Recent advances in visual and infrared face recognition—a review

Face recognition is a rapidly growing research area due to increasing demands for security in commercial and law enforcement applications. This paper provides an up-to-date review of research efforts in face recognition techniques based on two-dimensional (2D) images in the visual and infrared (IR) spectra. Face recognition systems based on visual images have reached a significant level of maturity with some practical success. However, the performance of visual face recognition may degrade under poor illumination conditions or for subjects of various skin colors. IR imagery represents a viable alternative to visible imaging in the search for a robust and practical identification system. While visual face recognition systems perform relatively reliably under controlled illumination conditions, thermal IR face recognition systems are advantageous when there is no control over illumination or for detecting disguised faces. Face recognition using 3D images is another active area of face recognition, which provides robust face recognition with changes in pose. Recent research has also demonstrated that the fusion of different imaging modalities and spectral components can improve the overall performance of face recognition.     

Discrimination between crude-oil spills and monomolecular sea slicks by airborne radar and infrared radiometer—possibilities and limitations

Abstract

The applicability of an X-band (9·4 GHz) real aperture radar (RAR) and an infrared (IR) radiometer to discriminate between crude-oil spills and monomolecular sea slicks is investigated over the same sea area. The results from quasi-simultaneous overflights over a crude-oil spill and three different sea slicks (oleyl alcohol, di-(ethylenglycol)-mono-isostearyletherand methyl oleate)show that the advantage of an imaging radar is its uniequi vocal potential for surveying large sea surfaces and that the advantage of an IR sensor is its ability to determinate quickly the thick centres of crude-oil spills. However, neither the RAR nor the IR radiometer can discriminate between crude-oil spills and sea slicks. Therefore, an airborne coastal patrol with the objective of monitoring oil pollution must comprise a package of additional sensors, e.g. a microwave radiometer and/or a lidar system.     

Fast over‐land atmospheric correction of visible and near‐infrared satellite images

A rapid atmospheric correction method is proposed to be used for visible and near‐infrared satellite sensor images over land. The method is based on a simplified use of a radiative transfer code (RTC), which is used only a priori, to generate Look‐Up‐Tables (LUTs) of the estimated surface reflectance. A typical scenario and ranges of values for the main atmospheric correction parameters are initially established. Each image pixel is treated as a slight deviation from the reference scenario defined by the vector of the typical values for the parameters. The assumption of the parameter's independence allows the use of one‐dimensional LUTs. The method is suitable for near real‐time processing or whenever a large number of data are to be handled rapidly. The operator intervention is minimal, and the computation time involved in the correction of a whole image is about 1000 times shorter than the full use of the base RTC. A test is performed with advanced very‐high‐resolution radiometer (AVHRR) visible and near‐infrared data, using the Second Simulation of the Satellite Signal in the Solar Spectrum (6S) RTC as the base code. The accuracy of the proposed method was compared with the standard use of the 6S RTC over the same dataset with resulting root mean square errors of 0.0114 and 0.0104 for AVHRR bands 1 and 2 for the estimated surface reflectance, respectively.     

The σ-IASI code for the calculation of infrared atmospheric radiance and its derivatives

This paper describes a new fast line-by-line radiative transfer scheme which computes top of the atmosphere spectral radiance and its Jacobians with respect to any set of geophysical parameters both for clear and cloudy sky, and presents the software which implements the procedure. The performance of the code has been evaluated with respect to accuracy and speediness through a comparison with a state-of-art line-by-line radiative transfer model. The new code is well suited for nadir viewing satellite and airplane infrared sensors with a sampling rate in the range 0.1–2 cm⁻¹.     

Visible?infrared and radar imagery fusion for geological application: A new approach using DEM and sun-illumination model

Radar-multispectral imagery fusion has been successfully used in several application fields. In this study, a new technique to merge an ERS-1 (Synthetic Aperture Radar precision image, SAR-PRI) image and a Landsat Thematic Mapper (TM ) image for the geological study of the western Aspromonte (southern Italy) was investigated. Spectral information provided by the TM image can be effectively combined with texture and pattern data from the radar imagery to produce a synergistic image. Landsat bands are normalized for shadowing effects using the semi-empirical Minnaert model and thereafter multiplied by the ERS1 image. The visible-infrared (VIR) and radar fused bands can be composed into colour images. This technique leads to the production of images in which the geologically relevant information were integrated. These images were compared with the imagery produced by the intensity-hue-saturation (IHS) transformation approach, commonly used for image fusion. The sun-illumination normalization method gives better results in image fusion, enhancing subtle spectral features. Compared to the individual images, the synergistic SAR-TM images produced by this technique improve the interpretation of lithology boundaries and recognition of structural features.     

