基于小波分析的烟雾多特征融合和空间精度补偿森林火情检测算法

提出一种基于烟雾图像多特征融合和空间精度补偿的森林火情检测算法。该算法首先将基于小波分析和运动分析的烟雾检测结果进行融合，然后利用烟雾的颜色特征和运动特征将融合检测结果累积，实现检测烟雾，并基于图像中的地平线信息进行空间精度补偿下的烟雾区域提取。实验结果表明此算法可提高检测的准确性，降低误检率，对环境较为鲁棒，在森林防火中具有重要的应用价值。

Forest-fire Detection Algorithm Based on Multiple Features Fusion by Wavelet Analysis and Spatial Accuracy Compensation

An algorithm for detecting forest-fire was proposed, which was based on multiple features fusion of smoke and spatial accuracy compensation.Firstly the detection results derived separately from motion analysis and wavelet analysis were fused, and then the fusion results were cumulated using smoke color and motion cues to realize the smoke detection.The smoke profiles were extracted with spatial accuracy compensation based on the scene horizon.We have tested our algorithm on a number of image sequences, and the results show that our algorithm can provide significant improvements over accuracy of forest-fire detection, decrease false alarm rate and enhance the robustness.This approach has important application value in forest-fire surveillance system.