13 research outputs found
Temperature reconstruction of infrared images with motion deblurring
Infrared images of an uncooled microbolometer camera can show significant
blurring effects while recording a moving object. The electrical signal in
the pixel of a microbolometer detector decays exponentially; hence, the
moving object is mapped to more pixels resulting in a blurred image. Not only
the contrast is corrupted by the motion, but also the temperature of the
object seems to be significantly lower. In this paper, it is shown how such
images can be deblurred and the true temperature with a good approximation
restored. Since the detection mechanism of a microbolometer camera is
different from complementary metal–oxide–semiconductor (CMOS) or
charge-coupled device (CCD) cameras, also the point-spread function (PSF)
needed for the deblurring restoration is different. It is shown how the
exponential coefficient of the PSF can be calculated if the motion speed and
the camera resolution are known, or otherwise how it can be estimated from
the image itself. Experimental examples are presented for motion deblurring
used to restore images with linear or rotational motion
Thermal resistance field estimations from IR thermography using multiscale Bayesian inference
The main goal of this paper is the estimation of thermal resistive fields in multilayer samples using the classical front face flash method as excitation and InfRared Thermography (IRT) as a monitoring sensor. The complete inverse processing of a multilayer analytical model can be difficult due to a lack of sensitivity to certain parameters (layer thickness, depth of thermal resistance, etc.) or processing time. For these reasons, our present strategy proposes a Bayesian inference approach. Using the analytical quadrupole method, a reference model can be calculated for a set of parameters. Then, the Bayesian probabilistic method is used to determine the maximum likelihood probability between the measured data and the reference model. To keep the processing method robust and fast, an automatic selection of the calculation range is proposed. Finally, in the case of a bilayer sample, both the thickness and resistive 3D layers are estimated in less than 2 min for a space and time matrix of 50,000 pixels by 4000 time steps with a reasonable relative error of less than 5%
Thermal (IR) and Other NDT Techniques for Improved Material Inspection
International audienc