (September 13, 2006): 2065–73. http://dx.doi.org/10.5194/angeo-24-2065-2006.

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Abstract. Desert dust over the arid regions of Africa is detected using the Infrared Difference Dust Index (IDDI) derived from the thermal infrared (TIR) channel of METEOSAT. However, the comparison with photometric aerosol optical thickness (AOT) of this dust index reveals some discrepancies. Using an instrumented site in Sahel where aerosol properties and meteorological conditions were monitored daily during the dry season, we performed radiative transfer computations with the MODTRAN 4.1 code to develop a method to improve the IDDI usefulness. We found that discrepancies between AOT and IDDI variations mostly come from changes in the surface temperature (Ts), which is an important parameter for radiative transfer computations in the TIR. We show that this temperature varies from day to day with the surface wind speed and during the course of the season with the solar elevation, and that it is possible, for the site considered, to correct Ts from these combined effect using a simple parameterization. We also observe that the dust layer itself has an impact on Ts by reducing the amount of solar radiation at the surface, and that this phenomenon can also be accounted for by adding an AOT-dependence to the above parameterization of Ts. We show that this parameterization allows improving the agreement between the IDDI and the photometric AOT.

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Elkins, Harold A. "Comments on “Use of Enhanced IR/Visible Satellite Imagery to Determine Heavy Snow Areas”." Monthly Weather Review 117, no. 1 (January 1989): 251–53. http://dx.doi.org/10.1175/1520-0493(1989)117<0251:cooeis>2.0.co;2.

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Grassi, D., A. Adriani, M. L. Moriconi, N. I. Ignatiev, E. D'Aversa, F. Colosimo, A. Negrão, et al. "Jupiter’s hot spots: Quantitative assessment of the retrieval capabilities of future IR spectro-imagers." Planetary and Space Science 58, no. 10 (August 2010): 1265–78. http://dx.doi.org/10.1016/j.pss.2010.05.003.

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Wani, Shahi, and Fasel Qadir. "Cellular Automata Based Study of Spectral Signatures of Dal_Lake Infrared Imagery." Oriental journal of computer science and technology 10, no. 2 (May 18, 2017): 276–81. http://dx.doi.org/10.13005/ojcst/10.02.04.

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Among all the water bodies in Jammu & Kashmir Dal Lake has a peculiar significance due to its location in the heart of the capital city Srinagar. Historical studies over last fifteen hundred years indicate a continuous squeezing of the Lake due to different natural and manmade interventions. Over this long period, the governance of the land has passed through various wise and ugly human plans besides some slow natural processes. The mathematical modelling of such a dynamics is not an easy task because of the many intervening variables and the difficulty which implies their measurements. On the other hand, during the last decades, the use of Cellular Automata (CA) techniques to simulate the behaviour of linear or non-linear systems is becoming of great interest. This fact is mainly due to the fact that this approach depends largely on local relations and a series of rules instead of precise mathematical formulae. The infrared (IR) satellite imagery can be helpful in identifying the different areas of interest using CA as a tool of image processing. The study will not only separate the areas of interest but also pave a way towards a comprehensive study of all the identified zones using spectral signatures received from the continuous IR imagery of both pre-monsoon and post-monsoon periods in future.

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Gai, M., D. F. Buscher, L. Corcione, S. Ligori, and J. S. Young. "Fringe Tracker for the VLTI Spectro-Imager." Proceedings of the International Astronomical Union 3, S248 (October 2007): 106–7. http://dx.doi.org/10.1017/s1743921308018759.

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AbstractInterferometry in the near IR aims at providing imaging resolution on the mas scale, and astrometry at the few μas level, from ground based infrastructures using current telescope technology. To take advantage of simultaneous combination of four to eight telescopes, an international consortium is proposing to ESO the development of the VLTI Spectro-Imager. One of the key sub-systems, to measure and correct the atmospheric perturbations relative to the beam phase, is the fringe tracker, aimed at providing the science combiner with long, stable observing conditions. The fringe tracker function in interferometer is equivalent to adaptive optics for conventional telescopes. The fringe tracker concept under study, using minimum redundancy combination and bulk optics, is described.