Assimilating satellite imagery and visible–near infrared spectroscopy to model and map soil loss by water erosion in Australia

Soil loss causes environmental degradation and reduces agricultural productivity over large areas of the world. Here, we use the latest earth observation data and soil visible–near infrared (vis–NIR) spectroscopy to estimate the factors of the Revised Universal Soil Loss Equation (RUSLE) and to model soil loss by water erosion in Australia. We estimate rainfall erosivity (R) using the Tropical Rainfall Measuring Mission (TRMM); slope length and steepness (L and S) using a 3-arcsec Shuttle Radar Topography Mission (SRTM) digital elevation model; cover management (C) and control practice (P) using the national dynamic land cover dataset (DLCD) of Australia derived from the moderate-resolution imaging spectroradiometer (MODIS); and soil erodibility (K) using vis–NIR estimates of the contents of sand, silt, clay and organic carbon in Australian soil. We model K using a machine-learning algorithm with environmental predictors selected to best capture the factors that influence erodibility and produced a digital map of K. We use the derived RUSLE factors to estimate soil loss at 1-km resolution across the whole of Australia. We found that the potential gross average soil loss by water erosion in Australian is 1.86 t ha⁻¹ y⁻¹ (95% confidence intervals of 1.78 and 1.93 t ha⁻¹ y⁻¹), equivalent to a total of 1242 × 10⁶ tonnes of soil lost annually (95% confidence intervals of 1195 and 1293 t × 10⁶ y⁻¹). Our estimates of erosion are generally smaller than previous continental estimates using the RUSLE, but particularly in croplands, which might indicate that soil conservation practices effectively reduced erosion in Australia. However we also identify localized regions with large erosion in northern Australia and northeastern Queensland. Erosion in these areas carries sediments laden with nitrogen, phosphorus and pollutants from agricultural production into the sea, negatively affecting marine ecosystems. We used the best available data and our results provide better estimates compared to previous assessments. Our approach will be valuable for other large, sparsely sampled areas of the world where assessments of soil erosion are needed.     

A method for cross‐calibrating geostationary and polar orbiting satellite sensors in the infrared windows

The forward radiative transfer routine has been used to remove the artefact caused by modulation on meteorological satellite‐sensor responses. This paper describes a direct method where images observed by the infrared channels aboard the Multi‐functional Transport Satellite (MTSAT‐1R) and Fengyun‐2C (FY‐2C) geostationary satellites are compared with those by the Advanced Very High Resolution Radiometer (AVHRR) sensor aboard the National Oceanic and Atmospheric Administration (NOAA) polar‐orbiting satellites. The calibration differences between the polar orbiting and the geostationary satellites are found to be within 1 K of each other.     

Thermal–infrared emissivities of natural surfaces: improvements on the experimental set-up and new measurements

Ground measurements of thermal infrared emissivities of terrestrial surfaces are required to derive accurate temperatures from radiometric measurements, and also to apply and validate emissivity models using satellite sensor observations. This paper focuses on the demanding aspects that are involved in the field measurement of emissivity using the box method and a hand-held radiometer. Measuring emissivities in field conditions can be hampered by external factors such as wind and solar irradiance. This can increase the time spent on the field campaign but, most importantly, it can cause no-sense fluctuations between consecutive observations. Here we propose original developments for the experimental instrumentation to ensure consistency of measurements. Moreover, we present a dataset of emissivity values for different soils, rocks and vegetation samples measured in the 8–14, 8.2–9.2, 10.5–1 1.5 and 11.5–12.5 µm wavebands.     

Identifying plant species using mid-wave infrared (2.5–6 μm) and thermal infrared (8–14 μm) emissivity spectra

Plant species discrimination using remote sensing is generally limited by the similarity of their reflectance spectra in the visible, NIR and SWIR domains. Laboratory measured emissivity spectra in the mid infrared (MIR; 2.5 μm–6 μm) and the thermal infrared (TIR; 8 μm–14 μm) domain of different plant species, however, reveal significant differences. It is anticipated that with the advances in airborne and space borne hyperspectral thermal sensors, differentiation between plant species may improve. The laboratory emissivity spectra of thirteen common broad leaved species, comprising 3024 spectral bands in the MIR and TIR, were analyzed. For each wavelength the differences between the species were tested for significance using the one way analysis of variance (ANOVA) with the post-hoc Tukey HSD test. The emissivity spectra of the analyzed species were found to be statistically different at various wavebands. Subsequently, six spectral bands were selected (based on the histogram of separable pairs of species for each waveband) to quantify the separability between each species pair based on the Jefferies Matusita (JM) distance. Out of 78 combinations, 76 pairs had a significantly different JM distance. This means that careful selection of hyperspectral bands in the MIR and TIR (2.5 μm–14 μm) results in reliable species discrimination.     

