Superresolution and noise filtering using moving least squares.

An irregularly spaced sampling raster formed from a sequence of low-resolution frames is the input to an image sequence superresolution algorithm whose output is the set of image intensity values at the desired high-resolution image grid. The method of moving least squares (MLS) in polynomial space has proved to be useful in filtering the noise and approximating scattered data by minimizing a weighted mean-square error norm, but introducing blur in the process. Starting with the continuous version of the MLS, an explicit expression for the filter bandwidth is obtained as a function of the polynomial order of approximation and the standard deviation (scale) of the Gaussian weight function. A discrete implementation of the MLS is performed on images and the effect of choice of the two dependent parameters, scale and order, on noise filtering and reduction of blur introduced during the MLS process is studied.

Landmine detection and classification with complex-valued hybrid neural network using scattering parameters dataset.

Neural networks have been applied to landmine detection from data generated by different kinds of sensors. Real-valued neural networks have been used for detecting landmines from scattering parameters measured by ground penetrating radar (GPR) after disregarding phase information. This paper presents results using complex-valued neural networks, capable of phase-sensitive detection followed by classification. A two-layer hybrid neural network structure incorporating both supervised and unsupervised learning is proposed to detect and then classify the types of landmines. Tests are also reported on a benchmark data.

High resolution image formation from low resolution frames using Delaunay triangulation.

An algorithm based on spatial tessellation and approximation of each triangle patch in the Delaunay (1934) triangulation (with smoothness constraints) by a bivariate polynomial is advanced to construct a high resolution (HR) high quality image from a set of low resolution (LR) frames. The high resolution algorithm is accompanied by a site-insertion algorithm for update of the initial HR image with the availability of more LR frames till the desired image quality is attained. This algorithm, followed by post filtering, is suitable for real-time image sequence processing because of the fast expected (average) time construction of Delaunay triangulation and the local update feature.

Vector quantization of neural networks.

The problem of vector quantizing the parameters of a neural network is addressed, followed by a discussion of different algorithms applicable for quantizer design. Optimal, as well as several suboptimal quantization schemes are described. Simulations involving nonlinear prediction of speech signals are presented to compare the performance of different quantization techniques. Performance evaluation conducted uncover the tradeoffs in implementational complexity. Among the three examined suboptimal quantization schemes, it is shown that the multistage quantizer offers the best tradeoff between complexity and performance.

Neural network design using Voronoi diagrams.

A novel approach is proposed which determines the number of layers, the number of neurons in each layer, and their connection weights for a particular implementation of a neural network, with the multilayer feedforward topology, designed to classify patterns in the multidimensional feature space. The approach is based on construction of a Voronoi diagram over the set of points representing patterns in feature space and this finds added usefulness in deriving alternate neural network structures for realizing the desired pattern classification.

Molecular cloning of Clostridium difficile toxin A gene fragment in lambda gt11.

Toxin A of Clostridium difficile has been purified and monospecific antiserum produced. A reliable procedure for isolation and restriction of C. difficile chromosomal DNA was developed which allowed for the construction of a genomic library in lambda gt11. Approx. 35,000 plaques were screened using anti-toxin A which resulted in the identification of one stable positive clone, lambda cd19. Verification of the immunological identity of the isolated toxin A gene fragment in lambda cd19 was determined by affinity purifying toxin A antibodies specific for lambda cd19 gene product, and using these selected antibodies to probe a Western blot of purified toxin A. The insert in lambda cd19 was demonstrated to be a 0.3 kb fragment by restriction digestion, and by hybridization of the clone to a chromosomal digest of C. difficile. The peptide coded for by the toxin A gene fragment in lambda cd19 was not cytotoxic for 3T3 mammalian tissue culture cells.