Low-complexity video compression for capsule endoscope based on compressed sensing theory

Recently, the notions of compressed sensing (CS) have attracted attention as an innovative concept in signal processing. In this exploratory paper, a CS-based video compression approach suitable for wireless capsule endoscopy is proposed. In general, the amount of video data generated by capsule endoscopy is so large that video compression is the best way to lower the communication bandwidth and save the RF transmitting power. However, due to power limitation and small size conditions, traditional video compression techniques are not appropriate. Applying state-of-the-art CS theory may significantly reduce power consumption and memory of video compressor, thanks to its low computational complexity. The proposed approach is based on YUV color space conversion, blocking, zigzag scan and CS measuring. Experimental results show the feasibility of the proposed idea and that future improving works are necessary.