NSCT域内结合边缘特征和自适应PCNN的红外与可见光图像融合
发布时间：2018-08-14 15:37
【摘要】：针对传统的基于多尺度变换的红外与可见光图像融合,对比度不高,边缘等细节信息保留不充分等问题,结合NSCT变换的多分辨率、多方向特性和PCNN全局耦合、脉冲同步激发等优点,提出一种基于NSCT变换结合边缘特征和自适应PCNN红外与可见光图像融合算法.对于低频子带,采用一种基于边缘的融合方法;对于高频方向子带,采用方向信息自适应调节PCNN的链接强度,使用改进的空间频率特征作为PCNN的外部激励,根据脉冲点火幅度融合子带系数.实验结果验证了该算法的有效性.
[Abstract]:Aiming at the problems of traditional infrared and visible image fusion based on multi-scale transform, the contrast is not high, the detail information such as edge is not enough, and so on, the multi-resolution, multi-direction characteristic and PCNN global coupling of NSCT transform are combined. Based on NSCT transform and edge feature, an adaptive PCNN infrared and visible image fusion algorithm is proposed. For low-frequency subbands, an edge-based fusion method is used, and for high-frequency directional subbands, directional information is used to adaptively adjust the link strength of PCNN, and an improved spatial frequency feature is used as the external excitation of PCNN. According to the pulse ignition amplitude fusion subband coefficient. Experimental results show that the algorithm is effective.
【作者单位】： 武汉大学测绘学院;武汉大学测绘遥感信息工程国家重点实验室;
【基金】：国家自然科学基金(No.41271456)
【分类号】：TP391.41
[Abstract]:Aiming at the problems of traditional infrared and visible image fusion based on multi-scale transform, the contrast is not high, the detail information such as edge is not enough, and so on, the multi-resolution, multi-direction characteristic and PCNN global coupling of NSCT transform are combined. Based on NSCT transform and edge feature, an adaptive PCNN infrared and visible image fusion algorithm is proposed. For low-frequency subbands, an edge-based fusion method is used, and for high-frequency directional subbands, directional information is used to adaptively adjust the link strength of PCNN, and an improved spatial frequency feature is used as the external excitation of PCNN. According to the pulse ignition amplitude fusion subband coefficient. Experimental results show that the algorithm is effective.
【作者单位】： 武汉大学测绘学院;武汉大学测绘遥感信息工程国家重点实验室;
【基金】：国家自然科学基金(No.41271456)
【分类号】：TP391.41
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