The Development Of A Low-power Wireless Transfer For Image Based On CS Theary

Recently, with the rapid development of the Internet of Things, multimedia sensornetwork (MSN) is growing concerned. Because of real-time acquisition andtransmission for multimedia information in a variety of environments efficiently,Low-power wireless multimedia sensor networks find applications very broad andbecome a core element in the future Internet of Things technology. Meeting thedemand of reducing power consumption in wireless communication andcommunicating normally in high-loss channel, has been an urgent problem for wirelesstransmission to solve.Candès introduced a novel theory of signal sampling, called compressed sensing(CS), in the international congress of mathematicians in2006. Thereafter, the CStheory became active signal reconstruction theory in recent years. By the sparsity ofthe signal, the original signal can be exactly or approximate accurately reconstructedonly with far less than the number of samples required by the Nyquist theorem. The CStheory has been demonstrated the advantages in many areas and is an effective way tosolve the contradictory between the channel’s capacity and mass information to betransmitted.In this paper, the CS theory’s application and implementation in low-powerwireless multimedia sensor networks was discussed. For video and image acquisitionsensor network, a novel video and image coding&wireless transmission system wasdesigned and implemented in a low-power platform.A modular structured design was used in the system, Based on low powerconsumption embedded development platform MSP430f449, applying the compressedsensing theory, the basic functions of the video&image coding, wireless transmissionand image reconstruction optimization were implemented. The system has highflexibility and scalability to support the data acquisition modules (sensors) to join aswell as receive other intelligent data acquisition algorithm transplant. The systemshould have a higher value in engineering.In the paper, the demand for wireless video image sensor network system and theresources of the development platform were analyzed, modular system was designed.The detailed hardware and algorithm designs for the key modules of the system werepresented. With the hardware and software condition in the low-power applications, the special algorithm for CS theory was discussed. To improve the quality of signalreconstruction, an effective compression and recovery algorithm suitable forlow-power application was improved and implemented.