  We propose a new method, {\it robust binary fused compressive sensing}
(RoBFCS), to recover sparse piece-wise smooth signals from 1-bit compressive
measurements. The proposed method is a modification of our previous {\it binary
fused compressive sensing} (BFCS) algorithm, which is based on the {\it binary
iterative hard thresholding} (BIHT) algorithm. As in BIHT, the data term of the
objective function is a one-sided $\ell_1$ (or $\ell_2$) norm. Experiments show
that the proposed algorithm is able to take advantage of the piece-wise
smoothness of the original signal and detect sign flips and correct them,
achieving more accurate recovery than BFCS and BIHT.
