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Infrared simulation plays an important role in small and affordable unmanned aerial vehicles. Its key and main goal is to get the infrared image of a specific target. Infrared physical model is established through a theoretical research, thus the temperature field is available. Then infrared image of a specific target can be simulated properly while taking atmosphere state and effect of infrared imaging system into account. For recent years, some research has been done in this field. Among them, the infrared simulation for large scale is still a key problem to be solved. In this passage, a method of classification based on texture blending is proposed and this method effectively solves the problem of classification of large number of images and increase the frame rate of large infrared scene rendering. The paper aims to discuss these issues.

Mosart Atmospheric Tool (MAT) is used first to calculate data of sun radiance, skyshine radiance, path radiance, temperatures of different material which is an offline process. Then, shader in OGRE does final calculation to get simulation result and keeps a high frame rate. Considering this, the authors convert data in MAT file into textures which can be easily handled by shader. In shader responding, radiance can be indexed by information of material, vertex normal, eye and sun. Adding the effect of infrared imaging system, the final radiance distribution is obtained. At last, the authors get infrared scene by converting radiance to grayscale.

In the fragment shader, fake infrared textures are used to look up temperature which can calculate radiance of itself and related radiance.

The radiance is transferred into grayscale image while considering effect of infrared imaging system.

Simulation results show that a high frame rate can be reached while guaranteeing the fidelity.

To show the wide range of applications of infrared imaging being used in industry.

Explains the recent cost reduction of infrared cameras, and reviews applications in product testing and quality control, process monitoring, structural inspection and fatigue limit measurement. Briefly reviews the capabilities of some off‐the‐shelf cameras.

That infrared imaging is a very powerful technique, bringing a whole new dimension of temperature detection to machine vision.

Highlights infrared imaging as a practicable and very valuable tool in industrial inspection.

A low cost two dimensional pyroelectric array technology has been developed, together with advanced signal processing algorithms. This enables the availability of intelligent passive infrared detector systems for surveillance, counting, and related applications. The technology has also made possible for the first time a truly affordable low‐resolution thermal imager for condition monitoring, plant maintenance, and process control.

This study aims to consider active vision in low-visibility environments to reveal the factors of optical properties which affect visibility and to explore a method of obtaining different depths of fields by multimode imaging.Bad weather affects the driver’s visual range tremendously and thus has a serious impact on transport safety.

A new mechanism and a core algorithm for obtaining an excellent large field-depth image which can be used to aid safe driving is designed and implemented. In this mechanism, atmospheric extinction principle and field expansion system are researched as the basis, followed by image registration and fusion algorithm for the Infrared Extended Depth of Field (IR-EDOF) sensor.

The experimental results show that the idea we propose can work well to expand the field depth in a low-visibility road environment as a new aided safety-driving sensor.

The paper presents a new kind of active optical extension, as well as enhanced driving aids, which is an effective solution to the problem of weakening of visual ability. It is a practical engineering sensor scheme for safety driving in low-visibility road environments.

Integrating complementary information with high-quality visual perception is essential in infrared and visible image fusion. Contrast-enhanced fusion required for target detection in military, navigation and surveillance applications, where visible images are captured at low-light conditions, is a challenging task. This paper aims to focus on the enhancement of poorly illuminated low-light images through decomposition prior to fusion, to provide high visual quality.

In this paper, a two-step process is implemented to improve the visual quality. First, the low-light visible image is decomposed to dark and bright image components. The decomposition is accomplished based on the selection of a threshold using Renyi’s entropy maximization. The decomposed dark and bright images are intensified with the stochastic resonance (SR) model. Second, texture information-based weighted average scheme for low-frequency coefficients and select maximum precept for high-frequency coefficients are used in the discrete wavelet transform (DWT) domain.

Simulations in MATLAB were carried out on various test images. The qualitative and quantitative evaluations of the proposed method show improvement in edge-based and information-based metrics compared to several existing fusion techniques.

In this work, a high-contrast, edge-preserved and brightness-improved image is obtained by the processing steps considered in this work to get good visual quality.

Infrared thermography is increasingly being used to diagnose pathologies in buildings, such as façade defects. The purpose of this paper is to assess the results reproducibility and the equipment influence on the measurements. To do so, it was defined as case study the assessment of rendering delamination.

Two infrared cameras of different makers were used to detect the presence of defects deliberately created in specimens. The tests were done in the laboratory with a heat source. The defects were detected through a temperature gradient between the zones with and without defect.

