Abstract: Images in complex backgrounds may contain a large amount of interference information, making it difficult to accurately extract image feature vectors. Therefore, a salient target recognition algorithm for wireless sensor network images in complex backgrounds is proposed. Mean shift algorithm is used to cluster targets and achieve image segmentation, obtaining several segmented image feature vectors. By fusing rules, the pyramid shapes of each layer in the image pyramid are prosessed, and the image pyramid sequence is combined to achieve image reconstruction. The image saliency of pixels is determined based on the results of image reconstruction and histogram statistics, and image saliency target recognition is achieved through pixel order expansion and sorting. The experimental results show that the proposed algorithm can accurately identify salient targets in wireless sensor network images under complex backgrounds, and the texture details of the image are clear, with good practical application effects. 

Key words: wireless sensor network, complex background images, significance target identification, image segmentation, low pass filtering