基于直觉模糊集和CLAHE红外舰船图像增强算法

Based on intuitionistic fuzzy set and CLAHE infrared ship image enhancement algorithm

复杂环境下海面舰船的红外图像会存在细节模糊、信噪比低的问题。为能更好突显舰船目标,针对上述问题,提出了基于直觉模糊集(Intuitional Fuzzy Set)和对比度受限的自适应直方图均衡(CLAHE)的IFS-CLAHE红外舰船图像增强方法。该算法基于引导滤波对图像进行分层处理,获得基本层和细节层,对细节层先采用迭代非局部均值滤波进行去噪,提出新的基于直觉模糊集增强细节层图像的细节;基本层图像经过CLAHE算法处理来改善对比度,得到新的基本层,将基本层同细节层进行加权融合,使得红外图像质量得到提升。经实验证实,本文算法针对弱小舰船目标增强效果更突出,背景抑制能力以及对比度提升效果较好。

In complex environment,infrared images of sea surface ships have problems of fuzzy details and low signal-to-noise ratio.In order to better highlight ship targets,an IFS-CLAHE infrared ship image enhancement method based on Intuitive Fuzzy Set and contrast limited adaptive histogram equalization(CLAHE)was proposed.The image was layered based on guided filtering and getting the basic and detail layers.The detail layer was denoised by iterative non-local mean filtering.A new method based on intuitionistic fuzzy set was proposed to enhance the detail of detail layer image.The basic layer image was processed by CLAHE algorithm to improve the contrast.The basic layer and the detail layer were weighted and fused.Experimental verification shows that the proposed algorithm has better enhancement effect for small and weak ship targets,and better background suppression ability and contrast enhancement effect.