Name
Title | ||
|---|---|---|
Phase retrieval of sparse signals from Fourier Transform magnitude using non-negative matrix factorization |
Abstract | ||
|---|---|---|
Signal 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. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/GlobalSIP.2013.6737089 | Global Conference Signal and Information Processing |
Keywords | DocType | ISSN |
convolution,correlation methods,image reconstruction,matrix decomposition,Fourier transform magnitude,NNMF,convolution,image autocorrelation,image reconstruction,inverse problem,nonnegative matrix factorization problem,phase estimation,phase retrieval,signal autocorrelation,signal reconstruction,sparse nonnegative matrix factorization,sparse signals | Conference | 2376-4066 |
Citations | PageRank | References |
0 | 0.34 | 1 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mohammad Shukri Salman | 1 | 33 | 9.09 |
| Alaa Eleyan | 2 | 51 | 5.64 |
| Zeynel Deprem | 3 | 0 | 0.68 |
| A. Enis Çetin | 4 | 871 | 118.56 |