| Paper: | SAM-L3.6 | ||
| Session: | Sensor Networks II | ||
| Time: | Thursday, May 18, 11:40 - 12:00 | ||
| Presentation: | Lecture | ||
| Topic: | Sensor Array and Multichannel Signal Processing: Data fusion and decision fusion from multiple sensor types | ||
| Title: | Environmental Sampling with Multiscale Sensing | ||
| Authors: | Xiangming Kong, Richard Pon, William Kaiser, Gregory Pottie, University of California, Los Angeles, United States | ||
| Abstract: | Environment reconstruction through sampling is a difficult task and usually requires a large amount of resources. In this paper, a sampling technique is presented that approaches exhaustive sampling performance with only sparse samples. The goal is achieved by combining information from sensors of different types and resolutions. Image processing techniques are employed to extract global information. This information is passed on to the local sensors to optimize the number and locations of low-level sampling points. The sampled values are then applied back to the image to reconstruct the whole field. The technique is tested in the lab setup and shown to achieve a better result than traditional sampling methods. | ||
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