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J. Imaging, Volume 2, Issue 2 (June 2016) – 11 articles

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4443 KiB  
Article
Detection by Infrared Thermography of the Effect of Local Cryotherapy Exposure on Thermal Spreadin Skin
by Matthieu Vellard and Ahlem Arfaoui
J. Imaging 2016, 2(2), 20; https://doi.org/10.3390/jimaging2020020 - 13 Jun 2016
Cited by 5 | Viewed by 5190
Abstract
The aim of the study is to evaluate the impact of the exposure duration of local cryotherapy on the skin temperature of the thigh and of the knee. Ten subjects performed a low-intensity exercise, rested for 20 min without ice, and then rested [...] Read more.
The aim of the study is to evaluate the impact of the exposure duration of local cryotherapy on the skin temperature of the thigh and of the knee. Ten subjects performed a low-intensity exercise, rested for 20 min without ice, and then rested for 5 min and 10 min with ice under the right knee. The skin temperatures were measured by infrared thermography to assess the thermal spread. The results of the statistical analysis reveal an increase of skin temperature of the knee after an exposure of 5 min to the cryotherapy (p < 0.05). There are also differences inthermal regulation between the 10-min exposure and the absence of ice pack. The exposure time variation of local cryotherapy gives different physiological responses which vary in intensity and in location. Full article
(This article belongs to the Special Issue The World in Infrared Imaging)
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1625 KiB  
Article
Optimized Distributed Hyperparameter Search and Simulation for Lung Texture Classification in CT Using Hadoop
by Roger Schaer, Henning Müller and Adrien Depeursinge
J. Imaging 2016, 2(2), 19; https://doi.org/10.3390/jimaging2020019 - 07 Jun 2016
Cited by 12 | Viewed by 6483
Abstract
Many medical image analysis tasks require complex learning strategies to reach a quality of image-based decision support that is sufficient in clinical practice. The analysis of medical texture in tomographic images, for example of lung tissue, is no exception. Via a learning framework, [...] Read more.
Many medical image analysis tasks require complex learning strategies to reach a quality of image-based decision support that is sufficient in clinical practice. The analysis of medical texture in tomographic images, for example of lung tissue, is no exception. Via a learning framework, very good classification accuracy can be obtained, but several parameters need to be optimized. This article describes a practical framework for efficient distributed parameter optimization. The proposed solutions are applicable for many research groups with heterogeneous computing infrastructures and for various machine learning algorithms. These infrastructures can easily be connected via distributed computation frameworks. We use the Hadoop framework to run and distribute both grid and random search strategies for hyperparameter optimization and cross-validations on a cluster of 21 nodes composed of desktop computers and servers. We show that significant speedups of up to 364× compared to a serial execution can be achieved using our in-house Hadoop cluster by distributing the computation and automatically pruning the search space while still identifying the best-performing parameter combinations. To the best of our knowledge, this is the first article presenting practical results in detail for complex data analysis tasks on such a heterogeneous infrastructure together with a linked simulation framework that allows for computing resource planning. The results are directly applicable in many scenarios and allow implementing an efficient and effective strategy for medical (image) data analysis and related learning approaches. Full article
(This article belongs to the Special Issue Image and Video Processing in Medicine)
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12935 KiB  
Article
Microwave Imaging Radiometers by Aperture Synthesis Performance Simulator (Part 2): Instrument Modeling, Calibration, and Image Reconstruction Algorithms
by Adriano Camps, Hyuk Park, Yujin Kang, Jorge Bandeiras, Jose Barbosa, Paula Vieira, Ana Friaças and Salvatore D’Addio
J. Imaging 2016, 2(2), 18; https://doi.org/10.3390/jimaging2020018 - 12 May 2016
Cited by 7 | Viewed by 6943
Abstract
The Synthetic Aperture Interferometric Radiometer Performance Simulator (SAIRPS) has been a three-year project sponsored by the European Space Agency (ESA) to develop a completely generic end-to-end performance simulator of arbitrary synthetic aperture interferometric radiometers. In a companion manuscript (Part I), the Radiative Transfer [...] Read more.