Simultaneous non‐linear retrieval of atmospheric profiles and surface skin temperature from MODIS infrared radiances in Taiwan Strait

A non‐linear iterative physical algorithm that simultaneously retrieves atmospheric temperature, water vapour distribution and surface skin temperature from Moderate Resolution Imaging Spectroradiometer (MODIS) longwave infrared radiances is presented. The retrieval algorithm uses clear‐sky radiances measured by MODIS in Taiwan Strait for both day and night, and shows that it is capable of retrieving medium‐scale atmospheric temperature and water vapour. Sea surface temperature is retrieved with an accuracy similar to that achieved by MOD07 products. Evaluation of retrieval total precipitable water vapour (TPW) is performed by comparisons with retrievals from MOD07 products and data from a ground‐based sunphotometer. These show that MODIS retrieval of TPW, in general, agrees with other sounder retrievals of TPW. The total totals index (TTI) distribution retrieved from MODIS data is similar to that from MOD07 products.     

Feasibility of estimating leaf water content using spectral indices from WorldView-3’s near-infrared and shortwave infrared bands

A recently-launched high-resolution commercial satellite, DigitalGlobe’s WorldView-3, has 8 bands in the shortwave infrared (SWIR) wavelength region, which may be capable of estimating canopy water content at 3.7-m spatial resolution. WorldView-3 also has 8 multispectral bands at 1.24-m resolution with two bands in the near-infrared (NIR). The relative spectral response functions for WorldView-3 were provided by DigitalGlobe, Inc., and band reflectances were determined for reflectance spectra of PROSPECT model simulations and leaf data from maize, trees, grasses, and broadleaf herbaceous eudicots. For laboratory measurements, the range of leaf water contents was extended by including drying leaves and leaf stacks of corn, soybean, oaks, and maples. Correlations between leaf water content and spectral indices from model simulations suggested that indices using SWIR band 1 (center wavelength 1210 nm) had low variability with respect to leaf water content, but also low sensitivity. Other indices using SWIR band 5 (2165 nm) had the highest sensitivity, but also had high variability caused by different values of the leaf structure parameter in PROSPECT. Indices using SWIR bands 2, 3 and 4 (1570, 1660, and 1730 nm, respectively) had high correlations and intermediate variability from the leaf structure parameter. Spectral indices calculated from the leaf data had the same overall patterns as the simulations for variation and sensitivity; however, indices using SWIR band 1 had low correlations, and the best correlations were from indices that used SWIR bands 2, 3 and 4. Spectral indices for maize, grasses, and herbaceous crops and weeds had similar responses to leaf water content; tree leaves had higher index values and saturated at lower leaf water contents. The specified width of NIR band 2 (860–1040 nm) overlaps the water absorption feature at 970 nm wavelength; however, the normalized difference of NIR band 1 and 2 was insensitive to water content because NIR band 2’s spectral response was most heavily weighted to wavelengths less than 930 nm. The high spatial resolution of the WorldView-3 SWIR data will help analyze how variation among plant species and functional groups affects spectral responses to differences in canopy water content.     

Near‐infrared discrimination of leafless saltcedar in wintertime Landsat TM

To test a hypothesis that leafless riparian canopies enable accurate multi‐spectral discrimination of saltcedar (Tamarix ramosissima Ledeb.) from other native species, winter Landsat TM5 data (16 November 2005) were analysed for a reach of the Arkansas River in Colorado, USA. Supporting spectroscopic analysis confirmed that saltcedar could not easily be discriminated from other riparian vegetation using TM5 data when in‐leaf, but bare branches could be easily distinguished due to much lower reflectance than other riparian cover. Use of TM Band 4 (B4) allowed differentiation of wintertime saltcedar into four qualitative density classes judged from high‐resolution low‐oblique aerial photography: high (76%–100%), medium (51%–75%), low (16%–50%), and none (0%–15%). Spectral overlap was removed from the B4 saltcedar classification using TM Band 5 (B5) thresholds to eliminate low‐reflectant wet areas and higher‐reflectant multi‐year darkened weed canopies. The accuracy of a classification algorithm that used B5 thresholds followed by a B4 density slice was judged against high‐resolution aerial photography as providing 98% discrimination of saltcedar cover from other riparian cover and about 90% discrimination of the qualitative density classes. Applying this method to the 2835 km² riparian corridor study area, 1298 km² (45.78%) was identified as containing saltcedar, with over 43% having medium or greater density.     

