  In this work, we show that reconstructing a sparse signal from quantized
compressive measurement can be achieved in an unified formalism whatever the
(scalar) quantization resolution, i.e., from 1-bit to high resolution
assumption. This is achieved by generalizing the iterative hard thresholding
(IHT) algorithm and its binary variant (BIHT) introduced in previous works to
enforce the consistency of the reconstructed signal with respect to the
quantization model. The performance of this algorithm, simply called quantized
IHT (QIHT), is evaluated in comparison with other approaches (e.g., IHT, basis
pursuit denoise) for several quantization scenarios.