The Synthetic Aperture Interferometric Radiometer Performance Simulator (SAIRPS) has been a three-year project sponsored by the European Space Agency (ESA) to develop a completely generic end-to-end performance simulator of arbitrary synthetic aperture interferometric radiometers. In a companion manuscript (Part I), the Radiative Transfer Module used to generate synthetic fully polarimetric brightness temperatures from 1 to 100 GHz, including land and ocean covers, as well as the atmosphere, is described in detail. In this manuscript (Part II), the instrument model, the calibration procedure, and the imaging algorithms are described. The instrument model includes the simulation of the array topology in terms of the number of antenna elements, the time-dependent position and orientation, and the arbitrary receivers’ topology which can be modified from a very generic one by connecting and disconnecting subsystems. All the parameters can be, one by one, defined either by mathematical functions or by input data files, including the frequency and temperature dependence. Generic calibration algorithms including an external point source, the flat target transformation, and the two-level correlated noise injection are described. Finally, different image reconstruction algorithms suitable for arbitrary array topologies have also been implemented and tested. Simulation results have been validated and selected results are presented. Full article
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14981 KiB  
Article
Microwave Imaging Radiometers by Aperture Synthesis—Performance Simulator (Part 1): Radiative Transfer Module
by Adriano Camps, Hyuk Park, Jorge Bandeiras, Jose Barbosa, Ana Sousa, Salvatore D’Addio and Manuel Martin-Neira
J. Imaging 2016, 2(2), 17; https://doi.org/10.3390/jimaging2020017 - 11 May 2016
Cited by 11 | Viewed by 6457
Abstract
The Synthetic Aperture Interferometric Radiometer Performance Simulator (SAIRPS) is a three-year project sponsored by the European Space Agency (ESA) to develop a completely generic end-to-end performance simulator of arbitrary synthetic aperture interferometric radiometers. This means, on one side, a generic radiative transfer module [...] Read more.
The Synthetic Aperture Interferometric Radiometer Performance Simulator (SAIRPS) is a three-year project sponsored by the European Space Agency (ESA) to develop a completely generic end-to-end performance simulator of arbitrary synthetic aperture interferometric radiometers. This means, on one side, a generic radiative transfer module from 1 to 100 GHz, including land and ocean covers, as well as a fully 3D atmosphere and Faraday ionospheric rotation based on variable TEC. On the other hand, the instrument can have an arbitrary array topology (number of antenna elements, and their time-dependent position and orientation). Receivers’ topology can also be modified, starting from a very generic one to connecting and disconnecting subsystems, whose parameters can be individually configured. These parameters can be defined either by mathematical functions or by input data files, including the frequency and temperature dependence. Generic calibration and image reconstruction algorithms that are suitable for arbitrary array topologies have also been implemented, as well as tools to compute the instrument performance metrics, i.e., radiometric accuracy, sensitivity, angular resolution, etc. This manuscript presents the generic architecture of the SAIRPS, the algorithms implemented in the Radiative Transfer Module, and simulation results showing its performance. A companion manuscript (Part II) describes the instrument and calibration modelling, the image reconstruction algorithms, and the validation tests that were performed. Full article
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12034 KiB  
Communication
A Foveon Sensor/Green-Pass Filter Technique for Direct Exposure of Traditional False Color Images
by Livio Fent and Al Meldrum
J. Imaging 2016, 2(2), 14; https://doi.org/10.3390/jimaging2020014 - 10 May 2016
Cited by 6 | Viewed by 11263
Abstract
A direct exposure technique to simulate the vegetation red-magenta hues associated with the traditional Kodak Ektachrome Professional Infrared EIR film is proposed. The method uses the Foveon sensor in full spectrum mode as found in Sigma cameras in combination with green-pass filters to [...] Read more.
A direct exposure technique to simulate the vegetation red-magenta hues associated with the traditional Kodak Ektachrome Professional Infrared EIR film is proposed. The method uses the Foveon sensor in full spectrum mode as found in Sigma cameras in combination with green-pass filters to reproduce the red-magenta hues of healthy vegetation without resorting to multi-exposures or channel swaps as is the current norm in single sensor cameras. An array of commercially available green-pass filters are analyzed via spectrophotmetric, densitometric and colorimetric measurements. A calibration technique using color-compensating filters is presented such that any green-pass filter will transmit green wavelengths to a set norm and ensure repeatability. A color model for the Foveon/green-pass filter is developed using quantum efficiencies to explain the color effects observed. Color similarities in near-infrared, blue and black and differences in red and green compared with Kodak Ektachrome Infrared film are discussed. Aerial photography examples are discussed, and the technique is proposed as a more direct means of obtaining traditional false color infrared imagery for pictorial and scientific applications when using Foveon type commercially available digital cameras. Full article
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2207 KiB  
Article
Wearable Structured Light System in Non-Rigid Configuration
by Carmen Paniagua, Gonzalo López-Nicolás and José Jesús Guerrero
J. Imaging 2016, 2(2), 16; https://doi.org/10.3390/jimaging2020016 - 09 May 2016
Cited by 1 | Viewed by 4744
Abstract
Traditionally, structured light methods have been studied in rigid configurations. In these configurations the position and orientation between the light emitter and the camera are fixed and known beforehand. In this paper we break with this rigidness and present a new structured light [...] Read more.
