Pablo Meza

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In this paper, the face recognitions rate performance using infrared imagery is improved by adding nonuniformity pre-processing techniques. The infrared spectra contains the heat energy emitted by a face and it naturally present an insensitive behavior to variations in illuminations. Infrared imaging system can be formed by a Focal-Plane-Array technology, a(More)
In this paper, a comprehensive spatio-spectral and temporal analysis for Chromobacterium violaceum colonies is reported. A hyperspectral imaging (HSI) system is used to recover the spectral signatures of pigment production in a non-homogeneous media with high spectral resolution and high sensitivity in vivo, without destructing the sample. This non-contact(More)
Infrared imaging suffer from an undesired fixed-pattern noise mainly due to the response disparity of the individual detectors in a focal-plane array. Even though this nonuniformity noise can be removed after a blackbody calibration procedure, it tends to reappear due to the intrinsic nature of infrared sensing. Online nonuniformity correction techniques(More)
In this paper, we use the recently presented wavelet-FFT filter [1] to reduce the nonuniformity noise that affect almost all infrared imaging systems. The wavelet-FFT filter was originally developed to compensate the one-dimensional noise known as stripping noise. We perform an extension of this methodology in order to compensate the two-dimensional noise(More)
In [1] we presented a recursive filter to estimate the detector offset nonuniformity (NU) noise present in infrared (IR) imaging systems. Such a filter was derived considering an estimation time-window short enough so that the offset NU can be regarded as a constant in noise. Since the offset NU is non-stationary, upon the arrival of new blocks of IR data(More)
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