The assessment of leaf water content using leaf reflectance ratios in the visible,near‐, and short‐wave‐infrared

The common features of spectral reflectance from vegetation foliage upon leaf dehydration are decreasing water absorption troughs in the near‐infrared (NIR) and short‐wave‐infrared (SWIR). We studied which leaf water index in the NIR and SWIR is most suitable for the assessment of leaf water content and the detection of leaf dehydration from the laboratory standpoint. We also examined the influence of the thickness of leaves upon leaf water indices. All leaf water content indices examined exhibited basic correlations with the relative water content (RWC) of leaves, while the R ₁₃₀₀/R ₁₄₅₀ leaf water index also demonstrated a high signal strength and low variability (R ²>0.94). All examined leaf reflectance ratios could also be correlated with leaf thickness. The thickness of leaves, however, was not independent of leaf RWC but appeared to decrease substantially as a result of leaf dehydration.     

Simulation of lazer light propagation and thermal processes in red blood cells exposed to infrared laser tweezers (λ = 1064 nm)

Continuous-wave laser micro-beams are generally used as diagnostic tools in laser scanning microscopes or, in the case of near-infrared micro-beams, as optical traps for cell manipulation and force characterization. Because single beam traps are created with objectives of high numerical aperture, typical trapping intensities and photon flux densities are in the order of 10⁶ W/cm² and 10³ cm⁻² s⁻¹, respectively. These extremely high fields may induce two-photon absorption processes and anomalous biological effects. We studied effects occurring in red blood cells (RBCs) radiated by near-infrared laser tweezers λ = 1064 nm). The main idea of our study was to investigate the thermal reaction of RBCs irradiated by laser micro-beam. It is supported by the fact that many experiments have been carried out on RBCs using laser near infrared tweezers. Usually they are relatively long lasting and the thermal aspects of such experiments are not examined. In the present work it has been identified that the laser affects a RBC with a density of absorbed energy at approximately 10⁷ J/cm³, which causes a temperature rise in the cell of about 10–15°C.     

Identification of plant species by using high spatial and spectral resolution thermal infrared (8.0-13.5 μm) imagery

High spatial and spectral resolution thermal infrared imagery (8.0-13.5 μm) from the SEBASS airborne sensor was used to analyze and map tree canopy spectral features at the State Arboretum of Virginia, near Boyce, Virginia. Fifty tree species were analyzed and about half were directly identified with varying degrees of success on the basis of spectral matched filtering that utilized laboratory-measured leaf spectra as the target signatures. Spectral averages of pixels extracted from SEBASS emissivity data compared favorably with laboratory spectra of leaves collected from individual tree species. Best results were obtained from species having relatively strong spectral contrast, wide and flat leaves, closed planophile canopies, and/or large canopy areas. Tree species having small leaves or unfavorable leaf orientations showed spectral attenuation likely resulting from cavity blackbody effects. Increased spatial resolution and better image calibration and atmospheric correction might lead to further improvements in thermal infrared plant species identification.     

Water turbidity estimation using a hand‐held spectropolarimeter to determine surface reflection polarization in visible,near and short‐wave infrared bands

This letter describes a radiometric technique to evaluate the turbidity (suspended solids concentration, SSC) of terrestrial waters (e.g. irrigation canals, creeks, ponds, streams and small rivers) using a hand‐held spectropolarimeter. A field experiment was conducted using a container of water with different turbidity levels. The intensity and degree of polarization of sunlight reflected from the water were measured in visible, near and short‐wave infrared bands. The intensity of the reflected light and its non‐polarized component were divided by the incident sunlight intensity to derive the radiant coefficient (Q, %), and the non‐polarized radiant coefficient (Qnp, %), respectively. The Q and Qnp in several wavelength bands were regressed against measured values of SSC. The multiple regression model using multi‐band Qnp is superior to a similar model using multi‐band Q because the Qnp model does not need viewing angles as explanatory variables, whereas the model using Q requires these angles. A result from preliminary testing in real streams is also presented.     

