Low-memory video compression architecture using strip-based processing for implementation in wireless multimedia sensor networks
Faculty of Computing, Health and Science
School of Engineering / Centre for Communications Engineering Research
This paper presents a very low-memory video compression architecture for implementation in a wireless multimedia sensor network. The approach employs a strip-based processing technique where a group of image sequences is partitioned into strips, and each strip is encoded separately. A new one-dimensional, memory-addressing method is proposed to store the wavelet coefficients at predetermined locations in the strip buffer for ease of coding. To further reduce the memory requirements, the video-coding scheme uses a modified set-partitioning in hierarchical trees algorithm to give a high compression performance. The proposed work is implemented using a soft-core microprocessor-based approach. Simulation tests conducted have verified that even though the proposed video compression architecture using strip-based processing requires a much less complex hardware implementation and its efficient memory organisation uses a lesser amount of embedded memory for processing and buffering, it can still achieve a very good compression performance.