Abstract
<span lang="EN-US">To prolong the life cycle of wireless sensor network, the basic theory of wavelet transform and its application in image compression are described, and several classic image compression algorithms based on wavelet transform are studied in depth. A compression algorithm combining the improved wavelet transform and <a name="_Hlk527539123"></a>Set Partitioning in Hierarchical Trees (SPIHT) algorithm of hierarchical wavelet tree set segmentation is proposed to effectively balance the energy consumption of each node in the sensor network and prolong the life of the whole wireless sensor network and an improved distributed image compression and transmission algorithm is proposed based on the distributed multi-node cooperative processing algorithm based on wavelet transformation, and detailed analytical test and energy consumption simulation experiment are carried out to verify the feasibility of the algorithm. The results show that the platform effectively implements and verifies the proposed algorithm, which can effectively realize the compression and transmission of distributed images, equalize the energy consumption of each sensor node in the network, and has strong practicability.</span>
Highlights
As a representative of advanced productive forces, the development of science and technology has continuously promoted the progress of human civilization and has had a profound impact on human material life, social culture and spiritual civilization
Wireless sensor network technology is widely used in medical, military, vehicle network, environmental detection and other fields due to its low cost, convenience, reliability and wide application scenarios
The traditional image objective quality evaluation algorithm is mainly based on Mean Squared Error (MSE) and Peak Signal to Noise Ratio (PSNR)
Summary
As a representative of advanced productive forces, the development of science and technology has continuously promoted the progress of human civilization and has had a profound impact on human material life, social culture and spiritual civilization. With the rapid development of high-end science and technology such as sensors, wireless communications, distributed and embedded sensing systems, the Wireless Sensor Network (WSN) has gradually become a hot research topic since its birth in the 1970s. People can spread sensor nodes in different application scenarios, build wireless sensor networks through mutual communication between nodes, collect information through sensors' perception of the surrounding environment, and process the iJOE ‒ Vol 15, No 1, 2019. As the size of the network grows larger, the amount of information that needs to be transmitted is increasing, especially the amount of multimedia information, making it impossible for energy-constrained sensor nodes to bear the overhead of data processing. Distributed image compression technology is important when wireless sensor networks transmit large amounts of information such as multimedia information. By adopting the distributed compression method, compared with the centralized compression, the energy consumption and the calculation amount required for the calculation task of a single node can be distributed to multiple nodes, which is beneficial to increase the life cycle of the entire network
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