Adaptive measurement rate allocation for block-based compressed sensing of depth maps

In recent years, compressed sensing (CS) has been used for compressing depth maps for the multi-view video plus depth. In these compression schemes, every block of the depth map is sampled with a fixed non-adaptive sensing matrix and the algorithms are generally incorporated into conventional codecs like H.264/AVC, resulting in high computational complexity both at the encoder and decoder. In this paper, we present a novel block-based CS codec for compressing depth maps that has two major features. First, an adaptive measurement rate allocation algorithm is introduced that computes the measurement rate for each compressively sensed block using rate-distortion optimization (RDO). Second, a simple block classification and frame-differencing module is utilized to reduce encoding complexity while maintaining good RD performance. Simulation results clearly show that the proposed codec has superior rate-distortion (RD) performance in comparison to H.264/AVC Baseline Profile (up to 3 dB gain) and an encoding time reduction of up to 97%.