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Visible and infrared image fusion technique using advance fuzzy set theory

机译:基于高级模糊集理论的可见光与红外图像融合技术

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Image fusion is the process of combining two or more images acquired from different image sensors into a single image which is advantageous for advance image processing assignments. In this work we present a new fusion method using fuzzy sets (FSs) that combine two or more images by using maximum, minimum operations in fuzzy images. In the processing stage, images are transformed into fuzzy images (FIs) in fuzzy plane. Fuzziness is applied to find the optimal value of the parameters of the fuzzy membership grades. The resulting FIs are fragmented into different fuzzy images depending on the range of dynamic intensity level. The partitioned fuzzy images are combined to find the optimal membership grade from partitioned fuzzy images and finally, fused image is obtained by defuzzification method. The experimental analysis shows that proposed method resolves the spectral distortion problems while preserving the spatial information and establishes that the proposed technique is outperforming all other state-of-the-art techniques in image fusion.
机译:图像融合是将从不同图像传感器获取的两个或更多个图像组合成单个图像的过程,该图像对于预先图像处理分配是有利的。在这项工作中,我们介绍了一种使用模糊集(FSS)的新融合方法,通过使用模糊图像中的最大值,最小的最小操作来组合两个或多个图像。在处理阶段,图像在模糊平面中转换为模糊图像(FIS)。应用模糊,以找到模糊隶属等级参数的最佳值。由此产生的FIS根据动态强度水平的范围分段为不同的模糊图像。组合分区模糊图像以找到从分区模糊图像的最佳成员资格等级,最后,通过排出方法获得融合图像。实验分析表明,所提出的方法解决了光谱失真问题,同时保留了空间信息,并确定所提出的技术在图像融合中的所有其他最先进的技术表现出。

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