Low power hardware-based image compression solution for wireless camera sensor networks

a r t i c l e i n f o Keywords: Image compression Wireless sensor networks System-on-chip Low power hardware VLSI In this paper, we present and evaluate a hardware solution for user-driven and packet loss tolerant image compression, especially designed to enable low power image compression and communication over wireless camera sensor networks (WCSNs). The proposed System-on-Chip is intended to be designed as a hardware coprocessor embedded in the camera sensor node. The goal is to relieve the node microcontroller of the image compression tasks and to achieve high-speed and low power image processing. The interest of our solution is twofold. First, compression settings can be changed at runtime (upon reception of a request message sent by an end user or according to the internal state of the camera sensor node). Second, the image compression chain includes a (block of) pixel interleaving scheme which significantly improves the robustness against packet loss in image communication. We discuss in depth the internal hardware architecture of the encoder chip which is planned to reach high performance running in FPGAs and in ASIC circuits. Synthesis results and relevant performance comparisons with related works are presented. The technological advances in wireless communication and microelectronics allow today to build small, inexpensive, and battery-powered sensing devices with on-board processing and communication capabilities. These devices, called wireless sensor nodes, can be densely deployed over large regions of space in order to collect data from their surrounding and to send them to a sink node. The data packets are transmitted in multi-hop mode through a self-organized and infrastructure-less wireless sensor network which is built by coordination between the sensor nodes [18]. There is a wide range of applications envisioned for such wireless sensor networks, including, e.g., environmental monitoring, habitat sensing, precision agriculture, disaster management, structural health monitoring, target imaging and tracking, and military operations. However, the energy supply to these nodes is scarce due to the limited capacities of the batteries. This makes the energy efficiency as one of the fundamental problems in wireless sensor networks and consequently , special challenges for energy-efficient data processing and communication must be addressed. More recently, there is a growing interest for the applications which require image sensing in order to achieve object detection, localization, tracking, and counting [2,5]. In this case, some nodes in the wireless sensor network are equipped with a small CMOS camera [1,6,7]. Such a sensor network …