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A Local Feature based Fusion Algorithm for Fire Detection Image

机译:基于局部特征的火灾检测图像融合算法

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Image fusion is an very important process for fire detection, it generates a single combined image that contains a more accurate description of the fire scene than multiple images from different sources. In this paper, a local feature based fusion algorithm for fire detection image is proposed. Using the non-subsampled contourlet transform (NSCT), each of the visual and infrared fire detection images is decomposed into a low frequency and a set of high frequency subbands. Then the fused coefficients are generated by applying different local feature measure to the low frequency and high frequency subbands, respectively. And the fused image is obtained by taking inverse NSCT. Experimental results indicate that the proposed method outperforms other methods in both of fire target enhancement and background detail preservation.
机译:图像融合是火灾检测的一个非常重要的过程,它产生单个组合图像,该组合图像包含比来自不同源的多个图像更准确的火场描述。本文提出了一种用于火灾检测图像的局部特征融合算法。使用非分配的Contourlet变换(NSCT),每个视觉和红外火灾检测图像被分解成低频和一组高频子带。然后,通过将不同的本地特征度量分别应用于低频和高频子带来生成融合系数。通过逆向NSCT获得熔融图像。实验结果表明,该方法在火灾目标增强和背景细节保存中表现出其他方法。

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