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We propose a single-camera multispectral Short Wave Infrared (SWIR) plenoptic imaging system free of fixed pattern noise (FPN). The developed system can form, for each scene’s object of interest, an in-focus noiseless 24 channels SWIR multispectral data cube. The Fourier Slice Photography Theorem is employed in the integrated multispectral light field to achieve images at a specific scene depth of focus. And, a reference-free image quality index is used for selecting the in-focus image for each scene object focal plane. Results are then compared to SWIR multispectral data cubes obtained from light fields achieved after applying to the SWIR camera a blackbody two-point calibration method. The scientific potential of the imaging system is proved by imaging thermal stressed plants at different scene depths of focus. The FPN SWIR spectral dependence is evaluated on the images digitally refocused at the farthest scene focal plane, resulting in concordance with the InGaAs FPA quantum efficiency. The lightfield (LF) system performance to naturally filter out the FPN was evaluated with a Black body (BB) reference base index, resulting in an SSIM index close to 98 % at the object image focus plane.

This paper proposes crowd estimation technology to help authorities make the right decisions in times of crisis. Specifically, deep learning models have faced these challenges, achieving excellent results. In particular, the trend of using single-column Fully Convolutional Networks (FCNs) has increased in recent years. A typical architecture that meets these characteristics is the autoencoder. However, this model presents an intrinsic difficulty: the search for the optimal dimensionality of the latent space. In order to alleviate such difficulty, we propose a dual architecture consisting of two cascaded autoencoders. The first autoencoder is responsible for carrying out the masked reconstruction of the original images, whereas the second obtains crowd maps from the outputs of the first one. In this way, our architecture improves the location of people and crowds in Focal Inverse Distance Transform (FIDT) maps, resulting in more accurate count estimates than estimates obtained through a single autoencoder architecture.

A reference-free image index to jointly assess infrared-imaging fixed-pattern-noise and blur artifacts is proposed in this work. The proposed index is based on tuned-spatial-domain filtering, which works by combining two Laplace operators to simultaneously quantify the global infrared-imaging fixed-pattern-noise and the global or local blur artifacts. The index effectiveness is demonstrated by two task-based image-quality assessments to determine the focused and fixed-pattern-noise free images from sequences captured with both a mid-wave-infrared microscope system and a long-wave-infrared plenoptic system. The index quantitative limits are shown on numerical computations over synthetic corrupted images as well as real black-body radiator calibrated infrared images with representative simulated fixed-pattern noise, from six well known infrared focal plane arrays transducer technologies, along with artificial blur added using real infrared imaging system point spread functions.

Infrared (IR) imaging systems are known to have a range of sensor and optical limitations that result in degraded imagery. Fixed pattern noise (FPN), resulting from pixel-to-pixel response nonuniformity, is a dominant source of error that manifests in collected imagery through the appearance of temporally and spatially correlated noise patterns that are mixed with each image. Furthermore, finite detector size coupled with imperfect system optics can introduce blurring effects and aliasing, ultimately reducing resolution in acquired images. Here, we propose a unified method to reduce FPN and recover high-frequency image content in IR microscopy images. The proposed method uses regularized nonlocal means to highlight spatial features in the scene while maintaining fine textural image details. We derive an iterative optimization method based upon a gradient descent minimization strategy that applies a Wiener deconvolution in each iteration to estimate the blur artifacts. The method is implemented within an embedded mid-wave IR imaging system for microscopy applications. We demonstrate a reduction in FPN and blurring artifacts, achieving improved image resolution in the reconstructed images that are apparent in recovered details on scene objects.

In this paper, we present the mid-wave infrared microscopic view of index finger pads of voluntary subjects, an analysis of their thermoregulation response, and a study of their thermal spatial morphology. This is accomplished by means of a custom-made mid-wave infrared imager fitted with appropriate infrared optics. The microscopic thermal images enable us to capture spatial and temporal thermal information emitted from the microscopic finger pad's blood vessels and irrigation system, spatially attenuated by the finger pad's skin morphology. As a consequence, we can acquire and extract features that visual-spectrum microscopes or regular infrared imagers are not able to disclose. The thermoregulation response is acquired by exposing to a thermal stress the finger pads of voluntary subjects, while a microscopic infrared sequence was recorded. We used standard infrared imaging and signal processing techniques to extract the thermoregulation curves of the infrared sequences, and the thermal morphology features were estimated from the same imagery. One of the key findings of this paper is that three distinctive index finger pads infrared morphology patterns were identified, and important insights of the thermal behavior of the micro-spatial finger pad anatomy were observed for the very first time.

In this paper, two novel multidimensional striping noise compensation (SNC) algorithms for push-broom hyperspectral cameras (PBHCs) have been developed. The SNC algorithms employ a novel pixelwise, affine image-degradation model, which assumes that the striping noise (SN) parameters are spatially uncorrelated, spectrally independent, and decoupled from the camera’s spectral response. Algorithms simultaneously exploit the spatial and temporal information contained in an image as well as the spectral information contained at adjacent spectral images. The multidimensional SNC algorithms were successfully tested on real hyperspectral data from both a commercial PBHC operating in the spectral range of 400–1000 nm, at a resolution of 1.04 nm, and the ESA earth-observing CHRIS/PROBA sensor. [ABSTRACT FROM PUBLISHER]

In this paper, a detailed comparative performance analysis of the two-color satellite laser ranging (SLR) systems of the Transportable Integrated Geodetic Observatory (TIGO) is presented. The study is based on four years of continuous measurement data and a comparison of two different layouts of the laser system. The focus lies on a quantitative analysis of measurement precision, range accuracy, and data production for the two laser system layouts. Main findings include a significant gain in temporal stability due to removal of active elements in the oscillator, an improvement of range measurement accuracy by a factor of 2, and an important increase in data productivity. The analysis presented here provides a valuable input for the design of future SLR systems, as well as related topics such as time transfer applications and optical communications to satellites. [ABSTRACT FROM PUBLISHER]

A rigorous model is developed for determining single-photon quantum efficiency (SPQE) of single-photon avalanche photodiodes (SPADs) with simple or heterojunction multiplication regions. The analysis assumes nanosecond gated-mode operation of the SPADs and that band-to-band tunneling of carriers is the dominant source of dark current in the multiplication region. The model is then utilized to optimize the SPQE as a function of the applied voltage, for a given operating temperature and multiplication-region structure and material. The model can be applied to SPADs with In0.52Al0.48As or InP multiplication regions as well as In0.52Al0.48As-InP heterojunction multiplication regions for wavelengths of 1.3 and 1.55 µm. The predictions show that the SPQE generally decreases with decreasing the multiplication-region thickness. Moreover, an InP multiplication region requires a lower breakdown electric field (and, hence, offers a higher SPQE) than that required by an In0.52Al0.48As layer of the same width. The model also shows that the fractional width of the In0.52Al0.48As layer in an In0.52Al0.48As-InP heterojunction multiplication region can be optimized to attain a maximum SPQE that is greater than that offered by an InP multiplication region. This effect becomes more pronounced in thin multiplication regions as a result of the increased significance of dead space. [ABSTRACT FROM AUTHOR]