FrWF-Based LMBTC: Memory-Efficient Image Coding for Visual Sensors

摘要: After the successful development of JPEG2000, many state-of-the-art wavelet-based image coding algorithms have been developed. However, traditional discrete wavelet transform (DWT) is implemented with memory intensive and time-consuming and, therefore, has very high system resource requirements. In particular, large requirement poses a serious limitation for multimedia applications on memory-constrained portable devices, such as digital cameras sensor nodes. this paper, we propose novel coder low requirements complexity that preserves compression efficiency. Our encoder employs fractional filter (FrWF) to calculate DWT coefficients, which are quantized encoded block tree (LMBTC) algorithm. The LMBTC listless form Simulation results demonstrate proposed significantly reduces computational competitive efficiency in comparison other coders. FrWF combined is, thus, viable option communication over wireless networks.