Compressive sensing-based multiple description image coding for wireless channel

A new theory, known as Compressive Sensing (CS), has recently proved that sparse or compressible signal can be accurately reconstructed from very highly undersampled data by solving by solving a convex LI optimization problem. This paper, based on such new theory, presents a novel multiple description coding (MDC) method to combat packet loss. According to compressive sensing framework, our method has an attractive property that the reconstruction error only depends on the received measurement number but not on which measurements are received. Another advantage of our method is that it is a balanced MDC scheme with fine description granularity and low encoding complexity.