Traditionally, structured light methods have been studied in rigid configurations. In these configurations the position and orientation between the light emitter and the camera are fixed and known beforehand. In this paper we break with this rigidness and present a new structured light system in non-rigid configuration. This system is composed by a wearable standard perspective camera and a simple laser emitter. Our non-rigid configuration permits free motion of the light emitter with respect to the camera. The point-based pattern emitted by the laser permits us to easily establish correspondences between the image from the camera and a virtual one generated from the light emitter. Using these correspondences, our method computes rotation and translation up to scale of the planes of the scene where the point pattern is projected and reconstructs them. This constitutes a very useful tool for navigation applications in indoor environments, which are mainly composed of planar surfaces. Full article
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6052 KiB  
Article
Viewing Geometry Sensitivity of Commonly Used Vegetation Indices towards the Estimation of Biophysical Variables in Orchards
by Jonathan Van Beek, Laurent Tits, Ben Somers, Tom Deckers, Pieter Janssens and Pol Coppin
J. Imaging 2016, 2(2), 15; https://doi.org/10.3390/jimaging2020015 - 09 May 2016
Cited by 3 | Viewed by 6402
Abstract
Stress-related biophysical variables of capital intensive orchard crops can be estimated with proxies via spectral vegetation indices from off-nadir viewing satellite imagery. However, variable viewing compositions affect the relationship between spectral vegetation indices and stress-related variables (i.e., chlorophyll content, water content [...] Read more.
Stress-related biophysical variables of capital intensive orchard crops can be estimated with proxies via spectral vegetation indices from off-nadir viewing satellite imagery. However, variable viewing compositions affect the relationship between spectral vegetation indices and stress-related variables (i.e., chlorophyll content, water content and Leaf Area Index (LAI)) and could obstruct change detection. A sensitivity analysis was performed on the estimation of biophysical variables via vegetation indices for a wide range of viewing geometries. Subsequently, off-nadir viewing satellite imagery of an experimental orchard was analyzed, while all influences of background admixture were minimized through vegetation index normalization. Results indicated significant differences between nadir and off-nadir viewing scenes (∆R2 > 0.4). The Photochemical Reflectance Index (PRI), Normalized Difference Infrared Index (NDII) and Simple Ratio Pigment Index (SRPI) showed increased R2 values for off-nadir scenes taken perpendicular compared to parallel to row orientation. Other indices, such as Normalized Difference Vegetation Index (NDVI), Gitelson and Merzlyak (GM) and Structure Insensitive Pigment Index (SIPI), showed a significant decrease in R2 values from nadir to off-nadir viewing scenes. These results show the necessity of vegetation index selection for variable viewing applications to obtain an optimal derivation of biophysical variables in all circumstances. Full article
(This article belongs to the Special Issue Image Processing in Agriculture and Forestry)
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1079 KiB  
Review
The Herschel Heritage to Medical Thermography
by Francis Ring
J. Imaging 2016, 2(2), 13; https://doi.org/10.3390/jimaging2020013 - 14 Apr 2016
Cited by 7 | Viewed by 10215
Abstract
The discovery of infrared radiation by William Herschel in 1800 led to John Herschel’s study of solar radiation that he imaged by evaporography. This he termed a thermogram. The measurement of temperature in medicine advanced with Dr Carl Wunderlich, who showed the significance [...] Read more.
The discovery of infrared radiation by William Herschel in 1800 led to John Herschel’s study of solar radiation that he imaged by evaporography. This he termed a thermogram. The measurement of temperature in medicine advanced with Dr Carl Wunderlich, who showed the significance of the use of temperature measurements for diagnosis of fever and for monitoring the course of temperature in relation to disease. It was William and John Herschel’s discovery of infrared radiation that has ultimately opened up many applications for thermal imaging. Radiometric determination of human body (skin) temperature is now achievable. Remote sensing of infrared radiation first developed in the 1940s and has continued to develop steadily since 1960. Modern high speed and high resolution camera systems have now reached a dramatic level of performance at more modest costs, which medicine can now employ for non-invasive and quantifiable imaging. This has applications in many areas of medicine both for diagnostics and monitoring treatment. In recent years the acute threat of pandemic infection has increased, heightened by today’s ever expanding world travel. Special interest has been shown in the potential of thermal imaging for airport and travel screening. This is in effect where Dr Wunderlich’s studies began, and it has yet to be proven that the technique can be responsibly employed for efficient screening of large numbers of the travelling public. Full article
(This article belongs to the Special Issue The World in Infrared Imaging)
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5083 KiB  
Communication
Quality Control of Slot-Die Coated Aluminum Oxide Layers for Battery Applications Using Hyperspectral Imaging
by Florian Gruber, Philipp Wollmann, Benjamin Schumm, Wulf Grählert and Stefan Kaskel
J. Imaging 2016, 2(2), 12; https://doi.org/10.3390/jimaging2020012 - 07 Apr 2016
Cited by 11 | Viewed by 6229
Abstract
Hyperspectral inspection using imaging systems is becoming more and more important for quality control tasks in several industries, replacing well trained operators or established machine vision systems based on RGB-systems. Hyperspectral imaging (HSI) on thin coated substrates is challenging due to the high [...] Read more.