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Blokhinov, Y. B., V. A. Gorbachev, Y. O. Rakutin, and D. A. Nikitin. "A REAL-TIME SEMANTIC SEGMENTATION ALGORITHM FOR AERIAL IMAGERY." Computer Optics 42, no. 1 (March 30, 2018): 141–48. http://dx.doi.org/10.18287/2412-6179-2018-42-1-141-148.

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We propose a novel effective algorithm for real-time semantic segmentation of images that has the best accuracy in its class. Based on a comparative analysis of preliminary segmentation methods, methods for calculating attributes from image segments, as well as various algorithms of machine learning, the most effective methods in terms of their accuracy and performance are identified. Based on the research results, a modular near real-time algorithm of semantic segmentation is constructed. Training and testing is performed on the ISPRS Vaihingen collection of aerial photos of the visible and IR ranges, to which a pixel map of the terrain heights is attached. An original method for obtaining a normalized nDSM for the original DSM is proposed.

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Suharyadi, R., Iswari Nur Hidayati, Made Dwiyana Surya Upadana, and Valentina Yulia Permatasari. "Improving the Traffic Management System Based on Remote Sensing Data Imagery." E3S Web of Conferences 468 (2023): 03006. http://dx.doi.org/10.1051/e3sconf/202346803006.

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Traffic management aims to increase or maintain the standard of transport services. The use of intelligent transport systems, such as traffic signals and variable message signs, can aid in the efficient management of traffic flow. Traffic management is a relatively inexpensive form of road management, but its impact is generally less studied. This study evaluated the level of road services (LOS) provided by Prof. Dr. Ir. Herman Yohanes Road based on the fusion of remote sensing data imagery and field surveys. The study found the LOS before the traffic management to be category E LOS, but it increased into category C after the traffic management. The increase heavily implied by the road capacity which shown the decrease of volume of vehicles from 3.030 to 993 and an increase of vehicle’s speed from 25 km/h to 40–60 km/h. Questionnaires were used to assess the effects of traffic management on road satisfaction and revenue changes among selected business along Prof. Dr. Ir. Herman Yohanes Road. The increase in LOS seems to also increase the road satisfaction due to less volume of vehicles and better travel speed. Despite the increase on both LOS and road satisfaction, annual revenue seemed to decrease for 20% on micro business, 50% on small business, 19,4% on medium business, and 40% on big business. The findings also include a detailed level of service road map indicating the differences of before and after the implementation of traffic management measures

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Oliver, Jacqueline A., Frédérique C. Pivot, Qing Tan, Alan S. Cantin, Martin J. Wooster, and Joshua M. Johnston. "A Machine Learning Approach to Waterbody Segmentation in Thermal Infrared Imagery in Support of Tactical Wildfire Mapping." Remote Sensing 14, no. 9 (May 8, 2022): 2262. http://dx.doi.org/10.3390/rs14092262.

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Wildfire research is working toward near real-time tactical wildfire mapping through the application of computer vision techniques to airborne thermal infrared (IR) imagery. One issue hindering automation is the potential for waterbodies to be marked as areas of combustion due to their relative warmth in nighttime thermal imagery. Segmentation and masking of waterbodies could help resolve this issue, but the reliance on data captured exclusively in the thermal IR and the presence of real areas of combustion in some of the images introduces unique challenges. This study explores the use of the random forest (RF) classifier for the segmentation of waterbodies in thermal IR images containing a heterogenous wildfire. Features for classification are generated through the application of contextual and textural filters, as well as normalization techniques. The classifier’s outputs are compared against static GIS-based data on waterbody extent as well as the outputs of two unsupervised segmentation techniques, based on entropy and variance, respectively. Our results show that the RF classifier achieves very high balanced accuracy (>98.6%) for thermal imagery with and without wildfire pixels, with an overall F1 score of 0.98. The RF method surpassed the accuracy of all others tested, even with heterogenous training sets as small as 20 images. In addition to assisting automation of wildfire mapping, the efficiency and accuracy of this approach to segmentation can facilitate the creation of larger training data sets, which are necessary for invoking more complex deep learning approaches.