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Recently a new classification assumption was proposed in [1]. It assumed that the training samples of a particular class approximately form a linear basis for any test sample belonging to that class. The classification algorithm in [1] was based on the idea that all the correlated training samples belonging to the correct class are used to represent the(More)
This works addresses the problem of reconstructing multiple T1- or T2-weighted images of the same anatomical cross section from partially sampled K-space data. Previous studies in reconstructing magnetic resonance (MR) images from partial samples of the K-space used compressed sensing (CS) techniques to exploit the spatial correlation of the images (leading(More)
This paper proposes a Majorization-Minimization approach for solving the synthesis and analysis prior joint-sparse multiple measurement vector reconstruction problem. The proposed synthesis prior algorithm yielded the same results as the Spectral Projected Gradient (SPG) method. The analysis prior algorithm is the first to be proposed for this problem. It(More)
The problem of recognizing a face from a single sample available in a stored dataset is addressed. A new method of tackling this problem by using the Fisherface method on a generic dataset is explored. The recognition scheme is also extended to multiscale transform domains like wavelet, curvelet and contourlet. The proposed method in the transform domain(More)