With this thermographic imaging, it was possible to identify the defects in the specimen both qualitatively and quantitatively. The results were found to be reproducible in the three cycles performed. The influence of the equipment on the results was of little significance for the quantitative assessment criterion “temperature difference between zones with and without defect”, but for the criterion “absolute surface temperature”, the difference in the results yielded by the two cameras was around 1.8°C.

The results suggest that there is reproducibility of the measurements, considering both the qualitative and quantitative approach, when assessing delamination, irrespective of the maker of the equipment used. The influence of the equipment on the results depends on the quantitative assessment criterion used.

Aero-engine exhaust plume length can be more than the aircraft length, making it easier to detect and track by infrared seeker. Aim of this study is to analyze the effect of free stream Mach number (M_∞) on length of potential core of plume. Also, change in infrared (IR) signature of plume and aircraft surface with variation in elevation angle (θ) is examined.

Convergent divergent (CD) nozzle is located outside the rear fuselage of the aircraft. A two dimensional axisymmetric computational fluid dynamics (CFD) study was carried out to study effect of M_∞ on potential core. The CFD data with aircraft and plume was then used for IR signature analysis. The sensor position is changed with respect to aircraft from directly bottom towards frontal section of aircraft. The IR signature is studied in mid wave IR (MWIR) and long wave IR (LWIR) band.

The potential plume core length and width increases as M_∞ increases. At higher altitudes, the potential core length increases for a fixed M_∞. The plume emits radiation in the MWIR band, whereas the aerodynamically heated aircraft surface emits IR in the LWIR band. The IR signature in the MWIR band continuously decreases as the sensor position changes from directly bottom towards frontal. In the LWIR band the IR signature initially decreases as the sensor moves from the directly bottom to the frontal, as the sensor begins to see the wing leading edges and nose cone, the IR signature in the LWIR band slightly increases.

The novelty of this study comes from the data reported on the effect of free stream Mach number on the potential plume core and variation of the overall IR signature of aircraft with change in elevation angle from directly below towards frontal section of aircraft.

The purpose of this paper is to develop a monocular visual measurement system for autonomous aerial refueling (AAR) for unmanned aerial vehicle, which can process images from an infrared camera to estimate the pose of the drogue in the tanker with high accuracy and real-time performance.

Methods and techniques for marker detection, feature matching and pose estimation have been designed and implemented in the visual measurement system.

The simple blob detection (SBD) method is adopted, which outperforms the Laplacian of Gaussian method. And a novel noise-elimination algorithm is proposed for excluding the noise points. Besides, a novel feature matching algorithm based on perspective transformation is proposed. Comparative experimental results indicated the rapidity and effectiveness of the proposed methods.

The visual measurement system developed in this paper can be applied to estimate the pose of the drogue with a fast speed and high accuracy and it is a feasible measurement strategy which will considerably increase the autonomy and reliability for AAR.

The SBD method is used to detect the features and a novel noise-elimination algorithm is proposed. Besides, a novel feature matching algorithm based on perspective transformation is proposed which is robust and accurate.

With the dramatically increasing number of substations, robots are expected to inspect equipment in the power industry. However, a traditional robotic system cannot work stably because of the strong electromagnetic field in substation. The purpose of this paper is to present a robust and stable robotic system for inspecting the substation equipment without the involvement of workers.

The paper presents in detail a robotic system that consists of a monitor center and a robot. With the monitor center, the workers could send inspection tasks and monitor status of the robot timely. Once a fault is detected, the alarm message will flash immediately to remind the workers. The patrol mode of the robot comprises teleoperation, regular inspection, special inspection and a key return mode. The robot only relies on a low-cost magnetic sensor for lateral positioning and radio frequency identification technology for longitudinal positioning when working under patrol mode. At each stop point, the substation equipment can be recognized quickly through accurate matching with the template image stored in the database.

It is shown that the robot could work efficiently and reliably in power substations. The positioning error is proved to be within 5 mm, compared to that of 20 cm by implementing integrated global positioning system-dead reckoning navigation. Because of the high positioning accuracy, it is much easier to recognize the substation equipment. It is observed that nearly 99 per cent of equipments can be recognized.

The proposed robotic system is tested in a simple substation environment. While the proposed system shows satisfactory positioning results, further studies considering changeable weather condition will focus on improving the equipment recognition rate in such environment, such as rainy, snowy and strong sunlight.

The key contribution of this paper is that it provides a robotic system to inspect substation equipment instead of workers, to improve working efficiency and to reduce manpower cost.

This paper presents a robotic system to inspect substation equipment instead of workers. Four patrol modes are designed to meet the inspection demand. Comparing with the previous robotic systems, this system contributes to higher position accuracy and higher equipment recognition rate.