**5. Conclusions**

In this paper, we presented the error resilient transmission scheme for block compressed sensing. For error-free transmission, we found that adaptive sampling enhanced the reconstructed image quality under both equality and the quadratic constraints. For lossy transmission, we observed the vulnerability of compressively sensed information for transmission over lossy channels, and noted the need to provide protection schemes to alleviate the effects of data loss. We proposed our algorithm to transmit compressed information over multiple independent and lossy channels, and to work with multiple description coding for protection and reconstruction. For grey-level images, multiple description coding demonstrated effective protection. For color images, high correlations between the color planes can further aid better quality of reconstruction. The simulation results presented enhanced performance with multiple description coding and adaptive sampling. A wide range of lossy probabilities were simulated to verify the effectiveness of multiple description coding for protecting block compressed sensing. In future, we intend to look for other effective means and the ways to choose the parameter values to ensure error resilient transmission for compressed sensing of images.

**Author Contributions:** Conceptualization, H.-C.H.; formal analysis, P.-L.C. and F.-C.C.; investigation, P.-L.C.; methodology, H.-C.H. and F.-C.C.; software, P.-L.C.; writing–original draft, H.-C.H.; writing–review and editing, H.-C.H. and F.-C.C. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the Ministry of Science and Technology of Taiwan, R.O.C., grant number MOST 107-2221-E-390-018-MY2.

**Conflicts of Interest:** The authors declare no conflict of interest.
