Non-uniqueness theory in sampled STFT phase retrieval

TL;DR

This paper demonstrates that, in sampled STFT phase retrieval, multiple distinct functions can produce identical spectrogram samples, showing non-uniqueness and the absence of a critical sampling density for unique recovery.

Contribution

The paper establishes general non-uniqueness results for sampled STFT phase retrieval, constructing explicit counterexamples across various dimensions, windows, and sampling lattices.

Findings

Counterexamples to unique recovery from sampled spectrograms.

Non-existence of a critical sampling density for phase retrieval.

Non-uniqueness persists even with real-valued windows and equal magnitude functions.

Abstract

The reconstruction of a function from its spectrogram (i.e., the absolute value of its short-time Fourier transform (STFT)) arises as a key problem in several important applications, including coherent diffraction imaging and audio processing. It is a classical result that for suitable windows any function can, in principle, be uniquely recovered up to a global phase factor from its spectrogram. However, for most practical applications only discrete samples - typically from a lattice - of the spectrogram are available. This raises the question of whether lattice samples of the spectrogram contain sufficient information for determining a function $f\in L^2(\mathbb{R}^d)$ up to a global phase factor. In the present paper, we answer this question in the negative by providing general non-identifiability results which lead to a non-uniqueness theory for the sampled STFT phase retrieval problem. Precisely, given any dimension $d$, any window function $g$ and any (symplectic or separable) lattice $\mathcal{L} \subseteq \mathbb{R}^d$, we construct pairs of functions $f,h\in L^2(\mathbb{R}^d)$ that do not agree up to a global phase factor, but whose spectrograms agree on $\mathcal{L}$. Our techniques are sufficiently flexible to produce counterexamples to unique recoverability under even more stringent assumptions; for example, if the window function is real-valued, the functions $f,h$ can even be chosen to satisfy $|f|=|h|$. Our results thus reveal the non-existence of a critical sampling density in the absence of phase information, a property which is in stark contrast to uniqueness results in time-frequency analysis.