Saliency area detection algorithm of electronic information and image processing based on multi-sensor data fusion

Researched in the 1980s, multi-sensor data convergence has become a hot issue. Not only does it differ from general signal processing, or single to multiple sensor surveillance and measurement, on the other hand, it is a higher level of integrated decision-making processes based on multiple sensor measurement outcomes, this paper is based on the study of the saliency area detection algorithm of electronic information and image processing based on multi-sensor data fusion, based on the improved FT algorithm and LC algorithm using multi-sensor data fusion technology, a new LVA algorithm is proposed, and these three algorithms are evaluated in an all-round way through various algorithm evaluation indicators such as PR curve, PRF histogram, MAE index, and recognition image rate. The research results show that the LVA algorithm proposed in this paper improves the detection rate of saliency maps by 5–10%.