基于多尺度多直方图融合的红外图像增强映射方法

An Infrared Image Enhancement Mapping Method Based on Multi-scale Multi-histogram Fusion

如何在尽可能地保留原始图像信息的同时,将红外探测器采集到的高动态范围(HDR)数据压缩成细节突出、对比度高、背景噪声小的可观测低动态范围图像,一直是红外技术研究的一个难点。针对此问题,提出了基于多尺度多直方图映射融合的红外图像增强映射方法,该方法首先采用全局线性变换和多尺度窗口的CLAHE对HDR红外图像进行分别映射,再基于局部显著度和动态范围特征自适应计算权重,完成多直方图映射结果融合以解决场景适应性问题,同时在权值计算中利用引导滤波优化融合权重,最后通过灰度域的高斯核函数实现自适应细节增强。实验结果表明,与其他方法相比,所提方法能有效增强图像对比度、丰富图像细节、降低背景噪声,且具有较强的场景适应能力。

How to compress the High Dynamic Range(HDR)data collected by the infrared detector into the observable low-dynamic range image with outstanding details,high contrast and low background noise while retaining the original image information as much as possible has always been a difficult aspect of infrared technology.In order to solve this problem,an infrared image enhancement mapping method based on the fusion of multi-scale multi-histogram mapping results is proposed.Firstly,the global linear transform and the multi-scale window CLAHE are used to map the HDR infrared image separately,and then adaptive weight calculation is conducted based on local saliency and dynamic-range features,and the multi-histogram mapping results are fused to solve the scene adaptability problem.At the same time,the fusion weight is optimized by using guided filtering in the weight calculation,and finally the adaptive detail enhancement is realized by using the Gaussian kernel function in the gray domain.The experimental results show that,compared with other methods,the proposed method can effectively enhance the image contrast,enrich the image details and reduce the background noise,and has strong scene adaptability.