The design and successful fielding of sensors and detectors vital for homeland security can benefit greatly by the use of advanced signal and image processing techniques. The intent is to extract as much reliable information as possible despite noisy and hostile environments where the signals and images are gathered. In addition, the ability to perform fast analysis and response necessitate significant compression of the raw data so that they may be efficiently transmitted, remotely accumulated from different sources, and processed. Proper decompositions into compact representations allow fast pattern detection and pattern matching in real time, in situ or otherwise. Wavelets for signals and curvelets for images or hyperspectral data promise to be of paramount utility in the implementation of these goals. Together with statistical modeling and iterative thresholding techniques, wavelets, curvelets and multiresolution analysis can alleviate the severity of the requirements which today’s hardware designs can not meet in order to measure trace levels of toxins and hazardous substances. Photonic or electrooptic sensor and detector designs of the future, for example, must take into account the end game strategies made available by advanced signal and image processing techniques. The promise is the successful operation at lower signal to noise ratios, with less data mass and with deeper statistical inferences made possible than with boxcar or running averaging techniques (low pass filtering) much too commonly used to deal with noisy data at present. SPREE diagrams (spectroscopic peak reconstruction error estimation) are introduced in this paper to facilitate the decision of which wavelet filter and which denoising scheme to use with a given noisy data set.
Z pinches produce an X ray rich plasma environment where backlighting imaging of imploding targets can be quite challenging to analyze. What is required is a detailed understanding of the implosion dynamics by studying snapshot images of its in flight deformations away from a spherical shell. We have used wavelets, curvelets and multiresolution analysis techniques to address some of these difficulties and to establish the Shell Thickness Averaged Radius (STAR) of maximum density, r*(N,θ) where N is the percentage of the shell thickness over which we average. The non-uniformities of r*(N,θ) are quantified by a Legendre polynomial decomposition in angle, θ, and the identification of its largest coefficients. Undecimated wavelet decompositions outperform decimated ones in denoising and both are surpassed by the curvelet transform. In each case, hard thresholding based on noise modeling is used.
Spatial-filter pinholes and knife-edge samples were irradiated in vacuum by 1053-nm, 5-20 ns pulses at intensities to 500 GW/cm2. The knife-edge samples were fabricated of plastic, carbon, aluminum, stainless steel, molybdenum, tantalum, gold, and an absorbing glass. Time- resolved two-beam interferometry with a 40-ns probe pulse was used to observe phase shifts in the expanding laser- induced plasma. For al of these materials, at any time during square-pulse irradiation, the phase shift fell exponentially with distance from the edge of the sample.. The expansion was characterized by the propagation velocity V2(pi ) of the contour for a 2(pi) phase shift. To within experimental error, V2(pi ) was constant during irradiation at a particular intensity, and it increased linearly with intensity for intensities < 300 GW/cm2. For metal samples V2(pi ) exhibited an approximate M-0.5 dependence where M is the atomic mass. Plasmas of plastic, carbon, and absorbing glass produced larger phase shifts, and expanded more rapidly, than plasmas of heavy metals. The probe beam and interferometer were also used to observe the closing of pinholes. With planar pinholes, accumulation of on-axis plasma was observed along with the advance of plasma away from the edge of the hole. On-axis closure was not observed in square, 4-leaf pinholes.
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