Hyperspectral inspection using imaging systems is becoming more and more important for quality control tasks in several industries, replacing well trained operators or established machine vision systems based on RGB-systems. Hyperspectral imaging (HSI) on thin coated substrates is challenging due to the high reflectivity of the substrates. Nevertheless, the thin films contribute to the spectral data and can be evaluated. Therefore, the performance of inspection systems can be increased significantly. However, the large amount of data generated by HSI has to be processed and evaluated for quality information about the product. In this paper, thin aluminum oxide (Al2O3) layers on stainless steel foil are investigated by HSI. These substrates can be used for the growth of vertically aligned carbon nanotubes (VA-SWCNT) for battery electrodes. HSI and spectral ellipsometry in combination with Partial Least Squares regression (PLS) was used to estimate the thickness of the Al2O3 layers and to calculate quality parameters for a possible monitoring process. The PLS model shows a R2CV of 0.979 and a RMSECV of 3.6. Full article
(This article belongs to the Special Issue Soft Computing in Image Processing)
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9127 KiB  
Review
Review of Active IR Thermography for Detection and Characterization of Defects in Reinforced Concrete
by Bojan Milovanović and Ivana Banjad Pečur
J. Imaging 2016, 2(2), 11; https://doi.org/10.3390/jimaging2020011 - 07 Apr 2016
Cited by 78 | Viewed by 14677
Abstract
Active thermography methods enable structural investigations of reinforced concrete elements taking into account many different testing problems. The goal of this review is to provide an overview on the state-of-the-art regarding the use of active infrared thermography (IRT) for detection and characterization of [...] Read more.
Active thermography methods enable structural investigations of reinforced concrete elements taking into account many different testing problems. The goal of this review is to provide an overview on the state-of-the-art regarding the use of active infrared thermography (IRT) for detection and characterization of defects in reinforced concrete. The paper will provide the physical background, equipment being used, as well as post-processing methods that are used to analyse sequences of thermograms. This work also presents the fields of applicability of IRT with a focus on the aspects related to reinforced concrete structures, as well as the advantages, limitations and potential sources of errors of IRT employment. Additionally previous non-destructive testing (NDT) studies that employed thermography techniques with natural excitation are briefly presented. A review of the future trends of thermal imaging are also included in this work. It can be concluded that while IRT is a useful tool for the characterisation of defects in the building sector, there is great prospect for the development of more advanced, effective and accurate approaches that will employ a combination of thermography approaches. Full article
(This article belongs to the Special Issue The World in Infrared Imaging)
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7439 KiB  
Article
Mapping of the Indoor Conditions by Infrared Thermography
by Frank Billy Djupkep Dizeu, Xavier Maldague and Abdelhakim Bendada
J. Imaging 2016, 2(2), 10; https://doi.org/10.3390/jimaging2020010 - 07 Apr 2016
Cited by 8 | Viewed by 8341
Abstract
We present an instrumentation devoted to the mapping of indoor ambient conditions by an infrared camera. In addition to a measurement grid composed of several spherical sensors, an infrared camera is used to visualize and quantify the spatial distribution of the air temperature, [...] Read more.
We present an instrumentation devoted to the mapping of indoor ambient conditions by an infrared camera. In addition to a measurement grid composed of several spherical sensors, an infrared camera is used to visualize and quantify the spatial distribution of the air temperature, the air speed, and the mean radiant temperature. A suitable procedure is developed so that from its temperature history recorded by the infrared camera, each sensor can measure, after solving an inverse heat transfer problem, all the three cited parameters. As the sensors are all imaged at the same time by the camera, an interpolation is done with the values they provide; the 2D distribution of each parameter is then obtained. By using a pair of stereoscopic cameras, it is possible to determine the 3D coordinates of each sensor of the measurement grid; consequently, the 3D mapping of the indoor ambient conditions is possible. Two steps are followed and allow us to achieve our goal: the validation of the performance of the sensor in terms of accuracy and reliability, and the validation of the complete experimental procedure which relies on digital image processing and on inverse heat transfer. Full article
(This article belongs to the Special Issue The World in Infrared Imaging)
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