# MB-OFDM-UWB Based Wireless Multimedia Sensor Networks for Underground Coalmine: A Survey
## 4 Other Research Issues
### Information Processing  
With the limitations in energy, processing capacity and other resources of sensor nodes, introducing information processing techniques into the acquiring, transmitting and displaying information processing techniques in WMSNs is an effective way to lift the QoS performance of multimedia service. Among these information processing techniques, compression coding, filtering and data fusion are the most common ones. Compression coding techniques compress image, audio and video streams which are tremendous in data amount, saving the bandwidth resource of network while providing high-quality multimedia service. Filtering techniques can filter out parts of data which are not interesting for observers and not valuable for monitoring results from raw sensing data, thus gaining useful monitoring information which are small in data quantity. In energy-limited WMSNs, the research for these information processing techniques would be particularly important. Apart from compression coding and filtering, data fusion also plays an important role, which is mainly shown in saving the resource of network and enhancing the accuracy of collected data. In [65], for video sensor networks, an image fusion algorithm based on visual correlation is proposed. Given the limited resource constraints on each single video sensor and the redundant visual information among multiple video sensors, the algorithm partitions a sensing task into the two highly correlated video sensors and utilizes the epipolar constraint to fuse the received multiple partial images and to reconstruct a complete visual scene. Shown by experiments, the algorithm can not only reduce the transmission workload and save network energy, but also conduct the visual monitoring task in an effective way. Nevertheless, the method works on the system level, without considering the pixel-level redundancy in lower layer and video compression techniques. In addition,  
Figure 6: Video collaborative localization of miner’s lamp based on WMSNs: (**a**) localization scene; and (**b**) camera vision imaging model. the assumed conditions in reconstructing a scene restrict the algorithm from being applied in the scene which has different hierarchy or depth. On the basis of YUV color space and the view correlation of adjacent nodes, [PERSON] et al. [66] has come up with an image fusion method that assigns monitor task to three video sensor nodes that are highly correlated. Then, with the depth information model, adaptive quadtree partitioning and space transform, the luminance and chrominance parts of decoded data are fused, which realizes the reconstruction of the color image of the scene. The method has achieved good tradeoffs between the storage of video sensors, transmission cost and scene monitoring quality. For the sake of generating high-resolution images with wide field of view under constraint network resource, [PERSON] et al. [67] utilizes the redundancy of visual information among multiple video sensors, and stitches two or more images which have overlapped regions together to make a wide-angle high-resolution one. Thus, the requirements of advanced applications in video surveillance can be satisfied, and the network load can be reduced which thereby prolongs network lifetime. In brief, these algorithms involve multiple information processing techniques and achieve evident effects. The WMSNs for underground coalmine normally consist of a large number of video, audio and scalar sensor nodes. Given a source of monitoring data, different applications in a network may require disparate information (e.g., for video surveillance, video streams are needed while for coalmine environment monitoring, scalar data is collected). In addition, some information, such as signals for detecting high concentration of flammable gas, is with top priorities and needs to be reported directly to the ground monitoring center, while other information like air humidity may be queried and processed with normal periods and priorities.