This seminar will cover two novel algorithms for (i) image deconvolution
in moment domain and (ii) signal analysis by using a new discrete orthogonal
moment. The first part of this talk will present a new method for image
deconvolution from the geometric moments (GMs) of a degraded image by a
circular or elliptical Gaussian point-spread function (PSF). The proposed
moment
equation invertibility in a closed form paves the way to reconstruct the
original image using the Stirling numbers of the first kind. The theoretical
analysis of the proposed scheme willbe validated through the comparative
studies.

The second part of seminar will address some computational aspects and
applications of the polynomial unbiased finite impulse response functions as a
new class of a one-parameter family of discrete orthogonal polynomials. Two new
explicit formulas (discrete Rodrigues’representation and hypergeometric form)
to compute these polynomials will be derived, directly. These straightforward
calculations lead us to propose another discrete signal representation in
moment domain. Experimental results show a comparison between the proposed
moments and discrete Chebyshev momentsin terms of noise-free/noisy signal
feature extraction and reconstruction error.