In several applications, it is important to determine if a target can be easily detected, recognized or identified. It is common practice to measure its thermal signature, represented by the thermal contrast, defined as the target background differencial temperature. In order to obtain the thermal contrast, it is necessary to establish a relationship between the radiance detected by the sensor and the target temperature. Energy emitted by the target will depend not only on its temperature but also on its emissivity. On the other hand, energy received on the sensor will depend, among other factors, on the atmospheric conditions which will affect the path radiance. Hence, target temperature, emissivity and atmospheric conditions are essential parameters in order to give accurate measurements of the thermal contrast. In this work, we propose a comparison between two methods to split temperature and emissivity from radiance measurements, "The Grey Body Emissivity (GBE)" algorithm and the "Bayesian Inference (BI)" method. This
comparison has been done with spectral radiance measured with a FTIR spectroradiometer in the MWIR (3-5μm) and LWIR (8-12μm) bands. Measurements were done over a blackbody at different distances (ranging from 6cm to 15m) and temperatures (ranging from 0°C to 140°C), and over metallic plates of different materials and finishing at a fixed temperature of 55°C. Atmospheric conditions were modeled using MODTRAN 4.0 v3r1 computer code.
Active imaging systems allow obtaining data in more than two dimensions. In addition to the spatial information, these systems are able to provide the intensity distribution of one scene. From this data channel a certain number of physic magnitudes that show some features of the illuminated surface can be recovered. The different behaviours of the scene elements about the directionality of the optical radiation, wavelength or polarization improve the ability to discriminate them. In this work, the capabilities of one 3D imaging laser scanner have been tested from both dimensional and radiometric points of view. To do this, a simple model of the observing system and the scene, in which only the directional propagation of the energy is taken into account, has been developed. Selected parameters corresponding to transmission, reception and optomechanical components of the active imaging system describe the full sensor. The surfaces of a non-complex scene have been divided into different elements with a defined geometry and directional reflectance. In order to measure the directional reflectance of several materials in the specific wavelength where the laser scanner works, a laboratory bench has been developed. The calculation of the received signal by the sensor has been carried out using several radiative transfer models. These models were validated by experiments in a laboratory with controlled conditions of illumination and reflectance. To do this, a certain number of images (angle, angle, range and intensity) were acquired by a commercial laser scanner using several standard targets calibrated in geometry and directional reflectance.
Based on the requirements in several applications of object and surface remote identification, and considering the advantages of using multispectral techniques, several systems that allow image acquisition in both specific subbands and single wavelengths have been developed by our group. These systems are based on different techniques. They comprise visible and NIR ranges, with different spectral resolution. Three experimental setups have been developed. The first system is a camera with a filter wheel to choose different spectral bands. The second setup consists of a high-speed camera in which a 1 nm-resolution liquid crystal tunable filter has been assembled. The full system is automatic and allows a fast scan of visible subbands. The third setup uses the same imaging sensor as system #2, but in this case the filter has been substituted by a slit-spectrograph which splits the visible radiation into the different wavelengths that compose the small area observed. The desired wavelength is therefore selected by extracting the appropriate columns of the image acquired from the sensor. The correlation between wavelengths and the CCD array is determined in previous calibration steps. An additional rotatory stage allows the scanning of scenes. Software has been developed to control the systems and make automatic measurements. A new file format specially developed for this project allows the storage of all the images acquired in a single file, which allows a faster ulterior spectral analysis. A bands selection application simplifies the image acquisition depending on the observed scene. The images obtained by the systems will be analyzed in some subsequent stages: qualitative and behavioural study of the elements in the scene, comparison of resolution and operation capabilities of the different configurations and image calibration.
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