Salman, M.S.Eleyan, A.Deprem, ZeynelÇetin, A. Enis2016-02-082016-02-082013http://hdl.handle.net/11693/27912Date of Conference: 3-5 Dec. 2013Signal and image reconstruction from Fourier Transform magnitude is a difficult inverse problem. Fourier transform magnitude can be measured in many practical applications, but the phase may not be measured. Since the autocorrelation of an image or a signal can be expressed as convolution of x(n) with x(-n), it is possible to formulate the inverse problem as a non-negative matrix factorization problem. In this paper, we propose a new algorithm based on the sparse non-negative matrix factorization (NNMF) to estimate the phase of a signal or an image in an iterative manner. Experimental reconstruction results are presented. © 2013 IEEE.EnglishFourier transform magnitudesNonnegative matrix factorizationPhase retrievalSparse non-negative matrix factorizationsSparse signalsData processingImage reconstructionIterative methodsInverse problemsConference Paper10.1109/GlobalSIP.2013.6737089