Does single broadband or multispectral thermal data add information for classification of visible,near‐ and shortwave infrared imagery of urban areas?

The potential value of combining broadband and multispectral thermal infrared (TIR) data with multispectral and hyperspectral visible, near‐infrared (VNIR) and shortwave infrared (SWIR) data was investigated within the context of urban land‐cover classification. Using a case study of airborne Digital Airborne Imaging Spectrometer (DAIS) imagery of Strasbourg, France, the relative contribution of TIR wavelengths to classification accuracy was investigated for hyperspectral and simulated multispectral IKONOS, SPOT and Landsat Thematic Mapper (TM) bands. A support vector machines (SVM) classifier was used because this method was found to be very effective at handling the complex distributions of the heterogeneous land cover classes. The overall classification accuracy varied greatly with different band combinations. The inclusion of a single broad thermal band increased classification accuracy by as much as 20% for simulated IKONOS bands, but only 4% for hyperspectral VNIR and SWIR data. Adding multispectral TIR data raised the average accuracy approximately a further 10% for each band combination studied. Thermal wavelengths were found to be particularly useful for reducing the confusion between road and roof surfaces.     

Spectral variability and bidirectional reflectance behaviour of urban materials at a 20 cm spatial resolution in the visible and near‐infrared wavelengths. A case study over Toulouse (France)

This letter presents an experiment carried out in Toulouse in May 2004 to study the spectral variability and bidirectional reflectance behaviour of urban materials. The measurements were carried out at a 20 cm spatial resolution in the visible and near‐infrared (350–2500 nm). These measurements allow quantification of three main types of reflectance spatial variability. In addition to these in situ experiments, the bidirectional properties of urban material samples were studied in the laboratory with a goniometer.     

Validating three infrared‐based rainfall retrieval algorithms for intense convective activity over Greece

Three different rainfall estimation techniques based on infrared data from Meteosat, the Arkin technique (ARKT), the Negri‐Adler‐Wetzel technique (NAWT) and the Convective‐Stratiform technique (CST), were applied to four convective systems over Greece to test their performance in case of flood episodes of varying intensities and to examine the possibility of their optimization for this particular geographical region. The comparison between satellite‐derived estimates and the corresponding 12‐hourly accumulated precipitation data from ground stations proved that all three techniques have the common characteristic of overestimating the precipitation in Greece. In general, the CST method was found to best represent the rainfall pattern observed in the rain gauge network, when the comparison is made on a single station basis. On the contrary, the overall performances of ARKT and NAWT methods were not satisfactory. Moreover, a sensitivity analysis of the ARKT and NAWT method to their different parameters indicated that the main parameter for improving their overall performance is the threshold temperature whereas the adjustment of the assigned rain rates has little influence on results. In general, the optimized NAWT technique may provide a very good representation of convective rainfall in the particular geoclimatic conditions of Greece, especially if the estimated values are averaged over suitable space‐time intervals.     

Cross‐calibration of MSG1‐SEVIRI infrared channels with Terra‐MODIS channels

This paper addresses the cross‐calibration of the infrared channels 4 (3.9 µm), 9 (10.8 µm) and 10 (12.0 µm) of the Spinning Enhanced Visible and Infra‐Red Imager (SEVIRI) onboard the Meteosat Second Generation 1 (MSG1) satellite with the channels of the MODerate resolution Imaging Spectroradiometer (MODIS) onboard Terra. The cross‐calibrations, including the Ray‐Matching (RM) method and the Radiative Transfer Modelling (RTM) method, were developed and implemented over a tropical area using SEVIRI and MODIS measurements of July 2005 and July 2006 with absolute view zenith angle differences (|ΔVZA|)<0.5°, absolute view azimuth angle differences (|ΔVAA|)<0.5° and absolute time differences (|ΔTime|)<10 min. The results obtained by the RM and RTM methods revealed calibration discrepancies between the two sensors. The results obtained by the RM method were consistent with previously published results. The results obtained by the RTM method were consistent with the results obtained by the RM method if the temperature differences caused by the spectral differences between the two sensors were taken into account. From the cross‐calibration results obtained by the two methods, the use of the results obtained by the RTM method to recalibrate the SEVIRI data is recommended. The recalibrations remove the overestimation of the Land Surface Temperature (LST) retrieved from the SEVIRI data by a split‐window method.