A Compression Method Based on Compressive Sampling for 3-D Laser Range Scans of Indoor Environments

Abstract

When 3-D models of environments need to be transmitted or stored, they should be compressed efficiently to increase the capacity of the communication channel or the storage medium. We propose a novel compression technique based on compressive sensing, applied to sparse representations of 3-D range measurements. We develop a novel algorithm to generate sparse innovations between consecutive range measurements along the axis of the sensor's motion, since the range measurements do not have highly sparse representations in common domains. Compared with the performances of widely used compression techniques, the proposed method offers the smallest compression ratio and provides a reasonable balance between reconstruction error and processing time.

Novel Compression Algorithm Based on Sparse Sampling of 3-D Laser Range Scans

“…Therefore, the proposed method is a kind of difference encoding technique. In summary, the proposed method provides acceptable CR compared with the alternative compression techniques that we have considered, and as it provides a reasonably good compromise between reconstruction accuracy and speed, it can be properly used for 3-D representation of environments [57]. The proposed method can be improved by coding the encoder output further via lossless coding techniques such as arithmetic coding or LZ77 [50], to reduce the CR even more.…”