ZM-SPECK: A Fast and Memoryless Image Coder for Multimedia Sensor Networks

Abstract

The set partitioned embedded block (SPECK) algorithm is an efficient block-based image coder to encode wavelet transformed images. SPECK uses linked lists to track significant/insignificant coefficients and block sets, thereby having a large memory requirement that increases with the encoding rate. Furthermore, multiple memory read/write operations and list management slow down the algorithm. In addition, the implementation of the traditional discrete wavelet transform (DWT) is memory intensive and time-consuming. Therefore, it is difficult to implement image coding using the traditional DWT and SPECK algorithm on low-cost visual sensor nodes. Most of the existing studies on low-memory implementations of the SPECK algorithm attempt to replace the dynamic memory of linked lists by a static memory in the form of fixed-length state tables/markers. In this paper, a fast and memoryless image coder is proposed, which uses the fractional wavelet filter to calculate the DWT coefficients of the image and a zero-memory listless SPECK algorithm for quantization and coding of the DWT coefficients. The proposed algorithm, referred as zero-memory SPECK (ZM-SPECK), completely eliminates the linked lists and only uses a few registers to perform some low-level arithmetic/logical operations. The elimination of linked lists also reduces the memory access time, thereby making ZM-SPECK faster than the original SPECK algorithm. Simulation results show that the proposed ZM-SPECK coder outperforms the contemporary state-of-the-art wavelet image coders in terms of memory requirement and computational complexity, while retaining their coding efficiency. The proposed ZM-SPECK image coder is thus very well suited for image communication in visual sensor networks.