This paper introduces a novel framework for single-pixel imaging via compressive sensing
(CS) in shift-invariant (SI) spaces by exploiting the sparsity property of a wavelet
representation. We reinterpret the acquisition procedure of a single-pixel camera as filtering
of the observed signal with continuous-domain functions that lie in an SI subspace spanned
by the integer shifts of the box function. The signal is modeled by an arbitrary SI generator
whose special case is the box function, which, as we show in the paper, is conventionally …